CN105551347B - A kind of intelligent mathematical teaching probability learning device - Google Patents
A kind of intelligent mathematical teaching probability learning device Download PDFInfo
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Abstract
The invention discloses a kind of intelligent mathematical teaching probability learning devices, including cabinet, test ball, pitching hole, collect ball, partition, baffle, motor, power supply device, display device, follower, conveyer belt, photoelectric sensor and counter, the middle upper end of cabinet is provided with pitching hole, the middle lower end of cabinet is provided with collection ball, partition is arranged in box house, partition is spaced substantially equidistant, intermediate space only can be by testing ball, partition between every row mutually staggers, baffle is provided on the outside of partition, the upper left corner of cabinet is arranged in motor, motor lower end is provided with power supply device, display device is embedded in the upper right side of cabinet, undermost partition, a photoelectric sensor is provided between every two, the output end of photoelectric sensor is connected with counter, the output end of counter is connected with display device.The present invention solves the problems, such as operation, count and records integrated, student can be helped to understand random chance, so that it is preferably learnt.
Description
Technical field
The invention belongs to teaching apparatus for mathematics field more particularly to a kind of intelligent mathematical teaching probability learning devices.
Background technique
Probability and mathematical statistics are an important subjects, are played an important role in middle school mathematics quality-oriented education.And it is general
Rate and statistics have the characteristics that abstractness, and being conducive to student by means of certain teaching aid, intuitively to observe probability phenomenal research random
Event, this has middle-school mathematics teaching outstanding meaning.Current Probability Teaching apparatus is less and is mostly manual operation and system
Meter, using trouble low efficiency.
Summary of the invention
The purpose of the present invention is to provide a kind of intelligent mathematical teaching probability learning devices, it is intended to solve current probability religion
It is less and be mostly manual operation and statistics to learn apparatus, the problem of using trouble low efficiency.
The invention is realized in this way a kind of intelligent mathematical teaching probability learning device, intelligent mathematical teaching is with generally
Rate learning device includes cabinet, experiment ball, pitching hole, collection ball, partition, baffle, motor, power supply device, display device, passive
Wheel, conveyer belt, photoelectric sensor and counter；
The middle upper end of the cabinet is provided with pitching hole, and the middle lower end of the cabinet is provided with collection ball, institute
State partition be arranged in the box house, the partition is spaced substantially equidistant, intermediate space only can by test ball, every row it
Between partition mutually stagger, be provided with baffle on the outside of the partition, the upper left corner of the cabinet, the electricity is arranged in the motor
Machine lower end is provided with power supply device, and the display device is embedded in the upper right side of the cabinet, undermost partition, every two it
Between be provided with a photoelectric sensor, the output end of the photoelectric sensor is connected with counter, the output end of the counter
It is connected with the display device；The photoelectric sensor is provided with pre-position, and there are identification modules and synchronized orthogonal frequency hopping
Signal blind source separating module；
The experiment ball is baton round, and baton round is dimensioned slightly smaller than partition room away from, the power supply device circumscripted power line,
The power supply line connects attaching plug, and the power supply device includes power supply connecting device, electrical storage device and protective relaying device, institute
State the power supply input circuit that power supply connecting device includes at least one connection external power supply and the load of at least one connection load
Output circuit, the electrical storage device include the accumulator charging/discharging circuit for connecting battery, and described device is tablet computer, described
Follower includes the first follower and the second follower；The power supply device is connect with photo-voltaic power supply；The photo-voltaic power supply setting
There is extremum search module；
First follower is arranged on the left of the pitching hole, and the second follower setting is left in the collection ball
Side, first follower and the second follower drive the conveyer belt to link together by the motor；The conveyer belt
Outside is provided with support plate, and the support plate is perpendicular to transmission zone face installation；The photoelectric sensor includes: the light for emitting light
Source；First photoelectric detector and the second photoelectric detector；With the first receiving lens of the first photoelectric detector positioned adjacent；
With the second receiving lens of the second photoelectric detector positioned adjacent；For dependently of each other supporting the light source, the first electricity
The support construction of detector and the second photoelectric detector and the first receiving lens and the second receiving lens；
The counter is a positive integer to export the count value with N number of, N, which includes:
State determining means receives the count value instantly to calculate next count value of the counter, wherein should
Count value has a high-order segment count and a low level segment count；
Numerical analysis unit, receive and output one resetting count value, compare the resetting count value and a delay period value with
Export a numerical value comparison signal；
Count comparing unit, receive a clock signal, according to the numerical value compare signal deciding using a first comparator or
One second comparator, and reset signal is counted to the state determining means according to comparison result and clock signal output one with weight
The count value is set, the digit of the first comparator is less than second comparator；
State buffer unit receives the clock signal and next count value, according under clock signal output
One count value is as the count value instantly.
Further, there are the implementation methods of identification module for the pre-position includes:
S1, from source emissioning light with by be located at pre-position target reflected；
S2, first passed through after the first receiving lens that emitted and reflection light is received by the first photoelectric detector
Point；
S3, second passed through after the second receiving lens that emitted and reflection light is received by the second photoelectric detector
Point；
S4, the first quantization that the first part for indicating emitted light is generated using first photoelectric detector are believed
Number；
S5, the second quantization that the second part for indicating emitted light is generated using second photoelectric detector are believed
Number；
S6, composite signal, the compound letter are generated based on both first quantized signal and second quantized signal
Number instruction target the pre-position presence.
