CN103259563A - Self-adapting filter divergence detection method and echo cancellation system - Google Patents

Self-adapting filter divergence detection method and echo cancellation system Download PDF

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CN103259563A
CN103259563A CN2012100348222A CN201210034822A CN103259563A CN 103259563 A CN103259563 A CN 103259563A CN 2012100348222 A CN2012100348222 A CN 2012100348222A CN 201210034822 A CN201210034822 A CN 201210034822A CN 103259563 A CN103259563 A CN 103259563A
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sef
adapting filter
self
amplitude
output signal
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CN103259563B (en
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许云峰
谢单辉
王彦
王威
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Shanghai Li Ke Semiconductor Technology Co., Ltd.
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Leadcore Technology Co Ltd
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Abstract

The invention relates to the field of voice communication and discloses a self-adapting filter divergence detection method and an echo cancellation system. Whether a self-adapting filter is in a divergent state or is in a normal state is judged through a comparison result of the amplitude difference of an input signal and an output signal of the self-adapting filter and a first prearranged threshold value. Once the divergence of the self-adapting filter is detected, the self-adapting filter is immediately reset to ensure that convergence of the self-adapting filter is started again, and accordingly the self-adapting filter is prevented from estimating incorrect echoes as far as possible to ensure that the echo cancellation system can correctly eliminate echoes, and reliability of the self-adapting filter is improved. Furthermore, whether the self-adapting filter is in a convergence process or not is taken into account before the self-adapting filter is judged to be in a divergent state, a special condition that the self-adapting filter is in a convergence process is incorrectly judged to be in a divergent state and accordingly accuracy degree of detection of the self-adapting filter is further guaranteed.

Description

Sef-adapting filter is dispersed detection method and echo cancelling system
Technical field
The present invention relates to the voice communication field, particularly a kind of sef-adapting filter disperses detection method and echo cancelling system.
Background technology
In voice communication system, after remote end input signal arrives the local signal receiving equipment, arrive receiver through the processing of local signal receiving equipment, in this process through regular meeting's echogenicity.In order to eliminate echo, before voice signal output, use sef-adapting filter to carry out echo elimination in the prior art.In echo was eliminated, the constringent quality of sef-adapting filter was related to the performance quality of whole Echo Canceller.Because the complexity of voice environment if two ends just are very easy to cause filter divergence when existing similar sound together, in case filter divergence will cause very serious noise, and also can't restrain after the filter divergence.
As shown in Figure 1, the principle schematic of eliminating for acoustic echo.In general echo processing, have 3 important module and constituted the basic framework that echo is eliminated: sef-adapting filter, nonlinear echo processor and double talk detection device.
Wherein sef-adapting filter is mainly used in following the tracks of the path of reecho, estimates the estimated echo signal Residual echo signal after the nonlinear echo processor is handled sef-adapting filter is eliminated; The double talk detection device is used for the renewal of control sef-adapting filter, prevents that filter from continuing renewal and causing filter divergence in two saying.
Sef-adapting filter generally adopts lowest mean square (LMS) algorithm in echo is eliminated, and its coefficiency updating method adopts steepest descent method.
The time domain least mean square algorithm adopts formula (1) to be described:
W j+1=W j+2με jX j (1)
Wherein, μ is learning efficiency;
W jWith X jBe respectively at j filter coefficient vector and input vector constantly, specifically suc as formula shown in (2) and (3) ( Expression W jTransposition, Expression X jTransposition):
W j T = [ w 1 j , w 2 j , w 3 j · · · w nj ] - - - ( 2 )
X j T = [ x j , x j - 1 , x j - 2 · · · x j - n + 1 ] - - - ( 3 )
ε jBe error, expression " desired output " With reality output d jDifference:
ϵ j = d j - y j ^ - - - ( 4 )
And the estimated value of echo Obtain by vector multiplication:
y j ^ = X j T W j - - - ( 5 )
But filter update has a restrictive condition will not have under the voice signal and could upgrade at near-end exactly, otherwise will produce filter divergence.In order to guarantee that sef-adapting filter do not disperse, need detect the dual end communication state, when detecting dual end communication, stop the renewal of sef-adapting filter.
