CN108322857A - A kind of signal processing apparatus - Google Patents
A kind of signal processing apparatus Download PDFInfo
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- CN108322857A CN108322857A CN201810031374.8A CN201810031374A CN108322857A CN 108322857 A CN108322857 A CN 108322857A CN 201810031374 A CN201810031374 A CN 201810031374A CN 108322857 A CN108322857 A CN 108322857A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
- H04R3/00—Circuits for transducers, loudspeakers or microphones
- H04R3/02—Circuits for transducers, loudspeakers or microphones for preventing acoustic reaction, i.e. acoustic oscillatory feedback
Abstract
Embodiment of the present invention is related to field of communication technology, discloses a kind of signal processing apparatus.The signal processing apparatus includes：Signal input part, filter, driver and signal output end；Signal input part is located in filter, and filter is connect with driver, and signal output end is located in driver；Filter by the input signal PDin that signal input part receives for that will carry out pre-filtering processing, and treated that signal is exported to driver by pre-filtering；Driver is used for the energized process to the signal after pre-filtering, and the signal after energized process is exported by signal output end；Wherein, opposite distorted characteristic is presented with the energized process of driver in the pre-filtering processing of filter.The signal processing apparatus, it is easy to operate, and can effectively improve distortion phenomenon.
Description
Technical field
Embodiment of the present invention is related to field of communication technology, more particularly to a kind of signal processing apparatus.
Background technology
With the development of science and technology, various electronic equipments are more and more applied in people’s lives.Driver is as one
Kind harmonic oscillator, is also widely used, for example, in the terminal devices such as smart mobile phone, tablet computer, usually
Screen vibration is driven to realize screen vocal function using driver, and the principle of sound of this screen sounding is：To driver
Input stimulus voltage drives screen vibration, output desired such as sound pressure signal by the vibration of driver.This kind utilizes driver
Carry out sounding mode may be also used in other can vibrate and on the screen of the shell of sounding or other electronic equipments
However, it was found by the inventors of the present invention that driver easy tos produce apparent distortion at work, this is seriously affected
The sound effect generated by driver in the prior art carries out the distortion of driver by physical modeling although also having
The mode of debugging, but its operating process is extremely cumbersome, and be easy effectively improve distortion phenomenon because modeling error is big.
Invention content
Embodiment of the present invention is designed to provide a kind of signal processing apparatus, easy to operate, and can effectively change
Kind distortion phenomenon.
In order to solve the above technical problems, embodiments of the present invention provide a kind of signal processing apparatus, including：Signal is defeated
Enter end, filter, driver and signal output end；Signal input part is located in filter, and filter is connect with driver, signal
Output end is located in driver；Filter by the input signal PDin that signal input part receives for that will carry out pre-filtering
Processing, and treated that signal is exported to driver by pre-filtering；Driver is used for the energized process to the signal after pre-filtering,
And the signal after energized process is exported by signal output end；Wherein, the pre-filtering processing of filter and driver
Opposite distorted characteristic is presented in energized process.
In terms of existing technologies, by before the driver, a filter is arranged in embodiment of the present invention,
And opposite distorted characteristic is presented with the energized process of driver in the pre-filtering processing of the filter, so that input signal
PDin has carried out the once distortion status phase with driver in advance before being distorted in entering driver in filter
Anti- distortion, so that the signal finally exported from driver, after it experienced distortion opposite twice, distortion shows
As can be cancelled out each other, therefore, the distortion effect to output signal is weakened, effectively improving distortion phenomenon, and the behaviour
It is not related to debugging manually, it is easy to operate.
In addition, filter specifically includes：Forward direction module, feedback module and resolving module；Forward direction module is used for according to swashing
The pre-filtering processing model that the distortion of device is modeled is encouraged, is exported after carrying out pre-filtering processing to input signal PDin
To driver；Feedback module is used to obtain the signal of driver output, and the signal that driver exports is fed back to resolving module；
The signal that module is used to export according to driver is resolved to be modified the modeling coefficients w of pre-filtering processing model；Forward direction module
It is additionally operable to update pre-filtering processing model according to revised modeling coefficients w, and passes through updated pre-filtering and handle model pair
Input signal PDin is exported after carrying out pre-filtering processing to driver.It is preceding to module, feedback module by being arranged in filter
With resolve module, and in forward direction module according to pre-filtering handle model to input signal carry out pre-filtering processing, feedback mould
It block and resolves under the cooperation of module, calculates the modeling coefficients w of corresponding input signal PDin, and constantly more by modeling coefficients w
It newly handles in model to the pre-filtering of forward direction module, as a result, in the state that modeling coefficients w is constantly corrected update, recycles
It updates revised modeling coefficients w and pre-filtering processing is carried out to input signal PDin, handled with reaching more accurate pre-filtering
Effect.