Further, the implementation method of the extremum search module includes:
Step 1, first initialization current disturbing amount Δ I (k), wherein k is the number of iterations, takes Δ I (k)=0.05Isc,
Isc is photovoltaic array short circuit current；
Step 2 measures current photovoltaic array exit potential Vpv(k), photovoltaic array exports electric current Ipv(k) and solar irradiation
Intensity S；
Step 3 calculates current photovoltaic array output power Ppv(k)=Vpv(k)×Ipv(k)；
Step 4 verifies current photovoltaic array outlet electric current Ipv(k) whether meet operation constraint condition, constraint condition is such as
Under: 2IMPP-Isc≤Ipv(k)≤Isc, wherein IMPPIt is gone to step for the outlet electric current under maximum power if constraint condition meets
Five enter current disturbing operator；If constraint condition is unsatisfactory for, goes to step eight and enter self adaptive control operator；
Step 5, current disturbing operator, based on classical perturbation observation method；Finally obtain reference current Iref=Ipv(k)+
sign(Ipv(k)-Ipv(k-1))*sign(Ppv(k)-Ppv(k-1)) * Δ I (k), while updating Ppv(k-1)=Ppv(k)、Ipv(k-
1)=Ipv(k)；
Step 6, variable step disturbing operator realize that dynamic regulation disturbs step-length, and realization reduces near maximum power point disturbs
The effect of dynamic step-length, variable step regulated quantity areWherein enable m1+m2=1, according to Practical Project
Middle selection, uses m1=0.6, m2=0.4, other M=sign (Ppv(k)-Ppv(k-1))+sign(Ppv(k-1)-Ppv(k-2))；
Step 7 updates Δ I (k)=Δ IF, return step two；
Step 8, self adaptive control operator are disturbed according to the mutation of Intensity of the sunlight with reference to short circuit current method dynamic regulation
Dynamic step-length increases disturbance step-length and quickly approaches maximum power point, improves extreme value and track efficiency, reference current and adaptive step tune
Specific calculating is as follows respectively for section amount:
Wherein Snom, Tnom, Isc(Snom, Tnom) it is respectively intensity of illumination under standard test condition, temperature and by them
Determining photovoltaic panel short circuit current function, KAFor photovoltaic panel aging life-span correction factor, empirical value 0.55, k is takenscFor photo-voltaic power supply
Extreme value tracks short circuit current method ratio system, takes 0.78~0.92, average value 0.85, S is current Intensity of the sunlight, and N is light
Photovoltaic panel quantity in photovoltaic array；
Step 9 updates Ppv(k-1)=Ppv(k)、Ipv(k-1)=Ipv(k)、Ipv(k)=Iref, Δ I (k)=Δ IC, return
Return step 2；
Step 10, as Δ PpvWhen=0, then current photovoltaic array operates on new maximum power point, and calculation process terminates.
Further, the synchronized orthogonal Frequency Hopping Signal blind source separating module implementation method the following steps are included:
Step 1 is believed using the array antenna received containing M array element from the frequency hopping of multiple synchronized orthogonal frequency hopping radio sets
Number, it is sampled to per reception signal all the way, the road the M discrete time-domain mixed signal after being sampled
Step 2 carries out overlapping adding window Short Time Fourier Transform to the road M discrete time-domain mixed signal, obtains M mixing letter
Number time-frequency domain matrix Wherein NfftIt indicates
The length of FFT transform, p indicate adding window number；(p, q) indicates time-frequency index, and specific time-frequency value is
Here NfftIndicate the length of FFT transform, p indicates adding window number, TsIndicate sampling interval, fsIndicate sample frequency, C is Fu in short-term
In leaf transformation adding window interval sampling number, C < Nfft, and Kc=Nfft/ C is integer, that is to say, that using overlapping adding window
Short Time Fourier Transform；
Step 3, to frequency-hopping mixing signal time-frequency domain matrix obtained in step 2
It is pre-processed；
To frequency-hopping mixing signal time-frequency domain matrixPre-processed, specifically include as
Lower two steps:
The first step is rightLow energy is carried out to pre-process, i.e., in each sampling instant p,
It willValue of the amplitude less than thresholding ε sets 0, obtains
The setting of thresholding ε can be determined according to the average energy for receiving signal；
Second step finds out the time-frequency numeric field data of p moment (p=0,1,2 ... P-1) non-zero, usesIt indicates, whereinIndicate the response of p moment time-frequency
Corresponding frequency indices when non-zero normalize these non-zeros and pre-process, obtain pretreated vector b (p, q)=[b1
(p, q), b2(p, q) ..., bM(p, q)]T, wherein
Step 4 estimates the jumping moment of each jump using clustering algorithm and respectively jumps corresponding normalized hybrid matrix
Column vector, Hopping frequencies；The jumping moment of each jump is estimated using clustering algorithm and respectively jumps corresponding normalized mixed moment
When array vector, Hopping frequencies, comprising the following steps:
The first step, p (p=0,1,2 ... P-1) moment,Indicate the response of p moment time-frequencyCorresponding frequency indices when non-zero,The frequency values of expression are clustered, and what is obtained is poly-
Class Center NumberIndicate carrier frequency number existing for the p moment,A cluster centre then indicates the size of carrier frequency, uses respectivelyIt indicates；
Second step, to each sampling instant p (p=0,1,2 ... P-1), utilize clustering algorithm pairIt is clustered,
It is same availableA cluster centre is usedIt indicates；
Third step, to allIt averages and is rounded, obtain the estimation of source signal numberI.e.
