119 results about "Adaptive filter coefficients" patented technology

The invention discloses a method for eliminating noise of a long-distance microphone array and a noise-eliminating system. In the invention, the signals collected from two microphones are treated with respect to beam forming, and then the intensified target phonetic signals and the weakened target phonetic signals are obtained; whether target phonetic signals exist in the signals collected from the two microphones is further tested; the update of the adaptive filter coefficient is controlled based on the test result; and lastly, based on a controlled adaptive filter coefficient, the obtained intensified target phonetic signals and the weakened target phonetic signals undergo an adaptive filter process. According to the invention, the performance of noise elimination is greatly improved without affecting the quality of the target phonetics even in case that the microphones are not increased in number.

An impluse response hmn(q) of each transmission path is estimated from N received signals rm (m=1, . . . , M) and a known signal (for a number of users equal to N, n=1, . . . , N). M×N matrix H (q) having hmn(q) as an element and a Q×Q matrix H having H(q) as an element are determined (where Q represents a number of multipaths of each transmitted wave and q=0, . . . , Q−1). A soft decision value b′n(k) is determined from decoded λ2 [bn(k)], and this is used to generate an interference component matrix B′(k) to generate an interference replica H·B′(k). The interference replica H·B′(k) is subtracted from a received matrix y(k) to determine y′(k). y(k) and H are used to determine an adaptive filter coefficient wn(k) to be applied to an n-th user in order to eliminate residual interference components in y′(k) according to the minimum mean square error criteria. y(k) is passed through wn(k) to provide a log-likelihood ratio as a received signal from the user n from which interferences are eliminated.

In an active noise cancellation system having an adaptive filter that outputs a control signal, first and second speakers that emit a canceling signal generated based on the control signal, a microphone that detects an error signal, a correction filter that corrects the base signal by a correction value to generate a reference signal and a filter coefficient updater that successively updates the adaptive filter coefficient based on the error signal and reference signal such that the error signal is minimized, the correction value of the correction filter is set to a sum obtained by adding the transfer characteristic from the first speaker to the microphone, and a product obtained by multiplying the transfer characteristic from the second speaker to the microphone by the prescribed value, thereby enabling to reduce the number of microphones and avoid the increase in parts, the amount of work to provide complicated wiring to the microphones, and the computational load involved in updating the adaptive filter coefficient, while enabling to maintain an area in which noise can be reduced to the same level as that obtained before reducing the number of microphones.

In an active noise cancellation system having an adaptive filter that outputs a control signal, first and second speakers that emit a canceling signal generated based on the control signal, a microphone that detects an error signal, a correction filter that corrects the base signal by a correction value to generate a reference signal and a filter coefficient updater that successively updates the adaptive filter coefficient based on the error signal and reference signal such that the error signal is minimized, the correction value of the correction filter is set to a sum obtained by adding the transfer characteristic from the first speaker to the microphone, and a product obtained by multiplying the transfer characteristic from the second speaker to the microphone by the prescribed value, thereby enabling to reduce the number of microphones and avoid the increase in parts, the amount of work to provide complicated wiring to the microphones, and the computational load involved in updating the adaptive filter coefficient, while enabling to maintain an area in which noise can be reduced to the same level as that obtained before reducing the number of microphones.

The invention relates to an echo cancellation method, an echo cancellation device, a conference tablet computer and a computer storage medium. The method comprises steps: reference signals inputted to a loudspeaker for playback are acquired, and acquisition signals of a microphone are acquired; coefficients of an adaptive filter are acquired, and the adaptive filter coefficients are used for estimating echo signals corresponding to the reference signals; the echo signals are canceled from the acquisition signals, and residual signals are acquired and outputted; and according to the relativity between the residual signals and the reference signals, the coefficients of the adaptive filter are updated. The embodiment creatively adjusts the coefficients of the adaptive filter through the relativity between the residual signals and the reference signals, echo cancellation can be carried out to an extremely large degree, updating on the coefficients of the adaptive filter only needs to be added on the basis of the traditional algorithm, and the newly-added cost is low.