In addition, forward direction module is specifically used for carrying out pre-filtering processing to input signal PDin according to following formula：
Wherein,For the distortion of driver, PDin (n+i) is input signal, and z (n+k) is auxiliary modeled terms,
wi,j,k,mFor the corresponding coefficient of spline function, SPLm(| PDin (n+j) |) it is spline function, n is the Duplication of batten, and i, j, k are
Memory depth；Modeled terms z (n) is assisted, just like giving a definition：
Wherein, AP is average power signal, and EVP is signal envelope.
In addition, feedback module, is specifically used for after the signal for obtaining driver output, the signal of removal driver output
Link influences, and the signal for removing the driver output after link influences is fed back to resolving module.From the output signal of driver
In the feedback signal that directly acquires there is the influence of the links such as noise, gain, time delay, therefore, to the feedback signal of acquisition into
It after link of the row removal including noise, gain, time delay etc. influences, then send to resolving in module, is conducive to calculation result
Accurately, finally enable to the processing of the pre-filtering to input signal PDin more accurate.
In addition, forward direction module is additionally operable to before the input signal PDin to next signal segment carries out pre-filtering processing, it is right
Modeling coefficients w carries out initialization process.So set, can be handled by right to avoid to the pre-filtering of each input signal PDin
The influence of upper input signal PDin processing, can make the processing of the pre-filtering to each input signal PDin all relatively independent
And it is accurate.
In addition, each signal segment corresponds to a modeling coefficients storage table；Module is resolved to be additionally operable to exported according to driver
After signal is modified the modeling coefficients w of pre-filtering processing model, revised w is recorded in modeling coefficients storage table；
Forward direction module be additionally operable to search with the modeling coefficients storage table corresponding to current demand signal section, by the w of the last time record, as repairing
Modeling coefficients w after just.
In addition, input signal PDin is digital signal, signal processing apparatus further includes D/A converter module and analog-to-digital conversion
Module, D/A converter module are arranged between forward direction module and driver, and D/A converter module is used to pre-filtering handling model
The signal exported after pre-filtering processing is carried out, digital-to-analogue conversion is carried out, forms the analog signal for transporting to driver；Analog-to-digital conversion module
It is arranged between driver and feedback module, the signal that analog-to-digital conversion module is used to export driver carries out analog-to-digital conversion, shape
At the digital signal obtained for feedback module.
In addition, feedback module obtains the signal that driver exports especially by microphone.
Description of the drawings
One or more embodiments are illustrated by the picture in corresponding attached drawing, these are exemplary
Illustrate not constitute the restriction to embodiment, the element with same reference numbers label is expressed as similar member in attached drawing
Part, unless there are special statement, composition does not limit the figure in attached drawing.
Fig. 1 is the structural schematic diagram of signal processing apparatus in first embodiment of the invention；
Fig. 2 is the concrete structure schematic diagram of signal processing apparatus in first embodiment of the invention；
Fig. 3 is method flow diagram corresponding with signal processing apparatus in first embodiment of the invention；
Fig. 4 is the structural schematic diagram of signal processing apparatus in second embodiment of the invention；
Fig. 5 is method flow diagram corresponding with signal processing apparatus in second embodiment of the invention；
Fig. 6 is the structural schematic diagram of signal processing apparatus in third embodiment of the invention；
Fig. 7 is method flow diagram corresponding with signal processing apparatus in third embodiment of the invention；
Fig. 8 is the structural schematic diagram of signal processing apparatus in four embodiment of the invention；
Fig. 9 is the detailed model structure schematic diagram of signal processing apparatus in four embodiment of the invention；
Figure 10 is method flow diagram corresponding with signal processing apparatus in four embodiment of the invention.
Specific implementation mode
To keep the purpose, technical scheme and advantage of embodiment of the present invention clearer, below in conjunction with attached drawing to this hair
Bright each embodiment is explained in detail.However, it will be understood by those skilled in the art that in each implementation of the invention
In mode, many technical details are proposed in order to make reader more fully understand the present invention.But it is even if thin without these technologies
Section and various changes and modifications based on the following respective embodiments, can also realize claimed technical solution of the invention.
The first embodiment of the present invention is related to a kind of signal processing apparatus 100, as shown in Figure 1, including：Signal input part
11, filter 12, driver 13 and signal output end 14；Wherein, filter 12 is connect with driver 13, signal input part 11
In filter 12, signal output end 14 is located in driver 13；Input signal PDin is entered by signal input part 11 to be filtered
The input signal PDin received is done pre-filtering processing by device 12, filter 12, and by pre-filtering treated signal exports to
In driver 13；Treated for 12 pre-filtering of filtered device after signal enters in driver 13, and driver 13 should to what is received
Signal does energized process, and the signal after energized process is exported via signal output end 14, wherein the pre-filtering of filter 12
Opposite distorted characteristic is presented with the energized process of driver 13 in processing.