4th step, finds outAt the time of, use phIt indicates, to the p of each section of continuous valuehIntermediate value is sought, is usedIndicate the l sections of p that are connectedhIntermediate value, thenIndicate the estimation at first of frequency hopping moment；
5th step is obtained according to estimation in second stepAnd the 4th estimate to obtain in step
The frequency hopping moment estimate it is each jump it is correspondingA hybrid matrix column vectorSpecific formula are as follows:
HereIndicate that l jumps corresponding mixing
Matrix column vector estimated value；
6th step is estimated the corresponding carrier frequency of each jump, is usedIt is corresponding to indicate that l is jumpedA frequency estimation, calculation formula are as follows:
Step 5 estimates time-frequency domain frequency hopping source signal according to the normalization hybrid matrix column vector that step 4 is estimated；
Time-frequency domain frequency hopping source signal is estimated according to the normalization hybrid matrix column vector estimated in step 4, the specific steps are as follows:
The first step judges which moment index belongs to and jump to all sampling instants index p, method particularly includes: ifThen indicate that moment p belongs to l jump；IfThen indicate that moment p belongs to the 1st
It jumps, whereinFirst of frequency hopping moment estimation；
Second step, all moment p that l (l=1,2 ...) is jumpedl, estimate the time-frequency domain number of each frequency hopping source signal of the jump
According to calculation formula is as follows:
Step 6 splices the time-frequency domain frequency hopping source signal between different frequency hopping points；To between different frequency hopping points
Time-frequency domain frequency hopping source signal is spliced, the specific steps are as follows:
The first step, estimation l jump correspondingA incident angle is usedIndicate l jump n-th of source signal it is corresponding enter
Firing angle degree,Calculation formula it is as follows:
Indicate that l jumps n-th of hybrid matrix column vector that estimation obtainsM-th of element, c indicate the light velocity,
That is c=3 × 108Meter per second, d indicate receiving antenna spacing, useIt is corresponding to indicate that l is jumpedA frequency
Rate estimated value；
Second step judges that l (l=2,3 ...) jumps the source signal of estimation and first and jumps pair between the source signal of estimation
It should be related to, judgment formula is as follows:
Wherein mn (l)Indicate that l jumps the m of estimationn (l)A signal and n-th of signal of the first jump estimation belong to the same source
Signal；
Third step, by different frequency hopping point estimation to the signal for belonging to the same source signal be stitched together, as final
Time-frequency domain source signal estimation, use Yn(p, q) indicates time-frequency domain estimated value of n-th of source signal on time frequency point (p, q), p=
0,1,2 ..., P, q=0,1,2 ..., Nfft- 1, i.e.,
Step 7 restores time domain frequency hopping source signal according to frequency hopping source signal time-frequency domain estimated value；Specific step is as follows:
The first step, to the frequency domain data Y of each sampling instant p (p=0,1,2 ...)n(p, q), q=0,1,2 ...,
Nfft- 1 is NfftThe IFFT transformation of point, obtains the corresponding time domain frequency hopping source signal of p sampling instant, uses yn(p, qt)(qt=0,1,
2 ..., Nfft- 1) it indicates；
Second step, the time domain frequency hopping source signal y obtained to above-mentioned all momentn(p, qt) processing is merged, it obtains final
Time domain frequency hopping source signal estimation, specific formula is as follows:
Here Kc=Nfft/ C, C are the sampling number at Short Time Fourier Transform adding window interval.
Technical effect
Intelligent mathematical teaching provided by the invention is simple with probability learning device overall structure, easy for operation, stablizes
Property good, high reliablity, by being received pitching using conveyer belt, photoelectric sensor automatic target assignment tests ball position, meter
Number device carries out counting statistics, and display device shows counted data automatically, solves operation, counts and record integrated ask
Topic, it is more intuitive to show probability learning to student, facilitate teachers ' teaching to use.The present invention is not knowing any channel information
Under the conditions of, according only to the mixed signal of the multiple Frequency Hopping Signals received, frequency hopping source signal is estimated, it can be in receiving antenna number
Under conditions of source signal number, blind estimate is carried out to multiple Frequency Hopping Signals, with only Short Time Fourier Transform, is calculated
Measure it is small, it is easy to accomplish, this method to Frequency Hopping Signal carry out blind separation while, moreover it is possible to partial parameters are estimated, it is practical
Property is strong, has strong promotion and application value.
Detailed description of the invention
Fig. 1 is intelligent mathematical teaching probability learning apparatus structure schematic diagram provided in an embodiment of the present invention；
Fig. 2 is the structural schematic diagram of power supply device provided in an embodiment of the present invention；
Fig. 3 is the structural schematic diagram of photoelectric sensor provided in an embodiment of the present invention；
Fig. 4 be photoelectric sensor provided in an embodiment of the present invention be used for detect target pre-position there are methods
Flow diagram；
Fig. 5 is the structural schematic diagram of counter provided in an embodiment of the present invention.
In figure: 1, cabinet；2, ball is tested；3, pitching hole；4, collect ball；5, partition；6, baffle；7, motor；8, power supply fills
It sets；8-1, power supply connecting device；8-2, electrical storage device；8-3, protective relaying device；9, display device；10, follower；10-1,
First follower；10-2, the second follower；11, conveyer belt；12, photoelectric sensor；12-1, light source；12-2, the inspection of the first photoelectricity
Survey device；12-3, the second photoelectric detector；12-4, the first receiving lens；12-5, the second receiving lens；12-6, support construction；
13, counter；13-1, state determining means；13-2, numerical analysis unit, 13-3, comparing unit is counted；13-4, state buffer
Unit；14, power supply line；15, attaching plug.