An adaptive spatio-temporal filter for use in video quality of service instruments based on human vision system models has a pair of parallel, lowpass, spatio-temporal filters receiving a common video input signal. The outputs from the pair of lowpass spatio-temporal filters are differenced to produce the output of the adaptive spatio-temporal filter, with the bandwidths of the pair being such as to produce an overall bandpass response. A filter adaptation controller generates adaptive filter coefficients for each pixel processed based on a perceptual parameter, such as the local average luminance, contrast, etc., of either the input video signal or the output of one of the pair of lowpass spatio-temporal filters. Each of the pair of lowpass spatio-temporal filters has a temporal IIR filter in cascade with a 2-D spatial IIR filter, and each individual filter is composed of a common building block,5 i.e., a first order, unity DC gain, tunable lowpass filter having a topology suitable for IC implementation. At least two of the building blocks make up each filter with the overall adaptive spatio-temporal filter response having a linear portion and a non-linear portion, the linear portion being dominant at low luminance levels and the non-linear portion being consistent with enhanced perceived brightness as the luminance level increases.

This invention discloses an self-adaptive mike array system and a method for processing its phone signals, which adds an self-adaptive filter coefficient refresh control module in the mike system to control if the filter should refresh the coefficient or the step-size value when refreshing the coefficient, so that the refreshment of the coefficient is only against the noise so as to avoid the side effect of reducing effective phone signal amplitude while conducting filter coefficient refresh using existing technology when the noise component from the back signals is comparable with or smaller so than the phone component from frontage. This invented system applies a high-order adaptive filter to reduce the noise amplitude to the utmost degree and ensures the best noise-elimination effect no matter what positions the system zero-point directs when multiple noise sources exist.

Provides speech enhancement techniques which are effective even for extemporaneous noise without a noise interval and unknown extemporaneous noise. An example of a signal enhancement device includes: spectral subtraction means for subtracting a given reference signal from an input signal containing a target signal and a noise signal by spectral subtraction; an adaptive filter applied to the reference signal; and coefficient control means for controlling a filter coefficient of the adaptive filter in order to reduce components of the noise signal in the input signal. In the signal enhancement device, a database of a signal model concerning the target signal expressing a given feature by means of a given statistical model is provided, and the filter coefficient is controlled based on the likelihood of the signal model with respect to an output signal from the spectral subtraction means.

The invention discloses a method for eliminating noises of microphone array. The microphone array comprises a unidirectional microphone and an omnidirectional microphone. The procedures are as follows: calibrating the gain of the target direction signal collected by two microphones, so as to lead the target direction signal collected by the two microphones to have the same gain; decreasing the signal collected by the two microphones, which has already calibrated; judging if target speech signal exists in the signal collected by the unidirectional microphone according to average energy of the signal difference between the signal collected by the unidirectional microphone and the signal collected by the two microphones which has already decreased; if target speech signal exists, noise in the signal collected by the unidirectional microphone is eliminated by adopting adaptive filter coefficients from fixed frequency domain; if target speech signal does not exist, noise in the signal collected by the unidirectional microphone is eliminated by adopting adaptive filter coefficients from a new frequency domain.

The invention provides a microphone array device and a beam forming method thereof. The microphone array device can effectively eliminate noise and realize the directive property of a conical beam. Compared with prior art, the invention restrains the noise by controlling the updating of the coefficient of a self-adapting filter with the coefficient a, and the efficiency is pretty high.

The invention relates to a template matching based method for encoding self-adaption intra-frame prediction filtering, belonging to the technical field of image processing. The method comprises the following steps of: acquiring a template of a current encoding block, respectively searching n optimal template matchings in a matching way according to the acquired template; obtaining the prediction of the current encoding block according to the template matchings; obtaining three pixel values of pixel predictions generated in the prediction of the current encoding block according to a standard supply method; computing the mean values of the encoding block predictions obtained by all the template matchings, and using the mean values as targets of the predictions; computing the mean values of n groups of the three pixel values of pixels, using the mean values as the support for generating target values, and computing the optimal self-adaption filter coefficient of a mode according to a least square principle; and generating a predicting value of the intra-frame prediction of the current encoding block. The invention can effectively reduce the residual error after the intra-frame prediction and enhance the objective image quality of decoding by more than 0.2 dB under the condition of same code rate.