In the present embodiment, by before the driver 13, a filter 12 is set, and the filter 12
Opposite distorted characteristic is presented with the energized process of driver 13 in pre-filtering processing, so that input signal PDin swashs in entrance
It encourages before being distorted in device 13, has carried out mistake once opposite with the distortion status of driver 13 in advance in filter 12
Very, so that the signal finally exported from driver 13, experienced distortion opposite twice, and so that last distortion is existing
As being cancelled out each other, therefore, the distortion effect to output signal is weakened, effectively improves distortion phenomenon, and the operation
It is not related to debugging manually, it is complicated and cumbersome when not debugged like physical model, it is therefore, easy to operate.
The details of the signal processing apparatus of present embodiment 100 is specifically described below, the following contents is only side
The realization details of offer is just provided, the necessary of this programme is not implemented.
In the present embodiment, in order to make signal processing apparatus 100 preferably improve distortion phenomenon, in above-mentioned filter
In 12, concrete structure includes：Forward direction module 121, feedback module 122 and resolving module 123, as shown in Figure 2.
Wherein, forward direction module 121 is used to be handled according to the pre-filtering for modeling the distortion of driver 13
Model exports after carrying out pre-filtering processing to input signal PDin to driver 13.
Wherein, forward direction module 121 carries out pre-filtering processing with specific reference to following formula to input signal PDin：
Above-mentionedFor the distortion of driver, PDin (n+i) is input signal, and z (n+k) is auxiliary modeled terms
(and input signal presentation multiplies sexual intercourse), wi,j,k,m(it is furtherly, in each model, often for the corresponding coefficient of spline function
The corresponding coefficient of a spline function, also corresponds to be fitting coefficient), SPLm(| PDin (n+j) |) it is that spline function is (specific
It says, index spline function SPL can be removed by the amplitude information of input signal, because different spline functions covers different width
Spend section), n be batten Duplication (over_ratio numbers, the Duplication is higher, and the result of modeling is more accurate, accurate), i, j,
K is that (i is the memory depth of PDin (n), j SPL to memory depthm(n) memory depth, the memory depth that k is Z (n)), it is secondary
The n=3 of batten, the n=2 of linear spline, z (n) are auxiliary modeled terms, and just like giving a definition：
AP in above-mentioned formula is average power signal, and EVP is signal envelope.It is noted that non-linear when using
When the obvious driver of aspect ratio, for above-mentioned formula Z (n), Z (n)=AP (PDin (n)), Z (n)=EVP is usually chosen
(PDin (n)) the two formula are calculated.
Additionally, it is preferred that, in the present embodiment, forward direction module 121 is additionally operable in the input signal to next signal segment
Before PDin carries out pre-filtering processing, initialization process is carried out to modeling coefficients w.
Specifically, if regarding filter 12 as a pre-distorting network, input signal PDin, pre-distorting network is answered
It is PDdpd with signal, the error that driver 13 generates isAnd the distortion generated to driver 13 models, it is preceding
To module 121, pre-filtering processing is done to input signal PDin according to following modeling formula：It should be noted that above-mentioned modeling
Formula is an example, can also be modeled to error signal by other formula or mode in present embodiment.Separately
Outside, it is worth mentioning at this point that, after finishing pre-filtering processing to the preceding paragraph input signal PDin, the preceding paragraph input signal
The modeling coefficients w of PDin has an impact the pre-filtering processing of next section of input signal PDin, in present embodiment, it is preferred that
It is also right before forward direction module 121 does initial pre-filtering using above-mentioned pre-filtering processing model to each section of input signal PDin
Modeling coefficients w carries out initialization process, at this point, forward direction module 121 is in pass-through state, i.e. input signal PDin is equal to predistortion
Network application signal PDdpd；It is noted that input signal PDin can be collected before input to before module 121
It obtains, it can also being acquired in an instant to module 121 before entry；To module before this input signal PDin enters
After in 121, according to above-mentioned modeling formula, pre-distorting network application signal PDdpd can be obtained, wherein
When it is preceding to module 121 according to obtain pre-distorting network application signal PDdpd after, pre-distorting network application signal PDdpd is defeated
Be sent in driver 13, when signal is exported from driver 13, feedback module 122 to the signal that is exported from driver 13 into
Row obtains.
Feedback module 122 is used to obtain the signal of the output of driver 13, also, the signal for also exporting driver 13 is fed back
Specifically pre-distorting network application signal PDdpd is delivered in driver 13 in forward direction module 121 to module 123 is resolved
Afterwards, the signal that feedback module 122 is also exported from driver 13 carries out signal acquisition.
Specifically, feedback module 122 obtains feedback signal FBout, and feedback signal FBout is as resolving module 123
Resolve the data basis of modeling coefficients w.It is noted that in feedback module 122, specifically, microphone may be used
Obtain the signal that driver 13 exports, it is to be understood that feedback module 122 can also take other modes to obtain letter
Number, it is not limited in the example above.After feedback module 122 obtains the feedback signal FBout of needs, which is delivered to
It resolves in module 123.
