CN108877829A - A kind of method and apparatus of signal processing - Google Patents
A kind of method and apparatus of signal processing Download PDFInfo
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- CN108877829A CN108877829A CN201810291719.3A CN201810291719A CN108877829A CN 108877829 A CN108877829 A CN 108877829A CN 201810291719 A CN201810291719 A CN 201810291719A CN 108877829 A CN108877829 A CN 108877829A
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- G10L21/00—Speech or voice signal processing techniques to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility
- G10L21/02—Speech enhancement, e.g. noise reduction or echo cancellation
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- G—PHYSICS
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- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L21/00—Speech or voice signal processing techniques to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility
- G10L21/02—Speech enhancement, e.g. noise reduction or echo cancellation
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Abstract
The embodiment of the invention provides a kind of method and apparatus of signal processing, including：Obtain reference signal；Reference signal is input to reference path transmission function, obtains the first desired signal；First desired signal is input to predictive filtering function, obtains the first prediction signal；First error signal is obtained according to the first desired signal and the first prediction signal；First error signal is adjusted by lowest mean square LMS function, obtains the second prediction signal；Second prediction signal is input to adjusting filter function, obtains adjustment signal；Adjustment signal is input to secondary path transmission function, obtains output signal；According to output signal and the second desired signal, the second error signal is obtained；Second error signal is input to reference path transmission function, obtains third error signal；Third error signal is input to filtering lowest mean square FxLMS function, obtains anti-noise signal；Wherein, the anti-noise signal is used for the noise reduction of noise cancelling headphone；In the embodiment of the present invention, noise reduction effect can be improved.
Description
Technical field
The present invention relates to the technical fields of vibration control, at the method and a kind of signal more particularly to a kind of signal processing
The device of reason.
Background technique
Existing Technique of Active Noise Control is widely applied in military, civil field, wherein adaptive active is made an uproar
Acoustic control technology is the difficult point of Technique of Active Noise Control application.
If desired it is studied for adaptive active noise control system, it can be according to digital feedforward single channel system
Structure constructs system model, and establishes physical model according to system model, and carry out chip type selecting Parameter analysis, then establishes imitative
True mode and to the LMS of classical adaptive algorithm (Least Mean Square, lowest mean square) algorithm, FxLMS (Filter-x
LMS filters LMS) algorithm emulated, and above two algorithm simulating noise reduction effect is preferable, however algorithm is applied in hardware electricity
Noise reduction effect is poor when road, and research finds signal A (analog signals, analog signal)/D (digital signals, number
Word signal), D/A conversion process, algorithm calculating process, signals transmission there is delay, wherein signal conversion process is prolonged
Account for major part late, through study LMS algorithm have ignored delay caused by influence, FxLMS algorithm consider secondary path delay and
Reference path delay is had ignored, if re-establishing simulation model after system delay is added, LMS algorithm and FxLMS algorithm are carried out
Simulation analysis, then the noise reduction effect of two kinds of algorithms is poor.
Summary of the invention
The embodiment of the present invention provides the method and a kind of device of signal processing accordingly of a kind of signal processing, to solve to work as
There are when system delay, the poor above problem of the noise reduction effect of LMS algorithm and FxLMS algorithm.
To solve the above-mentioned problems, the embodiment of the invention discloses a kind of methods of signal processing, including：
Obtain reference signal；
The reference signal is input to the reference path transmission function, obtains the first desired signal；
First desired signal is input to predictive filtering function, obtains the first prediction signal；
First error signal is obtained according to first desired signal and first prediction signal；
The first error signal is adjusted by lowest mean square LMS function, obtains the second prediction signal；
Second prediction signal is input to adjusting filter function, obtains adjustment signal；
The adjustment signal is input to secondary path transmission function, obtains output signal；
According to the output signal and the second desired signal, the second error signal is obtained；
Second error signal is input to reference path transmission function, obtains third error signal；
The third error signal is input to filtering lowest mean square FxLMS function, obtains anti-noise signal；Wherein, described
Anti-noise signal is used for the noise reduction of noise cancelling headphone.