Specific embodiment
In order to make the objectives, technical solutions, and advantages of the present invention clearer, with reference to embodiments, to the present invention
It is further elaborated.It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, it is not used to
Limit the present invention.
With reference to the accompanying drawing and specific embodiment is further described application principle of the invention.
As shown in Figure 1-Figure 3, the intelligent mathematical teaching probability learning device of the embodiment of the present invention includes cabinet 1, experiment
Ball 2, pitching hole 3, collection ball 4, partition 5, baffle 6, motor 7, power supply device 8, display device 9, follower 10, conveyer belt 11,
Photoelectric sensor 12 and counter 13, the middle upper end of the cabinet 1 are provided with pitching hole 3, under the middle of the cabinet 1
End is provided with collection ball 4, and the partition 5 is arranged inside the cabinet 1, and the partition 5 is spaced substantially equidistant, intermediate space
Only can be by testing ball 2, the partition 5 between every row mutually staggers, and baffle 6 is provided on the outside of the partition 5, the motor 7 is set
It sets in the upper left corner of the cabinet 1,7 lower end of motor is provided with power supply device 8, and the display device 9 is embedded in the case
The upper right side of body 1, undermost partition 5 are provided with a photoelectric sensor 12 between every two, the photoelectric sensor 12
Output end is connected with counter 13, and the output end of the counter 13 is connect with the display device phase 9, the power supply device 8
It is connect with photo-voltaic power supply；The photoelectric sensor 12 is provided with pre-position, and there are identification modules and synchronized orthogonal Frequency Hopping Signal
Blind source separating module, the photo-voltaic power supply are provided with extremum search module.
Further, the experiment ball 2 is baton round, and baton round is dimensioned slightly smaller than 5 spacing of partition.
Further, 8 circumscripted power line 14 of power supply device, the power supply line 14 connect attaching plug 15.
Further, the power supply device 8 includes power supply connecting device 8-1, electrical storage device 8-2 and protective relaying device 8-
3。
Further, the power supply connecting device 8-1 include at least one connection external power supply power supply input circuit and
The load output circuit of at least one connection load.
Further, the electrical storage device 8-2 includes the accumulator charging/discharging circuit for connecting battery.
Further, the display device 9 is tablet computer.
Further, the follower 10 includes the first follower 10-1 and the second follower 10-2.
Further, first follower 10-1 setting is in 3 left side of pitching hole, the second follower 10-2
Setting passes through the motor 7 drive institute in 4 left side of collection ball, the first follower 10-1 and the second follower 10-2
Conveyer belt 11 is stated to link together.
Further, support plate is provided with outside the conveyer belt 11, the support plate is perpendicular to transmission zone face installation.
Further, the photoelectric sensor 12 includes:
Emit the light source 12-1 of light；
First photoelectric detector 12-2 and the second photoelectric detector 12-3；
With the first receiving lens 12-4 of the first photoelectric detector 12-2 positioned adjacent；
With the second receiving lens 12-5 of the second photoelectric detector 12-3 positioned adjacent；
For dependently of each other supporting the light source 12-1, the first photoelectric detector 12-2 and the second photoelectric detector 12-3
And first receiving lens 12-4 and the second receiving lens 12-5 support construction 12-6.
Further, as shown in figure 5, the counter 13 is to export the count value with N number of, N is just whole for one
Number, the counter 13 include:
State determining means 13-1, receives the count value instantly to calculate next count value of the counter,
In the count value there is a high-order segment count and a low level segment count；
Numerical analysis unit 13-2, receives and output one resets count value, compares the resetting count value and a delay period
Value is to export a numerical value comparison signal；
Comparing unit 13-3 is counted, a clock signal is received, compares signal deciding according to the numerical value and compare using one first
Device or one second comparator, and reset signal is counted to the state determining means according to comparison result and clock signal output one
To reset the count value, the digit of the first comparator is less than second comparator；
State buffer unit 13-4 receives the clock signal and next count value, with defeated according to the clock signal
Next count value is as the count value instantly out.
As shown in figure 4, there are the implementation methods of identification module for the pre-position includes:
S1, from source emissioning light with by be located at pre-position target reflected；
S2, first passed through after the first receiving lens that emitted and reflection light is received by the first photoelectric detector
Point；
S3, second passed through after the second receiving lens that emitted and reflection light is received by the second photoelectric detector
Point；
S4, the first quantization that the first part for indicating emitted light is generated using first photoelectric detector are believed
Number；
S5, the second quantization that the second part for indicating emitted light is generated using second photoelectric detector are believed
Number；
S6, composite signal, the compound letter are generated based on both first quantized signal and second quantized signal
Number instruction target the pre-position presence.