The signal that module 123 is exported according to driver 13 is resolved to be modified the modeling coefficients w of pre-filtering processing model.
Specifically, in resolving module 123, current actual error is calculated by input signal PDin and feedback signal FBout and is believed
Number PDerr, i.e. PDerr=FBout-PDin in the modeler model before bringing the actual error of calculating into, are calculated new
/ revised modeling coefficients w, thus the modeling coefficients w in the pre-filtering processing model to preceding into module 121 repair
Just, wherein input signal PDin can be obtained from forward direction module 121, can also be obtained by other means, likewise,
Feedback signal FBout also can be obtained directly from feedback module 122, or can also be obtained by other means.When resolving mould
After block 123 calculates revised modeling coefficients w, forward direction module 121 also obtains the revised modeling coefficients w.
After forward direction module 121 obtains the revised modeling coefficients w, pre-flock is updated also according to revised modeling coefficients w
Wave handles model, and is handled after model carries out pre-filtering processing to input signal PDin and exported to sharp by updated pre-filtering
Encourage device 13.At this point, starting primary new cyclic process.
Specifically, after forward direction module 121 obtains the revised modeling coefficients w, by applying it at pre-filtering
It is replaced, realized to pre-filtering processing model more in reason model, with the former modeling coefficients w handled pre-filtering in model
Newly, it and handles model by updated pre-filtering input signal PDin is continued to do pre-filtering processing, herein, be equivalent to right
The training result of modeling coefficients w is applied, i.e. the application process to modeling coefficients w, and obtains a new pre-distorting network
Using signal PDdpd；At this point, the new pre-distorting network application signal PDdpd is delivered to driver 13 by forward direction module 121 again
In, also, feedback module 122 obtains the signal exported from driver 13 again, resolves module 123 again according to above-mentioned side
Formula calculates a new modeling coefficients w, is completed herein to building with doing the modified processing of update to original modeling coefficients w
The primary new training process of mode coefficient w, so continuous repetition training process and application process, every time in preceding primary modeling
Cycle is iterated on the basis of coefficient w, until obtained error PDerr gradually converges to a smaller value, that is to say, that no
It is defeated in autoexcitation device 13 after the disconnected revised pre-filtering processing model of update does pre-filtering processing to same section of input signal PDin
The signal gone out, compared with original input signal PDin, the distortion between them can enter a sufficiently small range, at this point,
It completes the pre-filtering to one section of input signal PDin to handle, then, is further continued for doing above-mentioned follow to next input signal PDin
Ring processing, in this way, the effect of pre-filtering processing of the pre-filtering processing model to each section of input signal PDin can be made more preferable,
Namely make the distortion of the signal from the output in driver 13 smaller.
It is understood that in order to preferably realize above-mentioned " error PDerr gradually converges to a smaller value " or
" distortion can enter a sufficiently small range " can be realized by the way that the iterative cycles number of modeling coefficients w is arranged, when
So, it can also be realized using other modes, for example, setting a threshold value and being compared, details are not described herein.
Generally speaking, the pre-filtering 12 in present embodiment is actually built according to the excitation distorted characteristic of driver 13
Inverse system is sought to it after mould, specifically：Before input signal PDin enters driver 13, pre-flock first is carried out to input signal PDin
Wave handles (i.e. pre-distortion) so that opposite mistake is presented with the non-linear distortion of driver 13 in the distortion of input signal PDin
True characteristic, to make the input and output of whole system that linear characteristic be presented.It is directly right using feed forward models method in present embodiment
Error carries out the modeling based on LS (least square method), and the coefficient in update pre-distortion system is removed with the result of single iteration.It adopts
Driver 13 is modeled with feed forward models method.When one section of input signal PDin input filter 12, signal first passes through filter
Forward direction module 121 in wave device 12, signal are energized device 13 and receive, when through too drastic after pre-filtering output in forward direction module 121
The signal of device 13 is encouraged after being exported in driver 13, feedback module 122 obtains the signal exported from driver 13 as feedback
Signal, and feedback signal is delivered to and resolves module 123, after resolving module 123 calculates modeling coefficients w according to modeling formula,
Modeling coefficients w is applied in filter 12, is carried out the pre-filtering processing of signal by forward direction module 121, and continues above-mentioned follow
Ring process, until after carrying out pre-filtering to the signal in filter 12 using the modeling coefficients w of last iteration, from driver 13
Until the distorted characteristic of the signal of middle output is sufficiently small.
In order to preferably illustrate in present embodiment, the forward direction module 121 of filter 12, resolves mould at feedback module 122
The overall workflow of block 123 will do a simple description, as shown in Figure 3 to whole workflow below：
S101：The error generated to driver 13 determines modeler model.