Preferably, the step that first error signal is obtained according to first desired signal and first prediction signal
Suddenly include：
First desired signal and first prediction signal are subtracted each other, the first error signal is obtained.
Preferably, described according to the output signal and the second desired signal, the step of obtaining the second error signal, includes：
Obtain second desired signal；
By the output signal and the second expectation signal subtraction, second error signal is obtained.
Preferably, described that the first error signal is adjusted by lowest mean square LMS function, obtain the second prediction signal
Step includes：
Adjusting the first error signal by the LMS function is zero, obtains the second prediction signal.
Preferably, the described the step of third error signal is input to FxLMS function, obtains anti-noise signal, includes：
Adjusting the third error signal by the FxLMS function is zero, obtains the anti-noise signal.
The embodiment of the invention also discloses a kind of devices of signal processing, including：
Reference signal obtains module, for obtaining reference signal；
First desired signal obtains module and obtains for the reference signal to be input to the reference path transmission function
Obtain the first desired signal；
First prediction signal obtains module, for first desired signal to be input to predictive filtering function, obtains the
One prediction signal；
First error signal obtains module, for obtaining the according to first desired signal and first prediction signal
One error signal；
Second prediction signal obtains module, for adjusting the first error signal by lowest mean square LMS function, obtains
Second prediction signal；
Adjustment signal obtains module, for second prediction signal to be input to adjusting filter function, obtains and adjusts letter
Number；
Output signal obtains module, for the adjustment signal to be input to secondary path transmission function, obtains output letter
Number；
Second error signal obtains module, for obtaining the second error according to the output signal and the second desired signal
Signal；
Third error signal obtains module and obtains for second error signal to be input to reference path transmission function
Obtain third error signal；
Anti-noise signal obtains module, for the third error signal to be input to filtering lowest mean square FxLMS function, obtains
Obtain anti-noise signal；Wherein, the anti-noise signal is used for the noise reduction of noise cancelling headphone.
Preferably, the first error signal acquisition module includes：
First error signal obtains submodule, for first desired signal and first prediction signal to be subtracted each other,
Obtain the first error signal.
Preferably, the second error signal acquisition module includes：
Second expectation signal acquisition submodule, for obtaining second desired signal；
Second error signal obtains submodule, for obtaining the output signal and the second expectation signal subtraction
Second error signal.
Preferably, the second prediction signal acquisition module includes：
Second prediction signal obtains submodule, is zero for adjusting the first error signal by the LMS function, obtains
Obtain the second prediction signal.
Preferably, the anti-noise signal acquisition module includes：
Anti-noise signal obtains submodule, is zero for adjusting the third error signal by the FxLMS function, obtains
The anti-noise signal.
The embodiment of the present invention includes following advantages：
In the embodiment of the present invention, reference signal is obtained；The reference signal is input to the reference path transmission function,
Obtain the first desired signal；First desired signal is input to predictive filtering function, obtains the first prediction signal；According to institute
It states the first desired signal and first prediction signal obtains first error signal；By described in the adjusting of lowest mean square LMS function
First error signal obtains the second prediction signal；Second prediction signal is input to adjusting filter function, obtains and adjusts letter
Number；The adjustment signal is input to secondary path transmission function, obtains output signal；According to the output signal and the second phase
It hopes signal, obtains the second error signal；Second error signal is input to reference path transmission function, obtains third error
Signal；The third error signal is input to filtering lowest mean square FxLMS function, obtains anti-noise signal；Wherein, the anti-noise
Signal is used for the noise reduction of noise cancelling headphone；In the embodiment of the present invention, after considering the system delay in practical application, as acoustic propagation is prolonged
Late, the delay etc. that device generates, carries out the improvement of algorithm, when there are system delay, noise reduction effect can be improved.