In general, double talk detection adopts the coherent detection method, confirms whether be the dual end communication state by the correlation of calculating near-end speech and far-end speech.For generally speaking, this double talk detection can be good at finishing the detection task.But because complexity of speech, exist such as near-end speech and far-end speech under the situation of big correlation (under some extreme cases, for example two mobile phones from very close in, be exactly the very strong signal of two-way correlation if collect signal), detect effect with regard to non-constant, and then cause filter divergence.Though this probability of dispersing is very low, just be difficult to return to original level in case disperse filter, cause the rapid deterioration of voice quality.
Existing sef-adapting filter technology is effectively dispersed testing mechanism owing to lacking, can not very fast recovery when causing filter divergence.Though this is a small probability event, and voice quality is had very large influence.Namely the echo path that estimates in this case and actual the falling far short of filter divergence, cause sef-adapting filter to estimate wrong echo, the estimated echo of this mistake and real echo fall far short, if use wrong estimated echo to do echo elimination, not only can not eliminate echo like this and can produce very large noise.
Summary of the invention
The object of the present invention is to provide a kind of sef-adapting filter to disperse detection method and echo cancelling system, whether can detect sef-adapting filter effectively disperses, make when detecting sef-adapting filter and disperse, the replacement sef-adapting filter, allow sef-adapting filter restart convergence, thereby avoid sef-adapting filter to estimate wrong echo as far as possible, make echo cancelling system can correctly eliminate echo, improve the reliability of sef-adapting filter.
For solving the problems of the technologies described above, embodiments of the present invention provide a kind of sef-adapting filter to disperse detection method, comprise following steps:
Detect the input signal of sef-adapting filter and the amplitude of output signal;
The amplitude of more described input signal and the amplitude of described output signal are if the difference of the amplitude of the amplitude of described input signal and described output signal judges then that greater than the first default thresholding described sef-adapting filter is in divergent state; If described difference is less than or equal to described first thresholding, judge that then described sef-adapting filter is in normal condition;
When judging that described sef-adapting filter is in divergent state, the described sef-adapting filter of resetting.
Embodiments of the present invention also provide a kind of echo cancelling system, comprise sef-adapting filter, and sef-adapting filter is dispersed checkout gear and sef-adapting filter reset apparatus;
Described sef-adapting filter is dispersed checkout gear and is comprised:
The amplitude detection module is for detection of the input signal of sef-adapting filter and the amplitude of output signal;
Comparison module is used for the amplitude of more described input signal and the amplitude of described output signal, obtains the difference of the amplitude of the amplitude of described input signal and described output signal;
The divergent state detection module is used for during greater than default first thresholding, judging that described sef-adapting filter is in divergent state in described difference, is less than or equal to described first thresholding in described difference, judges that then described sef-adapting filter is in normal condition;
The replacement trigger module is used for when described divergent state detection module judges that described sef-adapting filter is in divergent state, sends the indication of the described sef-adapting filter of resetting to described sef-adapting filter reset apparatus;
Described sef-adapting filter reset apparatus comprises:
The indication receiver module is used for receiving the indication of dispersing the described sef-adapting filter of replacement of checkout gear from described sef-adapting filter;
The replacement module is used for when described indication receiver module receives described indication the described sef-adapting filter of resetting.
Embodiment of the present invention in terms of existing technologies, the difference of the input signal by sef-adapting filter relatively and the amplitude of output signal judges that with the size of the first default thresholding described sef-adapting filter is in divergent state or is in normal condition, in case detect filter divergence with regard to the filter of resetting at once, allow filter restart convergence, thereby avoid sef-adapting filter to estimate wrong echo as far as possible, make echo cancelling system can correctly eliminate echo, improve the reliability of sef-adapting filter.