Wherein, modeling formula is as follows：
S102：Initialize modeling coefficients w.
Wherein, which carries out in forward direction module 121, it should be noted that initialization is to be happened to input one section
Signal PDin is carried out before doing initial pre-filtering processing, and when initializing progress, forward direction module 121 is in pass-through state, i.e.,
Input signal PDin is equal to pre-distorting network application signal PDdpd.
S103：Acquisition input signal PDin simultaneously calculates pre-distorting network application signal PDdpd, wherein
Wherein, which carries out in forward direction module 121, and after to modeling coefficients w initialization, by collected
Input signal PDin and formula：Pre-distorting network application signal PDdpd can be calculated
S104：After pre-distorting network application signal PDdpd enters driver 13, the output by acquiring driver 13 is believed
Number, obtain feedback signal FBout.
Wherein, which carries out in feedback module 122, pre-distorting network application signal PDdpd by driver 13 into
Row output, feedback module 122 obtains the output signal in the driver 13, in addition, the acquisition of feedback signal can pass through Mike
Wind is completed, it is of course also possible to complete by other means.
S105：Calculate currently practical error signal PDerr, PDerr=FBout-PDin.
Wherein, which carries out in resolving module 123, after obtaining input signal PDin and feedback signal FBout, root
Current actual error signal PDerr is calculated according to following formula：PDerr=FBout-PDin.
S106：Iterative solution update modeling coefficients w.
Wherein, which carries out in resolving module 123, resolves module 123 and is solved more by way of adaptive iteration
The coefficient w needed in new forward direction module 121.
In addition, enabling i=i+1, corresponding modeling coefficients w is modeled and is calculated to error PDerr, update is to preceding to module
In 121.
Second embodiment of the present invention is related to a kind of signal processing apparatus 200, as shown in figure 4, present embodiment and the
The content of one embodiment is substantially the same：Specifically, the signal processing apparatus 200 include signal input part 21, filter 22,
Driver 23, signal output end 24, signal input part 11, the filter of this and signal processing apparatus in first embodiment 100
12, driver 13, signal output end 14 generally correspond to；In present embodiment, filter 22 further includes preceding to module 221, feedback
Mould 222 resolves module 223, and, with first embodiment, forward direction module 121, feedback module 122 in filter 12 resolve for this
Module 123 generally corresponds to, the difference is that, present embodiment is further improved to first embodiment, improvements
It is：
The feedback module 222 is specifically used for after obtaining the signal that driver 23 exports, the letter that removal driver 23 exports
Number link influence, and feed back to the resolving module 223 by the signal that exports of the driver 23 after link influences is removed.
Specifically, the feedback signal directly acquired from the signal that driver 23 exports has link influence, should
Link influence can specifically include noise, gain, time delay etc., if feedback module 222 obtains feedback signal, and will carry upper
The feedback signal for stating link influence is fed directly to resolve in module 223, this can interfere resolving module 223 to calculate and accurately build
Mode coefficient w, and finally the pre-filtering processing in present embodiment is had an impact, therefore, in the present embodiment, in order to weaken
The interference that these links influence improves the accuracy for resolving and resolving modeling coefficients w in module 223, and makes to input signal
The pre-filtering effect of PDin is more accurate, feedback module 222 specific for：The signal that driver 23 exports is obtained to be fed back
Link signal LRAOut；To feedback link signal LRAOut processing, remove noise in link, gain and time delay influence,
The distortion data for only retaining system obtains the feedback signal FBout namely signal FBout of feedback network output.Further,
Feedback module 222 exports feedback signal FBout to resolving module 223.
In addition, in the present embodiment, filter 22 has workflow as described below, as shown in Figure 5：
S201：The error generated to driver 23 determines modeler model.
S202：Initialize modeling coefficients w.
S203：Acquisition input signal PDin simultaneously calculates pre-distorting network application signal PDdpd, wherein
S2041：After pre-distorting network application signal PDdpd enters driver 23, the output by acquiring driver 23 is believed
Number, obtain initial feedback signal LRAOut.
Wherein, which carries out in feedback module 222, pre-distorting network application signal PDdpd by driver 23 into
Row output, feedback module 222 obtain the output signal in the driver 23, obtain initial feedback signal LRAOut.
S2042：Removal link influences to obtain feedback signal FBout.
Wherein, which carries out in feedback module 222, it should be noted that due to initial feedback signal LRAOut
Feedback link influence is received, therefore.By feedback signal LRAOut processing, noise in link, gain and time delay are removed
It influences, only retains the distortion data of system, obtain the output signal FBout of feedback signal FBout namely feedback module 222, it should
Processed feedback signal FBout is conducive to do more accurate pre-filtering processing in filter 22.
S205：Calculate currently practical error signal PDerr, PDerr=FBout-PDin.
S206：Iterative solution update modeling coefficients w.