Detailed description of the invention
To describe the technical solutions in the embodiments of the present invention more clearly, make required in being described below to embodiment
Attached drawing is briefly described, it should be apparent that, drawings in the following description are only some embodiments of the invention, for
For those of ordinary skill in the art, without creative efforts, it can also be obtained according to these attached drawings other
Attached drawing；
Fig. 1 is a kind of step flow chart of the embodiment of the method one of signal processing of the embodiment of the present invention；
Fig. 2 is a kind of step flow chart of the embodiment of the method two of signal processing of the embodiment of the present invention；
Fig. 3 is a kind of structural block diagram of data processing model of the embodiment of the present invention；
Fig. 4 is the noise reduction figure that one of embodiment of the present invention postpones 2 sampled points；
Fig. 5 is the noise reduction figure of 2 sampled points of another delay in the embodiment of the present invention；
Fig. 6 is the noise reduction figure that one of embodiment of the present invention postpones 4 sampled points；
Fig. 7 is the noise reduction figure of 4 sampled points of another delay in the embodiment of the present invention；
Fig. 8 is the noise reduction figure that one of embodiment of the present invention postpones 6 sampled points；
Fig. 9 is the noise reduction figure of 6 sampled points of another delay in the embodiment of the present invention；
Figure 10 is the noise reduction figure that one of embodiment of the present invention postpones 8 sampled points；
Figure 11 is the noise reduction figure of 8 sampled points of another delay in the embodiment of the present invention；
Figure 12 is a kind of structural block diagram of the Installation practice of signal processing of the embodiment of the present invention.
Specific embodiment
The technical issues of in order to keep the embodiment of the present invention solved, technical solution and beneficial effect are more clearly understood, with
The embodiment of the present invention is further described in lower combination accompanying drawings and embodiments.It should be appreciated that specific implementation described herein
Example is only used to explain the present invention, is not intended to limit the present invention.
Referring to Fig.1, a kind of step flow chart of the embodiment of the method one of signal processing of the embodiment of the present invention is shown, is had
Body may include steps of：
Step 101, reference signal is obtained；
In the embodiment of the present invention, the data processing method can be applied to noise reducing apparatus, if noise reducing apparatus may include
Dry and digital signal processor and hardware circuit；For example, the noise reducing apparatus may include the equipment such as noise cancelling headphone, described
Hardware circuit may include reference sensor, error pick-up etc., the embodiment of the present invention to this with no restriction, the noise reducing apparatus
Reference signal can be got first.
Step 102, the reference signal is input to the reference path transmission function, obtains the first desired signal；
Specifically, the reference signal can be input to the reference path transmission function (i.e. reference path), obtain
Obtain the first desired signal；Reference signal p (n) is entered after system by reference path Hr(Z)；Due to Hr(Z) there is krA delay,
It is x (n-k by reference to the signal after accessr), the first desired signal as the moment.
Step 103, first desired signal is input to predictive filtering function, obtains the first prediction signal；
In the embodiment of the present invention, first desired signal is input to predictive filtering function (predictive filter), is obtained
Obtain the first prediction signal；The i.e. described predictive filter W1 is used to predict first prediction signal at the moment
Step 104, first error signal is obtained according to first desired signal and first prediction signal；
It is further applicable in the embodiment of the present invention, is obtained according to first desired signal and first prediction signal
First error signal；The first desired signal and the first prediction signal are subtracted each other as first error signal e1(n-kr)。
Step 105, the first error signal is adjusted by lowest mean square LMS function, obtains the second prediction signal；
In the embodiment of the present invention, can adjust the first error signal by the LMS function is zero, and it is pre- to obtain second
Survey signal；Adjusting error signal by LMS algorithm is zero to obtain more accurate second prediction signal.
Step 106, second prediction signal is input to adjusting filter function, obtains adjustment signal；
It is specifically applied in the embodiment of the present invention, second prediction signal further can be input to adjusting filtering letter
Number (i.e. adjusting filter W2), obtains adjustment signal；Continue to predict It obtains
Obtain the second prediction signalBy the second prediction signalIt is sent into adjusting filter W2 and finds out adjustment signal y (n+
ks).Predictive filter W1 is for predicting kr+ksInput of the reference signal delayed when+τ as sef-adapting filter, is equivalent to benefit
Having repaid reference path and secondary path delay bring influences, and can satisfy the causality requirement of system.Filter W2 is adjusted to use
In the not corresponding relationship of improvement reference signal and error signal, and then acquire accurate filter weights.