Preferably, before judging that described sef-adapting filter is in divergent state, also carry out following steps: detect in the current convergence process that whether is in self of described sef-adapting filter, if detect in the current convergence process that is not in self of described sef-adapting filter, then during greater than default first thresholding, judge that sef-adapting filter is in divergent state in the difference of the amplitude of the input signal of described sef-adapting filter and output signal again; If detect in the current convergence process that is in self of described sef-adapting filter, judge directly that then described sef-adapting filter is in normal condition.Because in the moment that sef-adapting filter is being restrained, described sef-adapting filter also is to be in a not situation of convergence, therefore by increasing a kind of current auxiliary judgement mechanism that whether is in self convergence process of sef-adapting filter that detects, can further avoid being in the convergence process in particular cases at sef-adapting filter, this sef-adapting filter erroneous judgement is divergent state.Thereby guaranteed that further sef-adapting filter disperses the accuracy of detection.
Preferably, detect in the following manner in the current convergence process that whether is in self of described sef-adapting filter: calculate the input signal of described sef-adapting filter and the cross-correlation coefficient of output signal; If the described cross-correlation coefficient that calculates greater than preset second threshold, is then judged in the current convergence process that is in self of described sef-adapting filter; If the described cross-correlation coefficient that calculates is less than or equal to described second thresholding, then judge in the current convergence process that is not in self of described sef-adapting filter.Realize simply easy operating.
Preferably, when the amplitude of the amplitude of comparator input signal and output signal, the maximum amplitude of the described input signal of each frame and the maximum amplitude of the described output signal in this frame are compared; Described difference is the difference of the maximum amplitude of the described input signal of each frame and described output signal.By the input signal of each frame and the amplitude of output signal are compared, can further guarantee when sef-adapting filter is in divergent state, can be detected in time.
Description of drawings
Fig. 1 is the principle schematic that acoustic echo is eliminated in the prior art;
Fig. 2 is the basic principle schematic of dispersing detection method according to the sef-adapting filter of first embodiment of the invention;
Fig. 3 is the flow chart of dispersing detection method according to the sef-adapting filter of first embodiment of the invention;
Fig. 4 is that second embodiment of the invention sef-adapting filter is dispersed the flow chart of detection method;
Fig. 5 is that second embodiment of the invention sef-adapting filter is dispersed the schematic diagram of detection method;
Fig. 6 is the structural representation according to the echo cancelling system of the 3rd execution mode of the present invention;
Fig. 7 is the structural representation according to the echo cancelling system of the 4th execution mode of the present invention;
Fig. 8 is the input/output relation analogous diagram under the sef-adapting filter convergence situation;
Fig. 9 is that sef-adapting filter is dispersed the input/output relation analogous diagram under the situation;
Figure 10 is the analogous diagram that concerns of the most significantly difference of sef-adapting filter and filter divergence;
Figure 11 is that sef-adapting filter is dispersed coefficient correlation change curve analogous diagram under the situation;
Figure 12 is in the sef-adapting filter convergence process and convergence back coefficient correlation change curve analogous diagram;
Figure 13 adopts the sef-adapting filter echo processing result who disperses detection technique involved in the present invention and the echo processing of not adopting sef-adapting filter to disperse detection technique comparison diagram as a result.
Embodiment
For making the purpose, technical solutions and advantages of the present invention clearer, below in conjunction with accompanying drawing the embodiments of the present invention are explained in detail.Yet, persons of ordinary skill in the art may appreciate that in each execution mode of the present invention, in order to make the reader understand the application better many ins and outs have been proposed.But, even without these ins and outs with based on many variations and the modification of following each execution mode, also can realize each claim of the application technical scheme required for protection.
First execution mode of the present invention relates to a kind of sef-adapting filter and disperses detection method, in the present embodiment, the input signal of needs detection sef-adapting filter and the amplitude of output signal also compare, if the difference of the amplitude of the amplitude of input signal and described output signal judges then that greater than the first default thresholding described sef-adapting filter is in divergent state; If described difference is less than or equal to described first thresholding, judge that then described sef-adapting filter is in normal condition.When judging that described sef-adapting filter is in divergent state, the described sef-adapting filter of resetting, as shown in Figure 2.