A digitized input signal is sampled, to obtain a reference input signal. The reference input signal is spuriously whitened, to obtain a pseudo whitened signal. An echo replica signal is generated on the basis of the pseudo whitened signal and an adaptive filter coefficient. A cancellation error signal is obtained on the basis of an echo signal and the echo replica signal. The adaptive filter coefficient is updated on the basis of the cancellation error signal, the adaptive filter coefficient, and the pseudo whitened signal.

A digitized input signal is sampled, to obtain a reference input signal. The reference input signal is spuriously whitened, to obtain a pseudo whitened signal. An echo replica signal is generated on the basis of the pseudo whitened signal and an adaptive filter coefficient. A cancellation error signal is obtained on the basis of an echo signal and the echo replica signal. The adaptive filter coefficient is updated on the basis of the cancellation error signal, the adaptive filter coefficient, and the pseudo whitened signal.

Characters of the method are that carrying out lowpass filtering and lowering sample process for input signals from far end and near end of communication system; carrying out cross correlation calculation for lowering sample processed input signals; obtaining two maximal cross correlation values and relevant positions so as to reduce amount of calculation for estimating echo time delay. Comparing with prior art, the invention possesses advantages: reducing amount of calculation greatly; coefficient of adaptive filter does not need increment as echo time delay lengthens when being applied to echo canceller; ensuring to estimate echo time delay accurately under condition of lowered occupancy rate of resources and cost; flexible configuring parameter to extend length of time delay so as to promote application range of echo canceller.

An adaptive filter implemented in a communication system transmitter or receiver has a real time clock associated therewith, and one or more coefficients of the adaptive filter are determined based at least in part on an output of the real time clock. For example, the adaptive filter may comprise a coefficient update engine and a memory for storing a plurality of sets of adaptive filter coefficients in association with respective time indicators derived from the output of the real time clock, with the coefficient update engine being configured to determine a particular one of the sets of filter coefficients for use by the adaptive filter based at least in part on one or more of the time indicators. The time indicators may comprise respective time stamps generated based on the output of the real time clock at respective times at which the corresponding sets of coefficients are determined.

The invention discloses a proportional adaptive filter coefficient vector updating method using coefficient reusing. According to the method, a current filter coefficient vector and each Euclidean norm of last R filter coefficient vector differences to sum-of-squares minimization, under the constraint condition that posteriori error is zero; a diagonal distribution matrix G(n) is introduced, and diagonal elements of the matrix correspond to proportional step size of each coefficient. When the method is applied to estimating a coefficient unknown system, convergence rate is higher and stability maladjustment is lower.

Present invention discloses a microphone echo elimination system. It contains speech-sounds detection module, two ends simultaneousness sounding detection module, track filtering module, nonlinear processing module, and control module. Said invention can make adaptive filter reaching effectively eliminating echo target.

Provided is a method and system for estimating distortion in a communications channel including an adaptive equalizer. The method includes determining one or more adaptive filter coefficients associated with a signal passed through the equalizer. The method also includes estimating un-equalized channel distortion based upon the determined adaptive filter coefficients.

By using the adaptive filter, the reference input signal is processed so as to identify a pseudo-signal of a particular signal to be deleted. The pseudo-signal is subtracted from the mixture containing a target signal inputted from a microphone, the particular signal to be deleted, and a noise so as to obtain an error signal. A stationary noise is estimated to obtain a stationary noise estimated value. A non-stationary noise is estimated to obtain a non-stationary noise estimated value. The stationary noise estimated value is mixed with the non-stationary estimated value to obtain a mixed noise estimated value. An update amount is calculated according to a correlation value between the error signal and the reference input signal, and the mixed noise estimated value. According to the update amount, a coefficient of the adaptive filter is updated.