Step 107, the adjustment signal is input to secondary path transmission function, obtains output signal；
In the embodiment of the present invention, the adjustment signal can be input to secondary path transmission function, obtain output signal；
I.e. by y (n+ks) pass through secondary path Hs(Z), secondary path Hs(Z) there is ksA delay, therefore the output signal generated is s (n).
Step 108, according to the output signal and the second desired signal, the second error signal is obtained；
Further, according to the output signal and the second desired signal, the second error signal is obtained, gets and states second
It is that s (n) subtracts each other as the second error with the second desired signal d (n) after earmuff is actually passed through by output signal after desired signal
Signal e (n)；Second desired signal is the desired signal d (n) for passing through the earmuff of noise reducing apparatus.
Step 109, second error signal is input to reference path transmission function, obtains third error signal；
After filter stability to be predicted, due to needing in error signal collection process by reference path krIt is delayed when a
It can acquire, therefore lag k compared with the practical reference signal with after prediction of the second error signalrA time delay, i.e., by institute
It states the second error signal and is input to reference path transmission function, obtain third error signal e2(n-kr)。
Step 110, the third error signal is input to filtering lowest mean square FxLMS function, obtains anti-noise signal, institute
State noise reduction of the anti-noise signal for noise cancelling headphone.
It is zero it is possible to further adjust the third error signal by the FxLMS function, obtains the anti-noise letter
Number, filter weights W is updated with FXLMS algorithm2It (n), is zero to obtain accurate anti-noise signal by adjusting third error signal；
Wherein, the anti-noise signal is used for the noise reduction of noise cancelling headphone.It should be noted that FxLMS (the Filtered-x Least
Mean Square) function be filtering type lowest mean square function.
In the embodiment of the present invention, reference signal is obtained；The reference signal is input to the reference path transmission function,
Obtain the first desired signal；First desired signal is input to predictive filtering function, obtains the first prediction signal；According to institute
It states the first desired signal and first prediction signal obtains first error signal；By described in the adjusting of lowest mean square LMS function
First error signal obtains the second prediction signal；Second prediction signal is input to adjusting filter function, obtains and adjusts letter
Number；The adjustment signal is input to secondary path transmission function, obtains output signal；According to the output signal and the second phase
It hopes signal, obtains the second error signal；Second error signal is input to reference path transmission function, obtains third error
Signal；The third error signal is input to filtering lowest mean square FxLMS function, obtains anti-noise signal；Wherein, the anti-noise
Signal is used for the noise reduction of noise cancelling headphone；In the embodiment of the present invention, after considering the system delay in practical application, as acoustic propagation is prolonged
Late, the delay etc. that device generates, carries out the improvement of algorithm, when there are system delay, noise reduction effect can be improved.
Referring to Fig. 2, a kind of step flow chart of the embodiment of the method two of signal processing of the embodiment of the present invention is shown, is had
Body may include steps of：
Step 201, reference signal is obtained；
In the embodiment of the present invention, the data processing method can be applied to noise reducing apparatus, if noise reducing apparatus may include
Dry and digital signal processor and hardware circuit, the noise reducing apparatus can get reference signal first.
Step 202, the reference signal is input to the reference path transmission function, obtains the first desired signal；
It is possible to further which the reference signal is input to the reference path transmission function (i.e. reference path), obtain
Obtain the first desired signal；Reference signal p (n) is entered after system by reference path Hr(Z)；Due to Hr(Z) there is krIt is a to prolong
It late, is x (n-k by reference to the signal after accessr), the first desired signal as the moment.
Step 203, first desired signal is input to predictive filtering function, obtains the first prediction signal；
It applies in the embodiment of the present invention, first desired signal can also be input to predictive filtering function
(predictive filter) obtains the first prediction signal；The i.e. described predictive filter W1 is used to predict first prediction signal at the moment
Step 204, first desired signal and first prediction signal are subtracted each other, obtains the first error letter
Number；
It is further applicable in the embodiment of the present invention, it can be by first desired signal and the first prediction signal phase
Subtract, obtains the first error signal；First desired signal and the first prediction signal are subtracted each other as first error signal e1(n-
kr)。
Step 205, adjusting the first error signal by the LMS function is zero, obtains the second prediction signal；
It is specifically applied in the embodiment of the present invention, can adjust the first error signal by the LMS function is zero,
Obtain the second prediction signal；Adjusting error signal by LMS algorithm is zero to obtain more accurate second prediction signal.