Idiographic flow comprises the steps: as shown in Figure 3
Step S301 detects the input signal d (k) of sef-adapting filter and the amplitude of output signal e (k).
Step S302 calculates the difference of the maximum amplitude of the maximum amplitude of described input signal of each frame and the described output signal in this frame.
Specifically, each frame maximum amplitude of sef-adapting filter input signal d (k) and output signal e (k) can be tried to achieve by following formula:
A e=Max(|e(k)|)
A d=Max(|d(k)|)
So, the maximum amplitude A of the described input signal of each frame dMaximum amplitude A with described output signal in this frame eDifference be:
a=A d-A e
Then, in step S303, judge that whether described difference is greater than the first default thresholding; If described difference then enters step S304 greater than the first default thresholding, judge that described sef-adapting filter is in divergent state; If described difference is less than or equal to the first default thresholding, then enter step S305, judge that described sef-adapting filter is in normal condition.Wherein, the concrete numerical value of first thresholding can be an empirical value relevant with the coefficient of sef-adapting filter, such as, take from a median of adaptive filter coefficient correlation dynamic range as first thresholding.
After step S304, enter step S306, the described sef-adapting filter of resetting.That is to say, when judging that sef-adapting filter is in divergent state, need this sef-adapting filter of resetting.
In addition, in the present embodiment, it is the input signal that calculates sef-adapting filter at each frame and the difference of the maximum amplitude of output signal and relatively big or small with the first default thresholding, yet, it will be appreciated by those skilled in the art that, in actual applications, also can every the difference that a frame carries out the maximum amplitude of input signal and output signal calculate and with default first thresholding size relatively; Perhaps calculate the difference of input signal and the maximum amplitude of output signal and relatively big or small with the first default thresholding at every N frame (as per 2 frames).
Owing to cause the principle of noise, noise to be because sef-adapting filter estimates wrong estimated echo causes from filter divergence, so only when having the downlink voice situation, just can cause noise.In theory, if filter is restrained fully, after filter was finished the linear echo elimination, the filter process input and output signal had tangible amplitude and descends.Be illustrated in figure 8 as the input/output relation analogous diagram under the sef-adapting filter convergence situation, as seen from Figure 8, the stage filter output amplitude that exists echo can significantly decrease.But disperse fully under the situation at filter, its result is on the contrary, is illustrated in figure 9 as sef-adapting filter and disperses input/output relation analogous diagram under the situation.As seen from Figure 9, sef-adapting filter is less than output amplitude at reflective local input range, and this is because the echo of sef-adapting filter misjudgment causes.According to the sef-adapting filter input/output relation as can be known, by filter input and output amplitude difference just can judge sef-adapting filter be the convergence or disperse.Be as shown in figure 10 sef-adapting filter the most significantly difference and filter divergence concern analogous diagram, first half component is depicted as sef-adapting filter input and output amplitude peak difference a, the Lower Half component is depicted as the output signal that linear echo is eliminated, exist under the noise situation as we can see from the figure, the value of a is just big especially.This shows that sef-adapting filter has been dispersed under the situation that has noise, so detect the size of the amplitude difference of sef-adapting filter input and output, degree of divergence that can objective reaction sef-adapting filter.
Therefore, in terms of existing technologies, input signal and the difference of the amplitude of output signal of first execution mode of the present invention by sef-adapting filter judges that with the comparative result of default first thresholding described sef-adapting filter is in divergent state or is in normal condition, in case detect filter divergence with regard to the filter of resetting at once, allow filter restart convergence, thereby avoid sef-adapting filter to estimate wrong echo as far as possible, make echo cancelling system can correctly eliminate echo, improve the reliability of sef-adapting filter.And by the input signal of each frame and the amplitude of output signal are compared, can further guarantee when sef-adapting filter is in divergent state, can be detected in time.