The invention discloses a sound processing method, a sound processing device, electronic equipment and a computer readable storage medium. The method comprises the following steps: in accordance witha plurality of acoustical signals acquired by a microphone array and an image signal which is acquired by a camera, determining a sound pre-processing direction; selecting a pre-processing filter coefficient based on the sound pre-processing direction; implementing pre-processing filtering on the plurality of acoustical signals with the adoption of the pre-processing filter coefficient, so that aninitial signal source signal and an initial noise source signal are obtained; determining an adaptive filter coefficient; and with the adoption of the adaptive filter coefficient, conducting adaptivefiltering on the initial signal source signal and the initial noise source signal, so that an enhanced signal source signal is obtained. With the application of the sound processing method and the sound processing device, the signal source signal can be enhanced, so that the tone quality of sound is improved.

An apparatus for calculating filter coefficients for a predefined loudspeaker arrangement has a multi-channel renderer. The multi-channel renderer calculates a filter coefficient for each loudspeaker of a virtual loudspeaker arrangement, being different from the predefined loudspeaker arrangement, based on a property (e.g. position or type) of a virtual source of an audio object to be reproduced by the predefined loudspeaker arrangement. Further, the multi-channel renderer determines an adapted filter coefficient for a loudspeaker of the predefined loudspeaker arrangement based on one or more calculated filter coefficients of one or more loudspeakers of the different virtual loudspeaker arrangement.

The present invention relates to a method for processing a microphone signal and a system for audio signal processing with feedback reduction. The method comprises processing the microphone signal by an adaptive feedback suppression filtering means; processing the microphone signal by an adaptive feedback compensation filtering means; and wherein the processing by the adaptive feedback suppression filtering means is performed in dependence on the processing by the adaptive feedback compensation filtering means. The system comprises an adaptive feedback compensation filtering means; and an adaptive feedback suppression filtering means configured to be adapted on the basis of the adapted filter coefficients of the adaptive feedback compensation filtering means.

A variable update step size is determined in proportion to a magnitude ratio or magnitude difference between a first residual signal and a second residual signal. The first residual signal is obtained by using adaptive filter coefficient sequence, where the adaptive filter coefficient sequence has been obtained in previous operations of the adaptive equalizer. The second residual signal is obtained by using a prior update adaptive filter coefficient sequence, where the prior update adaptive filter coefficient sequence is obtained by performing a coefficient update with an arbitrary prior update step size on the adaptive filter coefficient sequence having been obtained in previous operations of the adaptive equalizer.

An apparatus for canceling an acoustic echo signal caused by a far-end talker signal is provided. The apparatus for canceling an acoustic echo signal includes: a variance estimating unit configured to estimate a variance of a first audio signal of a near-end talker signal and a first noise signal of the near-end talker signal; a step size determining unit configured to determine a step size by using the variance of the first audio signal and the variance of the first noise signal; an adaptive filter coefficient updating unit configured to update an adaptive filter coefficient of an adaptive filter by using the step size; and an acoustic echo canceling unit configured to estimate an acoustic echo signal by using the adaptive filter coefficient, and cancel the acoustic echo signal from a microphone input signal by using the estimated acoustic echo signal.

The invention discloses a coefficient updating method for an adaptive filter in adaptive echo cancellation, and the method comprises the steps: estimating an echo signal y(k) according to a reference signal x(k) of a sound generation unit through the adaptive filter; calculating a residual signal e(k) according to the echo signal y(k) and a signal d(k) picked by a microphone; calculating a power spectrum xPow(f) of a frequency domain reference signal X(f); calculating a power spectrum ePow(f) of a frequency domain residual signal E(f); calculating the correlation power spectrum xePow(f) of a conjugate residual signal E*(f) of the frequency domain residual signal E(f) and the frequency domain reference signal X(f); calculating the correlation coefficient cohxe(f) of X(f) and E*(f); enabling a median cohxemed of cohxe(f) to serve as the adaptive step factor of the adaptive filter at each frequency point, and updating the coefficient of the adaptive filter. According to the technical scheme of the invention, the method enables the correlation coefficient between the residual signals and the reference signal to serve as the adaptive step factor so as to update the coefficient of the adaptive filter, and can achieve the effective echo cancellation of each voice state.