Wherein, LMS (least mean square algorithm, Least-Mean-Square) function is that a kind of standard of adaptive-filtering is calculated
Method.
Step 206, second prediction signal is input to adjusting filter function, obtains adjustment signal；
Specifically, adjusting filter function further can be input to second prediction signal, adjustment signal is obtained；
Continue to predictObtain the second prediction signalBy second
Prediction signalIt is sent into adjusting filter function W2 and finds out adjustment signal y (n+ks)。
Step 207, the adjustment signal is input to secondary path transmission function, obtains output signal；
In a kind of preferred embodiment of the embodiment of the present invention, the adjustment signal can be input to secondary path transmitting letter
Number obtains output signal；I.e. by y (n+ks) pass through secondary path Hs(Z), secondary path Hs(Z) there is ksA delay, therefore generate
Output signal be s (n).
Step 208, second desired signal is obtained；
The second desired signal is stated it is possible to further get；Second desired signal is to pass through noise reducing apparatus
The desired signal d (n) of earmuff.
Step 209, by the output signal and the second expectation signal subtraction, second error signal is obtained；
As in a kind of practical application of the embodiment of the present invention, by output signal be s (n) be actually passed through after earmuff the
Two desired signal d (n) subtract each other as the second error signal e (n).
Step 210, second error signal is input to reference path transmission function, obtains third error signal；
After filter stability to be predicted, due to needing in error signal collection process by reference path krIt is delayed when a
It can acquire, therefore lag k compared with the practical reference signal with after prediction of the second error signalrA time delay, i.e., by institute
It states the second error signal and is input to reference path transmission function, obtain third error signal e2(n-kr)。
Step 211, adjusting the third error signal by the FxLMS function is zero, obtains the anti-noise signal；Its
In, the anti-noise signal is used for the noise reduction of noise cancelling headphone.
It is zero it is possible to further adjust the third error signal by the FxLMS function, obtains the anti-noise letter
Number, filter weights W is updated with FXLMS algorithm2It (n), is zero to obtain accurate anti-noise signal by adjusting third error signal；
Wherein, the anti-noise signal is used for the noise reduction of noise cancelling headphone.
Referring to Fig. 3, a kind of structural block diagram of data processing model of the embodiment of the present invention is shown, as shown in figure 3, will ginseng
Signal p (n) is examined to enter after system by reference path Hr(Z)；Due to Hr(Z) there is krA delay, by reference to the signal after access
For x (n-kr), as first desired signal at the moment, predictive filter W1 is used to predict first prediction signal at the momentFirst desired signal and the first prediction signal are subtracted each other as first error signal e1(n-kr), error is adjusted by LMS algorithm
Signal is zero to obtain more accurate second prediction signal, that is, continues to predict
Obtain the second prediction signalBy the second prediction signalIt is sent into adjusting filter W2 and finds out adjustment signal y (n+
ks), by y (n+ks) pass through secondary path Hs(Z), secondary path Hs(Z) there is ksA delay, therefore the output signal generated is s
It (n), is that s (n) subtracts each other as the second error signal e with the second desired signal d (n) after earmuff is actually passed through by output signal
(n), k is lagged compared with the practical reference signal with after prediction of the second error signal e (n)rA time delay is missed described second
Difference signal e (n) is input to reference path transmission function, obtains third error signal e2(n-kr), it is updated and is filtered with FXLMS algorithm
Device weight W2(n), by adjusting third error signal e2(n-kr) it is zero to obtain accurate anti-noise signal.