Second execution mode of the present invention relates to a kind of sef-adapting filter and disperses detection method.Second execution mode improves on the basis of first execution mode, main improvements are: in second embodiment of the invention, before judging that described sef-adapting filter is in divergent state, also carry out to detect the step in the current convergence process that whether is in self of described sef-adapting filter, and judge in conjunction with this testing result whether this sef-adapting filter is in divergent state.
Idiographic flow as shown in Figure 4.Step S401 to S403 is consistent with the step S301 to S303 of first execution mode of the present invention, does not repeat them here.
When judging among the step S403 that described difference is whether during greater than default first thresholding, execution in step S404, judge whether to detect in the current convergence process that whether is in self of this sef-adapting filter, if detect in the current convergence process that is not in self of described sef-adapting filter, then enter step S405, judge that sef-adapting filter is in divergent state.If detect in the current convergence process that is in self of described sef-adapting filter, then enter step S406, judge that this sef-adapting filter is in normal condition.
(after being step S405) enters step S407, the described sef-adapting filter of resetting after the judgement sef-adapting filter is in divergent state.Step S407 is identical with step S306, does not repeat them here.
In the present embodiment, detect in the following manner in the current convergence process that whether is in self of sef-adapting filter:
(1) calculates the input signal of described sef-adapting filter and the cross-correlation coefficient of output signal; The formula that calculates cross-correlation coefficient is as follows:
ρ de ( k ) = R de ( k ) R d ( k ) · R e ( k )
Wherein, described ρ De(k) cross-correlation coefficient of the described input signal of expression and described output signal; Described R De(k) the cross-correlation statistic of the described input signal of expression and described output signal; Described R d(k) the auto-correlation statistic of the described input signal of expression; Described R e(k) the auto-correlation statistic of the described output signal of expression.
(2) judge described cross-correlation coefficient ρ De(k) whether greater than preset second threshold.If the described cross-correlation coefficient that calculates greater than preset second threshold, is then judged in the current convergence process that is in self of described sef-adapting filter; If the described cross-correlation coefficient that calculates is less than or equal to described second thresholding, then judge in the current convergence process that is not in self of described sef-adapting filter.Wherein, the concrete numerical value of second thresholding can be an empirical value relevant with the coefficient of sef-adapting filter, as with sef-adapting filter output amplitude value peaked 1/3rd as second thresholding, can effectively prevent from frequently resetting filter.
Need to prove, in the step S404 of present embodiment, what be applied to is to the current testing result that whether is in self convergence process of this sef-adapting filter, and to the current detection that whether is in self convergence process of sef-adapting filter, can be considered as be and the amplitude parallel work-flow relatively of the input signal of this sef-adapting filter and output signal, as shown in Figure 5.That is to say, if detect in the current convergence process that is not in self of described sef-adapting filter, then during greater than default first thresholding, judge that sef-adapting filter is in divergent state in described difference again; If detect in the current convergence process that is in self of described sef-adapting filter, judge directly that then described sef-adapting filter is in normal condition.
Because in the moment that sef-adapting filter is being restrained, described sef-adapting filter also is to be in a not situation of convergence, in order to prevent that sef-adapting filter be not judged as divergent state under the convergence state, need detect the state that filter is being restrained, therefore second execution mode of the present invention is by increasing a kind of current auxiliary judgement mechanism that whether is in self convergence process of sef-adapting filter that detects, can further avoid being in the convergence process in particular cases at sef-adapting filter, this sef-adapting filter erroneous judgement is divergent state.Thereby guaranteed that further sef-adapting filter disperses the accuracy of detection.
From theory analysis, if the correlation that the sef-adapting filter input and output change very little then two paths of signals is (in the sef-adapting filter convergence process) very greatly, if the sef-adapting filter input and output change very greatly, then the correlation of two paths of signals very little (as the sef-adapting filter divergent state).Figure 11 disperses coefficient correlation change curve analogous diagram under the situation for sef-adapting filter, can from figure, see in the place that noise occurs, i.e. and the place of filter divergence, its corresponding coefficient correlation is very little, almost close to 0.Figure 12 is in the filter convergence process and convergence back coefficient correlation change curve analogous diagram, can see that in the sef-adapting filter convergence process stage sef-adapting filter input and output coefficient correlation is very big, almost close to 1.Can obtain such conclusion from Figure 11 and Figure 12 simulation result: if sef-adapting filter is in divergent state and complete converged state, coefficient correlation is very little; When if sef-adapting filter is in the convergence process, coefficient correlation is just very big.By this characteristic, can effectively protect sef-adapting filter convergence process state by the detection of coefficient correlation, prevent that sef-adapting filter be not judged as divergent state under the convergence state.