Further, the implementation method of the extremum search module includes:
Step 1, first initialization current disturbing amount Δ I (k), wherein k is the number of iterations, takes Δ I (k)=0.05Isc,
Isc is photovoltaic array short circuit current；
Step 2 measures current photovoltaic array exit potential Vpv(k), photovoltaic array exports electric current Ipv(k) and solar irradiation
Intensity S；
Step 3 calculates current photovoltaic array output power Ppv(k)=Vpv(k)×Ipv(k)；
Step 4 verifies current photovoltaic array outlet electric current Ipv(k) whether meet operation constraint condition, constraint condition is such as
Under: 2IMPP-Isc≤Ipv(k)≤Isc, wherein IMPPIt is gone to step for the outlet electric current under maximum power if constraint condition meets
Five enter current disturbing operator；If constraint condition is unsatisfactory for, goes to step eight and enter self adaptive control operator；
Step 5, current disturbing operator, based on classical perturbation observation method；Finally obtain reference current Iref=Ipv(k)+
sign(Ipv(k)-Ipv(k-1))*sign(Ppv(k)-Ppv(k-1)) * Δ I (k), while updating Ppv(k-1)=Ppv(k)、Ipv(k-
1)=Ipv(k)；
Step 6, variable step disturbing operator realize that dynamic regulation disturbs step-length, and realization reduces near maximum power point disturbs
The effect of dynamic step-length, variable step regulated quantity areWherein enable m1+m2=1, according to Practical Project
Middle selection, uses m1=0.6, m2=0.4, other M=sign (Ppv(k)-Ppv(k-1))+sign(Ppv(k-1)-Ppv(k-2))；
Step 7 updates Δ I (k)=Δ IF, return step two；
Step 8, self adaptive control operator are disturbed according to the mutation of Intensity of the sunlight with reference to short circuit current method dynamic regulation
Dynamic step-length increases disturbance step-length and quickly approaches maximum power point, improves extreme value and track efficiency, reference current and adaptive step tune
Specific calculating is as follows respectively for section amount:
Wherein Snom, Tnom, Isc(Snom, Tnom) it is respectively intensity of illumination under standard test condition, temperature and by them
Determining photovoltaic panel short circuit current function, KAFor photovoltaic panel aging life-span correction factor, empirical value 0.55, k is takenscFor photo-voltaic power supply
Extreme value tracks short circuit current method ratio system, takes 0.78~0.92, average value 0.85, S is current Intensity of the sunlight, and N is light
Photovoltaic panel quantity in photovoltaic array；
Step 9 updates Ppv(k-1)=Ppv(k)、Ipv(k-1)=Ipv(k)、Ipv(k)=Iref, Δ I (k)=Δ IC, return
Return step 2；
Step 10, as Δ PpvWhen=0, then current photovoltaic array operates on new maximum power point, and calculation process terminates.
Further, the synchronized orthogonal Frequency Hopping Signal blind source separating module implementation method the following steps are included:
Step 1 is believed using the array antenna received containing M array element from the frequency hopping of multiple synchronized orthogonal frequency hopping radio sets
Number, it is sampled to per reception signal all the way, the road the M discrete time-domain mixed signal after being sampled
Step 2 carries out overlapping adding window Short Time Fourier Transform to the road M discrete time-domain mixed signal, obtains M mixing letter
Number time-frequency domain matrixP=0,1 ... P-1, q=0,1 ... Nfft- 1 wherein NfftTable
Show the length of FFT transform, p indicates adding window number；(p, q) indicates time-frequency index, and specific time-frequency value isHere NfftIndicate the length of FFT transform, p indicates adding window number, TsIndicate sampling interval, fsExpression is adopted
Sample frequency, C are the sampling number at Short Time Fourier Transform adding window interval, C < Nfft, and Kc=Nfft/ C is integer, that is to say, that
Using the Short Time Fourier Transform of overlapping adding window；
Step 3, to frequency-hopping mixing signal time-frequency domain matrix obtained in step 2
It is pre-processed；
To frequency-hopping mixing signal time-frequency domain matrixPre-processed, specifically include as
Lower two steps:
The first step is rightLow energy is carried out to pre-process, i.e., in each sampling instant p,
It willValue of the amplitude less than thresholding ε sets 0, obtains
The setting of thresholding ε can be determined according to the average energy for receiving signal；
Second step finds out the time-frequency numeric field data of p moment (p=0,1,2 ... P-1) non-zero, usesIt indicates, whereinIndicate the response of p moment time-frequency
Corresponding frequency indices when non-zero normalize these non-zeros and pre-process, obtain pretreated vector b (p, q)=[b1
(p, q), b2(p, q) ..., bM(p, q)]T, wherein
Step 4 estimates the jumping moment of each jump using clustering algorithm and respectively jumps corresponding normalized hybrid matrix
Column vector, Hopping frequencies；The jumping moment of each jump is estimated using clustering algorithm and respectively jumps corresponding normalized mixed moment
When array vector, Hopping frequencies, comprising the following steps:
The first step, p (p=0,1,2 ... P-1) moment,Indicate the response of p moment time-frequencyCorresponding frequency indices when non-zero,The frequency values of expression are clustered, and what is obtained is poly-
Class Center NumberIndicate carrier frequency number existing for the p moment,A cluster centre then indicates the size of carrier frequency, uses respectivelyIt indicates；
Second step, to each sampling instant p (p=0,1,2 ... P-1), utilize clustering algorithm pairIt is clustered,
It is same availableA cluster centre is usedIt indicates；
Third step, to allIt averages and is rounded, obtain the estimation of source signal numberI.e.