In addition, enabling i=i+1, corresponding modeling coefficients w is modeled and is calculated to error PDerr, update is to preceding to module
In 221.
Wherein, step S201 to step S203 is similar to step S103 with the S101 in first embodiment, step S205
Similar to step S106 with the S105 in first embodiment to step S206, in order to avoid repeating, details are not described herein again.
It should be noted that other multiple details and description in first embodiment are also applied for present embodiment, it is
It avoids repeating, which is not described herein again.
Third embodiment of the present invention is related to a kind of signal processing apparatus 300, as shown in fig. 6, present embodiment and the
Two embodiments are substantially the same, and specifically, which includes signal input part 31, filter 32, driver
33, signal output end 34, the signal input part 21, filter 22, excitation of this and signal processing apparatus in second embodiment 200
Device 23, signal output end 24 generally correspond to；In present embodiment, filter 32 further includes preceding to module 321, feedback mould 322, solution
Module 323 is calculated, with second embodiment, forward direction module 221, feedback module 222 in filter 22 resolve module 223 for this
It generally corresponds to；The difference is that present embodiment is further improved to second embodiment, the improvement is that：
Each signal segment corresponds to a modeling coefficients storage table；Module 323 is resolved to be additionally operable to exported according to driver 33
After signal is modified the modeling coefficients w of pre-filtering processing model, the revised w is recorded in modeling coefficients storage table
In；Also, forward direction module 321 is additionally operable to lookup and the modeling coefficients storage table corresponding to current demand signal section, and the last time is remembered
The w of record, as revised modeling coefficients w.
That is, in the present embodiment, by the way that a storage table LUT is arranged, remembering storage table LUT as one
Record and look for the carrier of modeling coefficients w.
Specifically, it during iterative cycles each time, resolves module 323 and is all asked by way of adaptive iteration
The coefficient w needed into module 321 before solution update, the modeling coefficients w solved every time are recorded into storage table LUT.
When forward direction module 321 does pre-filtering processing to input signal PDin, searches from storage table LUT and repaiied using newest
Modeling coefficients w after just.That is, forward direction module 321 carries out signal by the modeling coefficients w recorded in storage table LUT
Pre-distortion；It is noted that when it is preceding initialization process is carried out to modeling coefficients w to module 321 when, also correspond to this
The storage table LUT initialization of segment signal section, i.e., at this point, pre-distorting network application memory table LUT0=0 when the signal segment inputs,
Hereafter, after input signal PDin passes sequentially through filter 32, driver 33, feedback module 322 obtains the letter that driver 33 exports
Number, resolve module 323 according to the feedback signal computation modeling coefficient w in feedback module 322, at this point, modeling coefficients w be recorded into
Storage table LUT.
In addition, it is necessary to illustrate, in present embodiment, the modeling formula of LUT is：
Further, by LUT to errorIt is modeled, obtains pre-filtering processing model (i.e. first embodiment
In pre-filtering handle model)：
That is, corresponding modeling coefficients w is calculated by modeling error PDerr, and modeling coefficients w updates are arrived
In forward direction module 321, the signal of pre-distorting network application at this time
It is noted that storage table LUT can be：To multiple modified modeling coefficients of same input signal PDin
W is respectively recorded, and is done to different sections of input signal PDin and similarly recorded respectively, to record in whole process
All modeling coefficients w can also be to facilitate access of the later stage to parameter：Multiple amendments to same section of input signal PDin
Modeling coefficients w do iteration record, i.e., in same section of input signal PDin, finally leaving behind the modified modeling of last time is
Number w, and same record is done to the input signal PDin of other sections, it is arranged such, it is possible to reduce the memory space of occupancy is recorded,
It should be noted that the above two recording mode of storage table LUT can in good realization present embodiment to amendment after
Modeling coefficients w record, the handling result of pre-filtering can't be impacted, merely provide different recording modes.
In addition, in the present embodiment, filter 32 has workflow as described below, as shown in Figure 7：
S301：The error generated to driver 33 determines modeler model, and the storage table LUT of storage modeling coefficients w is arranged.
Wherein, modeling formula is as follows：
Storage table LUT is：
S302：Initialize modeling coefficients w and storage table LUT.
Wherein it is possible to understand, it is first when needing to be modeling coefficients w as the storage table LUT of storage modeling coefficients w
When beginningization processing, the storage table LUT of corresponding signal segment is also initialised processing, i.e. LUT0=0.
S303：Acquisition input signal PDin simultaneously calculates pre-distorting network application signal PDdpd, wherein
S3041：After pre-distorting network application signal PDdpd enters driver 33, the output by acquiring driver 33 is believed
Number, obtain initial feedback signal LRAOut.
S3042：Removal link influences to obtain feedback signal FBout.
S305：Calculate currently practical error signal PDerr, PDerr=FBout-PDin.
S306：Iterative solution update modeling coefficients w.