In order to further specify the beneficial effect that second execution mode of the present invention brings, the sef-adapting filter echo processing result who disperses detection technique who adopts this execution mode and the echo processing result who does not adopt sef-adapting filter to disperse detection technique are contrasted, as shown in figure 13.Simulate signal has adopted one section special speech data, and this speech data very easily causes filter divergence because correlation is too high.As Figure 13 the first half, adopted sef-adapting filter to disperse the simulation result of detection technique, in frame, do not have noise to occur, and in Figure 13 the latter half, do not adopt self adaptation to disperse the simulation result of detection technique, the noise on top appears cutting in frame.From this width of cloth analogous diagram, can confirm to have adopted self adaptation to disperse the reliability that detection technique has improved sef-adapting filter greatly.
What deserves to be mentioned is, above the step of the whole bag of tricks divide, just clear in order to describe, can merge into a step during realization or some step is split, be decomposed into a plurality of steps, as long as comprise identical logical relation, all in the protection range of this patent; To adding inessential modification in the algorithm or in the flow process or introduce inessential design, but the core design that does not change its algorithm and flow process is all in the protection range of this patent.
Third embodiment of the invention relates to a kind of echo cancelling system, as shown in Figure 6, comprises: sef-adapting filter, sef-adapting filter are dispersed checkout gear and sef-adapting filter reset apparatus.Wherein, sef-adapting filter is dispersed checkout gear detection sef-adapting filter and is in divergent state or is in normal condition, sef-adapting filter is dispersed checkout gear when judging that sef-adapting filter is in divergent state, sends the indication of replacement sef-adapting filter to the sef-adapting filter reset apparatus; The sef-adapting filter reset apparatus receives and comes from replacement when indication that sef-adapting filter is dispersed checkout gear, replacement sef-adapting filter.
Specifically, sef-adapting filter is dispersed checkout gear and is comprised amplitude detection module, comparison module, divergent state detection module and replacement trigger module.The amplitude detection module detects the input signal of sef-adapting filter and the amplitude of output signal, and sends into comparison module.The amplitude of the more described input signal of comparison module and the amplitude of described output signal obtain the difference of the amplitude of the amplitude of described input signal and described output signal.The divergent state detection module during greater than default first thresholding, judges that described sef-adapting filter is in divergent state in described difference, is less than or equal to described first thresholding in described difference, judges that then described sef-adapting filter is in normal condition.When the replacement trigger module judges that at described divergent state detection module described sef-adapting filter is in divergent state, send the indication of the described sef-adapting filter of resetting to described sef-adapting filter reset apparatus.If the divergent state detection module is judged described sef-adapting filter and is in normal condition, show that all are normal, can continue to handle by normal flow.
The sef-adapting filter reset apparatus comprises indication receiver module and replacement module.The indication receiver module is used for receiving the indication of dispersing the described sef-adapting filter of replacement of checkout gear from described sef-adapting filter.When the indication receiver module receives this indication, by replacement module reset sef-adapting filter.
Be not difficult to find that present embodiment is the system embodiment corresponding with first execution mode, present embodiment can with the enforcement of working in coordination of first execution mode.The correlation technique details of mentioning in first execution mode is still effective in the present embodiment, in order to reduce repetition, repeats no more here.Correspondingly, the correlation technique details of mentioning in the present embodiment also can be applicable in first execution mode.