The invention discloses a space-time self-adaptive filtering method and device. The space-time self-adaptive filtering method includes the steps of obtaining and storing multi-channel base band data, calculating the space-time self-adaptive filtering coefficient w according to the stored multi-channel base band data, carrying out smoothing processing on the space-time self-adaptive filtering coefficient w, obtaining the smoothed coefficient w<smooth>, and carrying out space-time filtering on the obtained multi-channel base band data according to the smoothed coefficient w<smooth>. The space-time self-adaptive filtering method and device can slow down the fluctuations of the space-time self-adaptive filter coefficients.

The invention disclose a polarization shift keying modulation-demodulation method, a system and a method for updating self-adaptive filtering coefficients of a reception end. The polarization shift keying modulation-demodulation method comprises the following steps: at a transmission end, modulating any QPSK (quadrature phase shift keying) signal (the formula is as shown in the specification) in an X polarization direction and modulating a Y polarization signal (the formula is as shown in the specification) same as or opposite to an X polarization signal (the formula is as shown in the specification) in a Y polarization direction according to an input signal S(n) by using a QPSK manner; at the reception end, demodulating a received signal into a corresponding electric signal by using a polarization multiplexing QPSK manner and carrying out digital signal processing to reduce the input signal S(n) after ADC sampling and quantification, wherein an improved CMA method is used during the digital signal processing to update the self-adaptive filtering coefficients. The polarization shift keying modulation-demodulation method has the advantages that polarization shift keying immunity phase noise is provided, the optical fiber nonlinear influence is reduced, important function is brought to ultralong-span transmission, the signal transmission / reception completely inherits the mature hardware architecture of polarization multiplexing QPSK, the realization is simple and high practicability is achieved.

The invention relates to a self-adaptive control method and a self-adaptive control device, wherein the method comprises the steps of: calculating the errors of an excepting signal and an estimating signal fed back by an output signal and calculating an error vector according to the errors; according to iteration times and the errors, calculating and updating the iteration times, and / or according to an amplitude range and the errors, calculating and updating the amplitude range; iteratively calculating the variables of self-adaptive filter coefficients according to the auto-correlative matrix of an output vector formed by the output signal, the iteration times and the amplitude range; updating the self-adaptive filter coefficients according to the variables of the self-adaptive filter coefficients; and processing the output signal by a self-adaptive filter to obtain the estimating signal fed back by the output signal. Therefore, the invention discloses a self-adaptive control method and a self-adaptive control device; in the method, two parameters, i.e. amplitude range and iteration times, are calculated according to an error signal, so that the parameters vary along with the variation of error, thus self-adaptively regulating the rate of convergence, the stable-state error and the algorithm complexity of the algorithm.

The invention discloses a radar moving target detection method based on a cognitive framework. The radar moving target detection method mainly solves the problem that in the strong clutter background, an existing method is poor in detection performance for a low-speed target. The achieving process comprises the following steps of separating ground clutter components from backward waves; obtaining a clutter image of a current frame according to the ground clutter components; sensing the environment according to the clutter image and separating the current frame into a noise region and a clutter region; calculating coefficients of associations according to the ground clutter components, utilizing the coefficients of associations to correct antenna pointing errors, and storing backward wave data after corrected to an environment dynamic data bank (EDDB); and utilizing the backward wave data of the EDDB to estimate an interference covariance matrix according to division of the current frame; obtaining a self-adaption filter coefficient according to the estimated interference covariance matrix, and conducting self-adaption filtering processing on input data; and conducting constant false alarm detection on output of a filter. The radar moving target detection method has the advantage of greatly improving detection performance under the condition that an existing device is not greatly changed, and can be used for conducting detection on the low-speed target in the strong clutter background.

A system for filtering digital television signals is provided. The system comprises a generator for providing a first data sequence to a private data packetizer, and a transmitter for transmitting the packetized first data sequence in a data channel of a digital television signal. The system further includes a receiver for receiving the digital television signal and recovering the first data sequence. The receiver includes a channel estimator for providing an estimate of channel characteristics, such as estimated channel impulse estimate and estimated noise variance. The receiver further includes an adaptive equalizer filter having an input for receiving the digital television signal and an input for receiving adaptive filter coefficients. The receiver further includes a coefficient processor for calculating adaptive filter coefficients based on the channel estimate, and providing the adaptive filter coefficients to the adaptive equalizer filter. The digital television signal is thus filtered to remove undesired channel effects.