In addition, enabling i=i+1, corresponding modeling coefficients w is modeled and is calculated to error PDerr, update is to preceding to module
In 321.
In addition, step S303 to step S306 is similar to step S206 with the S203 in second embodiment, in order to avoid
It repeats, details are not described herein again.
It should be noted that other multiple implementation details in second embodiment may be applicable to present embodiment, it is
It avoids repeating, which is not described herein again.
The 4th embodiment of the present invention is related to a kind of signal processing apparatus 400, as shown in figure 8, in present embodiment
Signal processing apparatus 400 is substantially the same with signal processing apparatus 300 in third embodiment, specifically, the signal processing device
It includes signal input part 41, filter 42, driver 43, signal output end 44 to set 400, this in third embodiment at signal
Signal input part 31, filter 32, driver 33, the signal output end 34 of reason device 300 generally correspond to；In present embodiment,
Filter 42 further include before to module 421, feedback mould 422, resolve module 423, this in third embodiment, in filter 32
Forward direction module 321, feedback module 322, resolve module 323 generally correspond to；The difference is that present embodiment is to third
Being further improved for embodiment, thes improvement is that, further includes in present embodiment：
D/A converter module 45 and analog-to-digital conversion module 46, input signal PDin are digital signal, wherein digital-to-analogue conversion mould
Block 45 is arranged between forward direction module 421 and driver 43, and D/A converter module 45 is used to carry out on pre-filtering processing model pre-
The signal exported after being filtered carries out digital-to-analogue conversion, forms the analog signal for transporting to driver 43；Analog-to-digital conversion module 46 is set
It sets between driver 43 and feedback module 422, the signal that analog-to-digital conversion module 46 is used to export driver 43 carries out modulus
Conversion forms the digital signal obtained for feedback module 422.
Specifically, in the present embodiment, by the way that digital-to-analogue conversion mould is arranged between forward direction module 421 and driver 43
Block 45 can want the signal PDdpd of input actuator 43 to be converted into analog signal before input actuator 43
(namely pre-distorting network application digital signal PDdpd (n) carries out digital-to-analogue conversion and obtains pre-distorting network application simulation signal
PDdpd (t)), to be more in line with the working characteristics of driver 43 in present embodiment, likewise, in driver 43 and feedback mould
Analog-to-digital conversion module 46 is set between block 422, can make the analog signal exported from driver 43, is entering filter 42
Feedback module 422 before, be converted to digital signal via the analog-to-digital conversion module 46, it is anti-to be more in line in present embodiment
Present the working characteristics of module 422.
In order to preferably illustrate each structure of the signal processing apparatus in present embodiment, and in view of digital-to-analogue turns
Change with the links such as time delay alignment, in present embodiment, detailed model structure is as shown in Figure 9.
In addition, it is necessary to which explanation, believes with the relevant data of above-mentioned modules and mould concrete composition part in the block
Number prevalence as shown in figure 9, it is noted that modules and the Structural assignments of mould concrete composition part in the block, only
It to be carried out according to data flow shown in Fig. 9 just, it is not limited to position shown in Fig. 9.
It is noted that by the preceding input signal PDin to module 421 and by anti-after feedback module 422
Feedback signal FBout is modeled, and after obtaining modeling coefficients w and storage table LUT, " will be missed to shown in Fig. 9 under storage table LUT
In difference fitting " module, the predistortion for carrying out data next time.In this way, feedback signal FBout next time can be based on specifically
The modeling coefficients w (namely storage table LUT) of calculating obtains updating revised modeling coefficients w, and (storage table LUT while being updated is repaiied
Just).
In addition, in the present embodiment, filter 42 has workflow as described below, as shown in Figure 10：
S401：The error generated to driver 43 determines modeler model, and the storage table LUT of storage modeling coefficients w is arranged.
S402：Initialize modeling coefficients w and storage table LUT.
S403：Acquisition input signal PDin simultaneously calculates pre-distorting network application signal PDdpd, wherein
In step S403, input signal PDin is digital signal, that is to say, that the PDin of acquisition is digital signal.
S404：Digital-to-analogue conversion is carried out to pre-distorting network application signal PDdpd (n) and obtains pre-distorting network application simulation letter
Number PDdpd (t).
Wherein, step S404 is realized by the digital analog converter 45 being arranged between forward direction module 421 and driver 43, the number
Signal PDdpd (n) that i.e. will be in input actuator 43 is converted to excitation by mode converter 45 before input actuator 43
Device 43 can identify the analog signal PDdpd (t) of application, coordinate the work of driver 43 as a result,.
S405：After pre-distorting network application simulation signal PDdpd enters driver 43,43 output signal of driver, this is defeated
Go out signal and is converted to digital signal by analog-digital converter 46.