4th step, finds outAt the time of, use phIt indicates, to the p of each section of continuous valuehIntermediate value is sought, is usedIndicate the l sections of p that are connectedhIntermediate value, thenIndicate the estimation at first of frequency hopping moment；
5th step is obtained according to estimation in second stepAnd the 4th estimate to obtain in step
The frequency hopping moment estimate it is each jump it is correspondingA hybrid matrix column vectorSpecific formula are as follows:
HereIndicate that l jumps corresponding mixing
Matrix column vector estimated value；
6th step is estimated the corresponding carrier frequency of each jump, is usedIt is corresponding to indicate that l is jumpedA frequency estimation, calculation formula are as follows:
Step 5 estimates time-frequency domain frequency hopping source signal according to the normalization hybrid matrix column vector that step 4 is estimated；
Time-frequency domain frequency hopping source signal is estimated according to the normalization hybrid matrix column vector estimated in step 4, the specific steps are as follows:
The first step judges which moment index belongs to and jump to all sampling instants index p, method particularly includes: ifThen indicate that moment p belongs to l jump；IfThen indicate that moment p belongs to the 1st
It jumps, whereinFirst of frequency hopping moment estimation；
Second step estimates the time-frequency domain number of each frequency hopping source signal of the jump to all moment pl that l (l=1,2 ...) is jumped
According to calculation formula is as follows:
Step 6 splices the time-frequency domain frequency hopping source signal between different frequency hopping points；To between different frequency hopping points
Time-frequency domain frequency hopping source signal is spliced, the specific steps are as follows:
The first step, estimation l jump correspondingA incident angle is usedIndicate l jump n-th of source signal it is corresponding enter
Firing angle degree,Calculation formula it is as follows:
Indicate that l jumps n-th of hybrid matrix column vector that estimation obtainsM-th of element, c indicate the light velocity,
That is c=3 × 108Meter per second, d indicate receiving antenna spacing, useIt is corresponding to indicate that l is jumpedA frequency
Rate estimated value；
Second step judges that l (l=2,3 ...) jumps the source signal of estimation and first and jumps pair between the source signal of estimation
It should be related to, judgment formula is as follows:
Wherein mn (l)Indicate that l jumps the m of estimationn (l)A signal and n-th of signal of the first jump estimation belong to the same source
Signal；
Third step, by different frequency hopping point estimation to the signal for belonging to the same source signal be stitched together, as final
Time-frequency domain source signal estimation, use Yn(p, q) indicates time-frequency domain estimated value of n-th of source signal on time frequency point (p, q), p=
0,1,2 ..., P, q=0,1,2 ..., Nfft- 1, i.e.,
Step 7 restores time domain frequency hopping source signal according to frequency hopping source signal time-frequency domain estimated value；Specific step is as follows:
The first step, to the frequency domain data Y of each sampling instant p (p=0,1,2 ...)n(p, q), q=0,1,2 ...,
Nfft- 1 is NfftThe IFFT transformation of point, obtains the corresponding time domain frequency hopping source signal of p sampling instant, uses yn(p, qt)(qt=0,1,
2 ..., Nfft- 1) it indicates；
Second step, the time domain frequency hopping source signal y obtained to above-mentioned all momentn(p, qt) processing is merged, it obtains final
Time domain frequency hopping source signal estimation, specific formula is as follows:
Here Kc=Nfft/ C, C are the sampling number at Short Time Fourier Transform adding window interval.
Teacher first passes through power supply line 14 with attaching plug 15 and connects electricity when with intelligent mathematical teaching probability learning device
Source sets required throwing number by display device 9, and then motor 7 drives conveyer belt 11 to rotate, and conveyer belt 11 can
Take experiment ball 2 to pitching hole 3 from collection ball 4, experiment ball 2 will be fallen into immediately in undermost 5 gap of partition, pass through photoelectricity
Sensor 12 perceives and records the number that each experiment ball 2 passes through 5 gap of partition by counter 13, counts by mass data
Afterwards, student is allowed to record data, teacher carries out Probability teaching to student.
The foregoing is merely illustrative of the preferred embodiments of the present invention, is not intended to limit the invention, all in essence of the invention
Made any modifications, equivalent replacements, and improvements etc., should all be included in the protection scope of the present invention within mind and principle.
Claims (4)
1. a kind of intelligent mathematical teaching probability learning device, which is characterized in that intelligent mathematical teaching probability learning device
Including cabinet, experiment ball, pitching hole, collection ball, partition, baffle, motor, power supply device, display device, follower, conveyer belt,
Photoelectric sensor and counter；
The middle upper end of the cabinet is provided with pitching hole, and the middle lower end of the cabinet is provided with collection ball, it is described every
Plate is arranged in the box house, and the partition is spaced substantially equidistant, and intermediate space only can be by testing ball, between every row
Partition mutually staggers, and is provided with baffle on the outside of the partition, and the motor is arranged in the upper left corner of the cabinet, under the motor
End is provided with power supply device, and the display device is embedded in the upper right side of the cabinet, undermost partition, sets between every two
It is equipped with a photoelectric sensor, the output end of the photoelectric sensor is connected with counter, the output end of the counter and institute
Display device is stated to be connected；The photoelectric sensor is provided with pre-position, and there are identification modules and synchronized orthogonal Frequency Hopping Signal
Blind source separating module；
The experiment ball is baton round, and baton round is dimensioned slightly smaller than partition room away from the power supply device circumscripted power line is described
Power supply line connects attaching plug, and the power supply device includes power supply connecting device, electrical storage device and protective relaying device, the electricity
Source attachment device includes the power supply input circuit of at least one connection external power supply and the load output of at least one connection load
Circuit, the electrical storage device include the accumulator charging/discharging circuit for connecting battery, and the display device is tablet computer, described
Follower includes the first follower and the second follower；The power supply device is connect with photo-voltaic power supply；The photo-voltaic power supply setting
There is extremum search module；
First follower is arranged on the left of the pitching hole, and second follower is arranged on the left of the collection ball, institute
It states the first follower and the second follower and drives the conveyer belt to link together by the motor；It is set outside the conveyer belt
It is equipped with support plate, the support plate is perpendicular to transmission zone face installation；The photoelectric sensor includes: the light source for emitting light；The
One photoelectric detector and the second photoelectric detector；With the first receiving lens of the first photoelectric detector positioned adjacent；With institute
State the second receiving lens of the second photoelectric detector positioned adjacent；For dependently of each other supporting the light source, the inspection of the first photoelectricity
Survey the support construction of device and the second photoelectric detector and the first receiving lens and the second receiving lens；
The counter is a positive integer to export the count value with N number of, N, which includes:
State determining means, receives the count value instantly to calculate next count value of the counter, the wherein counting
Value has a high-order segment count and a low level segment count；
Numerical analysis unit, receives and output one resets count value, compares the resetting count value and a delay period value to export
One numerical value comparison signal；
Comparing unit is counted, a clock signal is received, compares signal deciding according to the numerical value and uses a first comparator or one the
Two comparators, and reset signal is counted to the state determining means according to comparison result and clock signal output one to reset this
The digit of count value, the first comparator is less than second comparator；
State buffer unit receives the clock signal and next count value, next to export according to the clock signal
The count value as the count value instantly.