Referring to Fig. 4, the noise reduction figure that one of embodiment of the present invention postpones 2 sampled points is shown；Wherein, the letter of Fig. 4
It number may include noise signal, prediction signal and error signal, referring to Fig. 5, the another kind shown in the embodiment of the present invention prolongs
The noise reduction figure of slow 2 sampled points；Wherein, the signal of Fig. 5 may include voice signal, Noisy Speech Signal, de-noising signal and drop
Signal after making an uproar.
Referring to Fig. 6, the noise reduction figure that one of embodiment of the present invention postpones 4 sampled points is shown；Referring to Fig. 7, show
The noise reduction figure of 4 sampled points of another delay in the embodiment of the present invention；
Referring to Fig. 8, the noise reduction figure that one of embodiment of the present invention postpones 6 sampled points is shown；Referring to Fig. 9, show
The noise reduction figure of 6 sampled points of another delay in the embodiment of the present invention；
Referring to Fig.1 0, show the noise reduction figure that one of embodiment of the present invention postpones 8 sampled points；Referring to Fig.1 1, show
The noise reduction figure of 8 sampled points of another delay in the embodiment of the present invention is gone out；It should be noted that Fig. 5, Fig. 7, Fig. 9, Figure 11
Middle de-noising signal, that is, anti-noise signal.
One section of voice signal is added in noise signal, carrys out computational algorithm by comparing the signal-to-noise ratio before noise reduction and after noise reduction
The noise reduction of model；The noise reduction for postponing different sampled points is summarized as shown in table 1, as can be seen from Table 1, there are systems to prolong
In the case where late, the method for the embodiment of the present invention improves to the signal-to-noise ratio of signals with noise, and as delay is counted
Increase signal-to-noise ratio raising amount become smaller, be consistent with actual conditions, noise reduction effect can be effectively improved.
| Delay sampling points | 2 | 4 | 6 | 8 |
| Signals with noise signal-to-noise ratio (dB) | -7.2 | -7.2 | -7.2 | -7.2 |
| Signal-to-Noise (dB) after noise reduction | 9.9 | 4.9 | 0.0 | -2.1 |
| Signal-to-noise ratio improves (dB) | 17.1 | 12.1 | 7.2 | 5.1 |
Table 1:The embodiment of the present invention postpones the signal-to-noise ratio raising table of different sampled points
It should be noted that for simple description, therefore, it is stated as a series of action groups for embodiment of the method
It closes, but those skilled in the art should understand that, embodiment of that present invention are not limited by the describe sequence of actions, because according to
According to the embodiment of the present invention, some steps may be performed in other sequences or simultaneously.Secondly, those skilled in the art also should
Know, the embodiments described in the specification are all preferred embodiments, and the related movement not necessarily present invention is implemented
Necessary to example.
Referring to Fig.1 2, a kind of structural block diagram of the Installation practice of signal processing of the embodiment of the present invention is shown, specifically
It may include following module：
Reference signal obtains module 301, for obtaining reference signal；
First desired signal obtains module 302, for the reference signal to be input to the reference path transmission function,
Obtain the first desired signal；
First prediction signal obtains module 303, for first desired signal to be input to predictive filtering function, obtains
First prediction signal；
First error signal obtains module 304, for obtaining according to first desired signal and first prediction signal
Obtain first error signal；
Second prediction signal obtains module 305, for adjusting the first error signal by lowest mean square LMS function,
Obtain the second prediction signal；
Adjustment signal obtains module 306 and is adjusted for second prediction signal to be input to adjusting filter function
Signal；
Output signal obtains module 307 and is exported for the adjustment signal to be input to secondary path transmission function
Signal；
Second error signal obtains module 308, for obtaining second and missing according to the output signal and the second desired signal
Difference signal；
Third error signal obtains module 309, for second error signal to be input to reference path transmission function,
Obtain third error signal；
Anti-noise signal obtains module 310, for the third error signal to be input to filtering lowest mean square FxLMS letter
Number obtains anti-noise signal；Wherein, the anti-noise signal is used for the noise reduction of noise cancelling headphone.
Preferably, the first error signal acquisition module includes：
First error signal obtains submodule, for first desired signal and first prediction signal to be subtracted each other,
Obtain the first error signal.