Wherein, step S405 is realized by the analog-digital converter 46 being arranged between driver 431 and feedback module 422, from
The signal exported in driver 43 is analog signal, the analog-digital converter 46 by i.e. will be in input feedback module 422 signal,
Before input feedback module 422, digital signal is converted to, coordinates feedback module 422 or even entire filter 42 as a result,
Work.
S4061：The digital signal that driver 43 exports is acquired, initial feedback signal LRAOut is obtained.
It is noted that feedback module 422 acquires the signal that driver 43 exports, and the signal is digital signal.
S4062：Removal link influences to obtain feedback signal FBout.
S407：Calculate currently practical error signal PDerr, PDerr=FBout-PDin.
S408：Iterative solution update modeling coefficients w.
In addition, enabling i=i+1, PDerr models and is calculated corresponding modeling coefficients w, and update is to preceding into module 421.
In addition, step S401 to step S403 is similar to step S303 with the S301 in third embodiment, step S4062
Similar to step S306 with the S3042 in third embodiment to step S408, in order to avoid repeating, details are not described herein again.
It should be noted that multiple implementation details in third embodiment may be applicable to present embodiment, in order to keep away
Exempt to repeat, which is not described herein again.
It will be understood by those skilled in the art that the respective embodiments described above are to realize the specific embodiment party of the present invention
Formula, and in practical applications, can to it, various changes can be made in the form and details, without departing from the spirit and model of the present invention
It encloses.
Claims (8)
1. a kind of signal processing apparatus, which is characterized in that including：Signal input part, filter, driver and signal output end；
The signal input part is located in the filter, and the filter is connect with the driver, the signal output end
In the driver；
The input signal PDin that the filter is used to receive by the signal input part carries out pre-filtering processing, and
By pre-filtering, treated that signal is exported to the driver；
The driver is used for the energized process to the signal after the pre-filtering, and by the signal after energized process described in
Signal output end is exported；
Wherein, the pre-filtering of the filter is handled is presented opposite distorted characteristic with the energized process of the driver.
2. signal processing apparatus according to claim 1, which is characterized in that the filter specifically includes：Forward direction module,
Feedback module and resolving module；
The forward direction module is used to handle model according to the pre-filtering for modeling the distortion of driver, to described
Input signal PDin is exported after carrying out pre-filtering processing to the driver；
The feedback module is used to obtain the signal of the driver output, and the signal that the driver exports is fed back to institute
State resolving module；
The signal of the module for being exported according to the driver that resolve repaiies the modeling coefficients w of pre-filtering processing model
Just；
The forward direction module is additionally operable to update the pre-filtering processing model according to revised modeling coefficients w, and passes through update
Pre-filtering processing model afterwards exports after carrying out pre-filtering processing to the input signal PDin to the driver.
3. signal processing apparatus according to claim 2, which is characterized in that the forward direction module is specifically used for according to following
Formula carries out pre-filtering processing to the input signal PDin：
Wherein, describedFor the distortion of driver, the PDin (n+i) is input signal, and the z (n+k) is auxiliary
Modeled terms, the wi,j,k,mFor the corresponding coefficient of spline function, the SPLm(| PDin (n+j) |) it is spline function, the n is
The Duplication of batten, i, j, k are memory depth；Modeled terms z (n) is assisted, just like giving a definition：
Wherein, the AP is average power signal, and the EVP is signal envelope.
4. signal processing apparatus according to claim 2, which is characterized in that
The feedback module is specifically used for after the signal for obtaining the driver output, removes the letter of the driver output
Number link influence, will remove link influence after the driver output signal feed back to the resolving module.
5. signal processing apparatus according to claim 2, which is characterized in that the forward direction module is additionally operable to next letter
Before the input signal PDin of number section carries out pre-filtering processing, initialization process is carried out to modeling coefficients w.
6. signal processing apparatus according to claim 5, which is characterized in that each signal segment corresponds to modeling coefficients storage
Table；
It is described resolve module be additionally operable to signal export according to the driver to pre-filtering processing model modeling coefficients w into
After row is corrected, the revised w is recorded in the modeling coefficients storage table；
The forward direction module is additionally operable to lookup and the modeling coefficients storage table corresponding to current demand signal section, by the last time record
The w, as revised modeling coefficients w.
7. signal processing apparatus according to claim 2, which is characterized in that the input signal PDin is digital signal；
The signal processing apparatus further includes D/A converter module and analog-to-digital conversion module；
The D/A converter module is arranged between the forward direction module and the driver, and the D/A converter module is used for will
The pre-filtering processing model carries out the signal exported after pre-filtering processing, carries out digital-to-analogue conversion, and the driver is transported in formation
Analog signal；
The analog-to-digital conversion module is arranged between driver and feedback module, and the analog-to-digital conversion module is used for the excitation
The signal of device output carries out analog-to-digital conversion, forms the digital signal obtained for the feedback module.
8. signal processing apparatus according to claim 1, which is characterized in that the feedback module is obtained especially by microphone
Take the signal of the driver output.
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