2. intelligent mathematical teaching probability learning device as described in claim 1, which is characterized in that the pre-position exists
The implementation method of identification module includes:
S1, from source emissioning light with by be located at pre-position target reflected；
S2, the first part passed through after the first receiving lens that emitted and reflection light is received by the first photoelectric detector；
S3, the second part passed through after the second receiving lens that emitted and reflection light is received by the second photoelectric detector；
S4, the first quantized signal for indicating the first part of emitted light is generated using first photoelectric detector；
S5, the second quantized signal for indicating the second part of emitted light is generated using second photoelectric detector；
S6, composite signal is generated based on both first quantized signal and second quantized signal, the composite signal refers to
Show target in the presence of the pre-position.
3. intelligent mathematical teaching probability learning device as described in claim 1, which is characterized in that the extremum search module
Realization includes:
Step 1, first initialization current disturbing amount Δ I (k), wherein k is the number of iterations, takes Δ I (k)=0.05Isc, the Isc to be
Photovoltaic array short circuit current；
Step 2 measures current photovoltaic array exit potential Vpv(k), photovoltaic array exports electric current Ipv(k) and Intensity of the sunlight
S；
Step 3 calculates current photovoltaic array output power Ppv(k)=Vpv(k)×Ipv(k)；
Step 4 verifies current photovoltaic array outlet electric current Ipv(k) whether meet operation constraint condition, constraint condition is as follows:
2IMPP-Isc≤Ipv(k)≤Isc, wherein IMPPFor the outlet electric current under maximum power, if constraint condition meets, go to step five into
Enter current disturbing operator；If constraint condition is unsatisfactory for, goes to step eight and enter self adaptive control operator；
Step 5, current disturbing operator, based on classical perturbation observation method；Finally obtain reference current I ref=Ipv(k)+sign
(Ipv(k)-Ipv(k-1))*sign(Ppv(k)-Ppv(k-1)) * Δ I (k), while updating Ppv(k-1)=Ppv(k)、Ipv(k-1)=
Ipv(k)；
Step 6, variable step disturbing operator realize that dynamic regulation disturbs step-length, realize and reduce disturbance step near maximum power point
Long effect, variable step regulated quantity areM1+m2=1 is wherein enabled, is selected according in Practical Project,
Use m1=0.6, m2=0.4, other M=sign (Ppv(k)-Ppv(k-1))+sign(Ppv(k-1)-Ppv(k-2))；
Step 7 updates Δ I (k)=Δ IF, return step two；
Step 8, self adaptive control operator are disturbed with reference to short circuit current method dynamic regulation and are walked according to the mutation of Intensity of the sunlight
It is long, increase disturbance step-length and quickly approach maximum power point, improves extreme value and track efficiency, reference current and adaptive step regulated quantity
Specific calculating is as follows respectively:
Wherein Snom, Tnom, Isc (Snom, Tnom) are respectively intensity of illumination under standard test condition, temperature and by them
Determining photovoltaic panel short circuit current function, K A are photovoltaic panel aging life-span correction factor, take empirical value 0.55, and k sc is photovoltaic
Power supply extreme value tracks short circuit current method ratio system, takes 0.78~0.92, average value 0.85, S is current Intensity of the sunlight, N
For photovoltaic panel quantity in photovoltaic array；
Step 9 updates Ppv(k-1)=Ppv(k)、Ipv(k-1)=Ipv(k)、Ipv(k)=Irev, Δ I (k)=Δ IC, return to step
Rapid two；Wherein IrevFor the electric current after change；
Step 10, as Δ PpvWhen=0, then current photovoltaic array operates on new maximum power point, and calculation process terminates；ΔPpv
For power change values.