Preferably, the second error signal acquisition module includes：
Second expectation signal acquisition submodule, for obtaining second desired signal；
Second error signal obtains submodule, for obtaining the output signal and the second expectation signal subtraction
Second error signal.
Preferably, the second prediction signal acquisition module includes：
Second prediction signal obtains submodule, is zero for adjusting the first error signal by the LMS function, obtains
Obtain the second prediction signal.
Preferably, the anti-noise signal acquisition module includes：
Anti-noise signal obtains submodule, is zero for adjusting the third error signal by the FxLMS function, obtains
The anti-noise signal.
The embodiment of the invention also discloses a kind of electronic equipment, including memory, processor and storage are on a memory simultaneously
The computer program that can be run on a processor, the processor realize the step such as above-mentioned signal processing when executing described program
Suddenly.
Also a kind of computer readable storage medium of the embodiment of the present invention is stored with meter on the computer readable storage medium
The step of calculation machine program, the computer program realizes above-mentioned signal processing processing when being executed by processor.
For device embodiment, since it is basically similar to the method embodiment, related so being described relatively simple
Place illustrates referring to the part of embodiment of the method.
All the embodiments in this specification are described in a progressive manner, the highlights of each of the examples are with
The difference of other embodiments, the same or similar parts between the embodiments can be referred to each other.
It should be understood by those skilled in the art that, the embodiment of the embodiment of the present invention can provide as method, apparatus or calculate
Machine program product.Therefore, the embodiment of the present invention can be used complete hardware embodiment, complete software embodiment or combine software and
The form of the embodiment of hardware aspect.Moreover, the embodiment of the present invention can be used one or more wherein include computer can
With in the computer-usable storage medium (including but not limited to magnetic disk storage, CD-ROM, optical memory etc.) of program code
The form of the computer program product of implementation.
The embodiment of the present invention be referring to according to the method for the embodiment of the present invention, terminal device (system) and computer program
The flowchart and/or the block diagram of product describes.It should be understood that flowchart and/or the block diagram can be realized by computer program instructions
In each flow and/or block and flowchart and/or the block diagram in process and/or box combination.It can provide these
Computer program instructions are set to general purpose computer, special purpose computer, Embedded Processor or other programmable data processing terminals
Standby processor is to generate a machine, so that being held by the processor of computer or other programmable data processing terminal devices
Capable instruction generates for realizing in one or more flows of the flowchart and/or one or more blocks of the block diagram
The device of specified function.
These computer program instructions, which may also be stored in, is able to guide computer or other programmable data processing terminal devices
In computer-readable memory operate in a specific manner, so that instruction stored in the computer readable memory generates packet
The manufacture of command device is included, which realizes in one side of one or more flows of the flowchart and/or block diagram
The function of being specified in frame or multiple boxes.
These computer program instructions can also be loaded into computer or other programmable data processing terminal devices, so that
Series of operation steps are executed on computer or other programmable terminal equipments to generate computer implemented processing, thus
The instruction executed on computer or other programmable terminal equipments is provided for realizing in one or more flows of the flowchart
And/or in one or more blocks of the block diagram specify function the step of.
Although the preferred embodiment of the embodiment of the present invention has been described, once a person skilled in the art knows bases
This creative concept, then additional changes and modifications can be made to these embodiments.So the following claims are intended to be interpreted as
Including preferred embodiment and fall into all change and modification of range of embodiment of the invention.
Finally, it is to be noted that, herein, relational terms such as first and second and the like be used merely to by
One entity or operation are distinguished with another entity or operation, without necessarily requiring or implying these entities or operation
Between there are any actual relationship or orders.Moreover, the terms "include", "comprise" or its any other variant meaning
Covering non-exclusive inclusion, so that process, method, article or terminal device including a series of elements not only wrap
Those elements are included, but also including other elements that are not explicitly listed, or further includes for this process, method, article
Or the element that terminal device is intrinsic.In the absence of more restrictions, being wanted by what sentence "including a ..." limited
Element, it is not excluded that there is also other identical elements in process, method, article or the terminal device for including the element.