What deserves to be mentioned is that each involved in present embodiment module is logic module, in actual applications, a logical block can be a physical location, also can be the part of a physical location, can also realize with the combination of a plurality of physical locations.In addition, for outstanding innovation part of the present invention, will not introduce not too close unit with solving technical problem relation proposed by the invention in the present embodiment, but this does not show the unit that does not have other in the present embodiment.
Four embodiment of the invention relates to a kind of echo cancelling system, as shown in Figure 7.The 4th execution mode improves on the basis of the 3rd execution mode, main improvements are: in the 3rd execution mode, described sef-adapting filter is dispersed the difference that checkout gear directly adopts the amplitude of the amplitude of input signal of described sef-adapting filter and described output signal, with the comparative result of first thresholding of presetting, judge that described sef-adapting filter is in divergent state or is in normal condition.And in four embodiment of the invention, described sef-adapting filter is dispersed checkout gear also needs the current testing result that whether is in self convergence process of combining adaptive filter, judges that sef-adapting filter is in divergent state or is in normal condition.
Specifically, sef-adapting filter is dispersed checkout gear and is also comprised convergence process detection module and control module.
Wherein, the convergence process detection module is for detection of in the current convergence process that whether is in self of described sef-adapting filter.
Control module is used for when described convergence process detection module detects the current convergence process that is not in self of described sef-adapting filter, allow described divergent state detection module during greater than default first thresholding, to judge that described sef-adapting filter is in divergent state in described difference; When described convergence process detection module detects the current convergence process that is in self of described sef-adapting filter, forbid that described divergent state detection module is in described difference during greater than default first thresholding, judge that described sef-adapting filter is in divergent state, control described divergent state detection module and judge that directly described sef-adapting filter is in normal condition.
In the present embodiment, the convergence process detection module is according to the input signal of described sef-adapting filter and the cross-correlation coefficient of output signal, detects in the current convergence process that whether is in self of described sef-adapting filter.Such as described convergence process detection module is at described cross-correlation coefficient during greater than preset second threshold, judges in the current convergence process that is in self of described sef-adapting filter; When described cross-correlation coefficient is less than or equal to described second thresholding, judge in the current convergence process that is not in self of described sef-adapting filter.
Because second execution mode is corresponding mutually with present embodiment, thus present embodiment can with the enforcement of working in coordination of second execution mode.The correlation technique details of mentioning in second execution mode is still effective in the present embodiment, and the technique effect that can reach in second execution mode can be realized in the present embodiment too, in order to reduce repetition, repeats no more here.Correspondingly, the correlation technique details of mentioning in the present embodiment also can be applicable in second execution mode.
Persons of ordinary skill in the art may appreciate that the respective embodiments described above are to realize specific embodiments of the invention, and in actual applications, can do various changes to it in the form and details, and without departing from the spirit and scope of the present invention.

Claims (9)

1. a sef-adapting filter is dispersed detection method, it is characterized in that, comprises following steps:
Detect the input signal of sef-adapting filter and the amplitude of output signal;
The amplitude of more described input signal and the amplitude of described output signal are if the difference of the amplitude of the amplitude of described input signal and described output signal judges then that greater than the first default thresholding described sef-adapting filter is in divergent state; If described difference is less than or equal to described first thresholding, judge that then described sef-adapting filter is in normal condition;
When judging that described sef-adapting filter is in divergent state, the described sef-adapting filter of resetting.
2. sef-adapting filter according to claim 1 is dispersed detection method, it is characterized in that, before judging that described sef-adapting filter is in divergent state, also carries out following steps:
Detect in the current convergence process that whether is in self of described sef-adapting filter, if detect in the current convergence process that is not in self of described sef-adapting filter, then during greater than default first thresholding, judge that sef-adapting filter is in divergent state in described difference again; If detect in the current convergence process that is in self of described sef-adapting filter, judge directly that then described sef-adapting filter is in normal condition.