4. intelligent mathematical teaching probability learning device as described in claim 1, which is characterized in that the synchronized orthogonal frequency hopping letter
The implementation method of number blind source separating module the following steps are included:
Step 1, the Frequency Hopping Signal using the array antenna received containing M array element from multiple synchronized orthogonal frequency hopping radio sets, to each
Road receives signal and is sampled, the road the M discrete time-domain mixed signal after being sampled
Step 2 carries out overlapping adding window Short Time Fourier Transform to the road M discrete time-domain mixed signal, obtains M mixed signal
Time-frequency domain matrixWherein NfftTable
Show the length of FFT transform, p indicates adding window number；(p, q) indicates time-frequency index, and specific time-frequency value is,This
In NfftIndicate the length of FFT transform, p indicates adding window number, TsIndicate sampling interval, fsIndicate sample frequency, C is in Fu in short-term
The sampling number at leaf transformation adding window interval, C < Nfft；The length of q expression FFT transform；
Step 3, to frequency-hopping mixing signal time-frequency domain matrix obtained in step 2
It is pre-processed, specifically includes following two step:
The first step is rightLow energy is carried out to pre-process, i.e., it, will in each sampling instant p 'Value of the amplitude less than thresholding ε sets 0, obtains
The setting of thresholding ε can be determined according to the average energy for receiving signal；
Second step finds out p ' moment, p '=0,1,2 ... p ' -1, the time-frequency numeric field data of non-zero, use
It indicates, whereinIndicate the response of p ' moment time-frequencyCorresponding frequency indices, right when non-zero
The normalization pretreatment of these non-zeros, obtains
Pretreated vector b (p, q)=[b1(p, q), b2(p, q) ..., bM(p, q)]T, wherein
Step 4, using clustering algorithm estimate each jump jumping moment and respectively jump corresponding normalized mixed moment array to
Amount, Hopping frequencies the following steps are included:
The first step, in p, p=0,1,2 ... p-1, moment indicate the response of p moment time-frequency
Corresponding frequency indices when non-zero,The frequency values of expression are clustered, obtained cluster centre numberIndicate that the p moment exists
Carrier frequency number,A cluster centre then indicates the size of carrier frequency, uses respectivelyIt indicates；
Indicate that pth jumps 0-n corresponding frequency estimations；
Second step, to each sampling instant p, p=0,1,2 ... p-1 utilizes clustering algorithm pairIt is clustered, equally
It is availableA cluster centre is usedIt indicates；
Third step, to allIt averages and is rounded, obtain the estimation of source signal numberI.e.
4th step, finds outAt the time of, it is indicated with ph, intermediate value is asked to the ph of each section of continuous value, used
Indicate the intermediate value of the connected ph of paragraph 1, thenIndicate the estimation at the 1st frequency hopping moment；
5th step is obtained according to estimation in second stepAnd the 4th estimation in step obtain
It is corresponding that the frequency hopping moment estimates each jumpA hybrid matrix column vectorSpecific formula are as follows:
HereIndicate that the 1st jump is correspondingIt is a mixed
Close matrix column vector estimated value；
6th step is estimated the corresponding carrier frequency of each jump, is usedIndicate that the 1st jump is correspondingA frequency
Rate estimated value, calculation formula are as follows:
Step 5 estimates time-frequency domain frequency hopping source signal according to the normalization hybrid matrix column vector that step 4 is estimated, specifically
Steps are as follows:
The first step judges which moment index belongs to and jump to all sampling instants index p, method particularly includes: ifThen indicate that moment p belongs to the 1st jump；IfThen indicate moment p
Belong to the 1st jump, whereinThe 1st frequency hopping moment estimation；
Second step, all moment p that l (l=1,2 ...) is jumpedl, estimate the time-frequency numeric field data of each frequency hopping source signal of the jump, count
It is as follows to calculate formula:
WhereinIndicate each frequency hopping source signal of the jump
Time-frequency numeric field data；
Step 6 splices the time-frequency domain frequency hopping source signal between different frequency hopping points, the specific steps are as follows:
The first step, estimation l jump correspondingA incident angle is usedIndicate that l jumps the corresponding incidence angle of n-th of source signal
Degree,Calculation formula it is as follows:
Indicate n-th of hybrid matrix column vector that the 1st jump estimation obtainsM-th of element, c indicate the light velocity, i.e. c
=3 × 108Meter per second, d indicate receiving antenna spacing, useIndicate that the 1st jump is correspondingA frequency
Estimated value；
Second step, judges that l (l=2,3 ...) jumps the source signal of estimation and first jumps between the source signal of estimation corresponding closes
System, judgment formula are as follows:
Wherein mn (l)Indicate that l jumps the m of estimationn (l)A signal and n-th of signal of the first jump estimation belong to the same source and believe
Number；
Third step, by different frequency hopping point estimation to the signal for belonging to the same source signal be stitched together, as it is final when
The estimation of frequency domain source signal, uses YnTime-frequency domain estimated value of n-th of the source signal of (p, q) expression on time frequency point (p, q), p=0,1,
2 ..., P, q=0,1,2 ..., Nfft- 1, i.e.,
Wherein Sn(p, q) indicates time-frequency numeric field data of n-th of source signal on time frequency point (p, q)；
Indicate mn (l)Time-frequency numeric field data of a source signal on time frequency point (p, q)；
Step 7 restores time domain frequency hopping source signal according to frequency hopping source signal time-frequency domain estimated value；Specific step is as follows:
The first step, to each sampling instant p, p=0,1,2 ..., frequency domain data Yn(p, q), q=0,1,2 ..., Nfft- 1 does
NfftThe IFFT transformation of point, obtains the corresponding time domain frequency hopping source signal of p sampling instant, uses yn(p, qt) (qt=0,1,2 ...,
Nfft- 1) it indicates；
Second step, the time domain frequency hopping source signal y obtained to above-mentioned all momentn(p, qt) processing is merged, when obtaining final
The estimation of domain frequency hopping source signal, specific formula is as follows:
Here Kc=Nfft/ C, C are the sampling number at Short Time Fourier Transform adding window interval.
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