Method to a kind of signal processing provided by the present invention and a kind of device of signal processing above have carried out in detail
It introduces, used herein a specific example illustrates the principle and implementation of the invention, the explanation of above embodiments
It is merely used to help understand method and its core concept of the invention；At the same time, for those skilled in the art, according to this
The thought of invention, there will be changes in the specific implementation manner and application range, in conclusion the content of the present specification is not answered
It is interpreted as limitation of the present invention.
Claims (10)
1. a kind of method of signal processing, which is characterized in that including：
Obtain reference signal；
The reference signal is input to the reference path transmission function, obtains the first desired signal；
First desired signal is input to predictive filtering function, obtains the first prediction signal；
First error signal is obtained according to first desired signal and first prediction signal；
The first error signal is adjusted by lowest mean square LMS function, obtains the second prediction signal；
Second prediction signal is input to adjusting filter function, obtains adjustment signal；
The adjustment signal is input to secondary path transmission function, obtains output signal；
According to the output signal and the second desired signal, the second error signal is obtained；
Second error signal is input to reference path transmission function, obtains third error signal；
The third error signal is input to filtering lowest mean square FxLMS function, obtains anti-noise signal；Wherein, the anti-noise
Signal is used for the noise reduction of noise cancelling headphone.
2. the method according to claim 1, wherein described according to first desired signal and described first pre-
Surveying the step of signal obtains first error signal includes：
First desired signal and first prediction signal are subtracted each other, the first error signal is obtained.
3. the method according to claim 1, wherein described according to the output signal and the second desired signal,
The step of obtaining the second error signal include：
Obtain second desired signal；
By the output signal and the second expectation signal subtraction, second error signal is obtained.
4. the method according to claim 1, wherein described adjust described first by lowest mean square LMS function
Error signal, obtain the second prediction signal the step of include：
Adjusting the first error signal by the LMS function is zero, obtains the second prediction signal.
5. the method according to claim 1, wherein described be input to FxLMS letter for the third error signal
Number, obtain anti-noise signal the step of include：
Adjusting the third error signal by the FxLMS function is zero, obtains the anti-noise signal.
6. a kind of device of signal processing, which is characterized in that including：
Reference signal obtains module, for obtaining reference signal；
First desired signal obtains module, for the reference signal to be input to the reference path transmission function, obtains the
One desired signal；
First prediction signal obtains module, and for first desired signal to be input to predictive filtering function, it is pre- to obtain first
Survey signal；
First error signal obtains module, misses for obtaining first according to first desired signal and first prediction signal
Difference signal；
Second prediction signal obtains module, for adjusting the first error signal by lowest mean square LMS function, obtains second
Prediction signal；
Adjustment signal obtains module, for second prediction signal to be input to adjusting filter function, obtains adjustment signal；
Output signal obtains module, for the adjustment signal to be input to secondary path transmission function, obtains output signal；
Second error signal obtains module, for obtaining the second error signal according to the output signal and the second desired signal；
Third error signal obtains module, for second error signal to be input to reference path transmission function, obtains the
Three error signals；
Anti-noise signal obtains module, for the third error signal to be input to filtering lowest mean square FxLMS function, is resisted
Noise cancellation signal；Wherein, the anti-noise signal is used for the noise reduction of noise cancelling headphone.
7. device according to claim 6, which is characterized in that the first error signal obtains module and includes：
First error signal obtains submodule, for subtracting each other first desired signal and first prediction signal, obtains
The first error signal.
8. device according to claim 6, which is characterized in that second error signal obtains module and includes：
Second expectation signal acquisition submodule, for obtaining second desired signal；
Second error signal obtains submodule, for by the output signal and the second expectation signal subtraction, described in acquisition
Second error signal.
9. device according to claim 6, which is characterized in that second prediction signal obtains module and includes：
Second prediction signal obtains submodule, is zero for adjusting the first error signal by the LMS function, acquisition the
Two prediction signals.
10. device according to claim 6, which is characterized in that the anti-noise signal obtains module and includes：
Anti-noise signal obtains submodule, is zero for adjusting the third error signal by the FxLMS function, described in acquisition
Anti-noise signal.
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