3. sef-adapting filter according to claim 2 is dispersed detection method, it is characterized in that, detects in the following manner in the current convergence process that whether is in self of described sef-adapting filter:
Calculate the input signal of described sef-adapting filter and the cross-correlation coefficient of output signal;
If the described cross-correlation coefficient that calculates greater than preset second threshold, is then judged in the current convergence process that is in self of described sef-adapting filter; If the described cross-correlation coefficient that calculates is less than or equal to described second thresholding, then judge in the current convergence process that is not in self of described sef-adapting filter.
4. sef-adapting filter according to claim 3 is dispersed detection method, it is characterized in that,
The formula of described calculating cross-correlation coefficient is as follows:
ρ de ( k ) = R de ( k ) R d ( k ) · R e ( k )
Wherein, described ρ De(k) cross-correlation coefficient of the described input signal of expression and described output signal; Described R De(k) the cross-correlation statistic of the described input signal of expression and described output signal; Described R d(k) the auto-correlation statistic of the described input signal of expression; Described R e(k) the auto-correlation statistic of the described output signal of expression.
5. disperse detection method according to each described sef-adapting filter in the claim 1 to 4, it is characterized in that, in the step of the amplitude of described comparator input signal and the amplitude of described output signal, comprise following substep:
The maximum amplitude of the described input signal of each frame and the maximum amplitude of the described output signal in this frame are compared;
Described difference is the difference of the maximum amplitude of the described input signal of each frame and described output signal.
6. an echo cancelling system comprises sef-adapting filter, it is characterized in that, also comprises: sef-adapting filter is dispersed checkout gear and sef-adapting filter reset apparatus;
Described sef-adapting filter is dispersed checkout gear and is comprised:
The amplitude detection module is for detection of the input signal of sef-adapting filter and the amplitude of output signal;
Comparison module is used for the amplitude of more described input signal and the amplitude of described output signal, obtains the difference of the amplitude of the amplitude of described input signal and described output signal;
The divergent state detection module is used for during greater than default first thresholding, judging that described sef-adapting filter is in divergent state in described difference, is less than or equal to described first thresholding in described difference, judges that then described sef-adapting filter is in normal condition;
The replacement trigger module is used for when described divergent state detection module judges that described sef-adapting filter is in divergent state, sends the indication of the described sef-adapting filter of resetting to described sef-adapting filter reset apparatus;
Described sef-adapting filter reset apparatus comprises:
The indication receiver module is used for receiving the indication of dispersing the described sef-adapting filter of replacement of checkout gear from described sef-adapting filter;
The replacement module is used for when described indication receiver module receives described indication the described sef-adapting filter of resetting.
7. echo cancelling system according to claim 6 is characterized in that, described sef-adapting filter is dispersed checkout gear and also comprised:
The convergence process detection module is in the current convergence process that whether is in self of described sef-adapting filter;
Control module, be used for when described convergence process detection module detects the current convergence process that is not in self of described sef-adapting filter, allow described divergent state detection module during greater than default first thresholding, to judge that described sef-adapting filter is in divergent state in described difference; When described convergence process detection module detects the current convergence process that is in self of described sef-adapting filter, forbid that described divergent state detection module is in described difference during greater than default first thresholding, judge that described sef-adapting filter is in divergent state, control described divergent state detection module and judge that directly described sef-adapting filter is in normal condition.
8. echo cancelling system according to claim 7, it is characterized in that, described convergence process detection module is according to the input signal of described sef-adapting filter and the cross-correlation coefficient of output signal, detects in the current convergence process that whether is in self of described sef-adapting filter;
Wherein, described convergence process detection module is at described cross-correlation coefficient during greater than preset second threshold, judges in the current convergence process that is in self of described sef-adapting filter; When described cross-correlation coefficient is less than or equal to described second thresholding, judge in the current convergence process that is not in self of described sef-adapting filter.
9. according to each described echo cancelling system in the claim 6 to 8, it is characterized in that, described comparison module compares the maximum amplitude of the described input signal of each frame and the maximum amplitude of the described output signal in this frame when the amplitude of the amplitude of more described input signal and described output signal;
The difference that described comparison module obtains is the difference of the maximum amplitude of the described input signal of each frame and described output signal.
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