177 results about "Finite impulse response" patented technology

The invention belongs to the field of power equipment monitoring, and discloses an electrical signal acquisition system based on intelligent dynamic sampling, which comprises a signal acquisition module, a signal conditioning module, an abrupt change detection module, an impedance calculation module and an upper computer, and is characterized in that the signal acquisition module comprises a first ADC module, a second ADC module, a first MCU module and a second MCU module. Short-circuit impedance real-time calculation and waveform abrupt change detection are adopted for cooperative judgment, and when equipment operates stably, the sampling rate of the system is kept low; when impedance changes or waveform changes suddenly, the sampling rate is improved automatically, important signal changes are recorded accurately, and waveform abrupt change detection is carried out by adopting an edge detection algorithm improved based on an FIR (Finite Impulse Response) filter. The system ensures the time sequence consistency of data under different sampling frequencies through multi-channel data synchronization and timestamp management, and meanwhile, smooth transition is performed by applying an interpolation algorithm during sampling switching, so that the continuity of a data sequence is ensured. The data redundancy is reduced; and the integrity of key information is ensured.

A closed-loop neuromodulation system, including an electrode array that is implantable to a brain of a subject, analog front-end device (AFD) for selectively selecting and reading a plurality of channels from electrode array, a finite impulse response (FIR) filter for selectively filtering signals from the AFD, a feature extraction engine (FEE) operatively connected to the FIR filter, configured to selectively extract features from signals provided by the FIR filter, a tree-structured hierarchical neural network classifier for detecting disease symptoms, and a multi-channel stimulator having high-voltage (HV) drivers operatively connectable to the electrode array.

The invention belongs to the technical field of underwater acoustic engineering and digital signal processing, and particularly relates to a fractional delay FIR (Finite Impulse Response) phase calibration method and system of a multichannel sonar system. Comprising the steps of signal acquisition and reference channel selection; high-precision relative delay estimation; calculating a cross-correlation function of other channel signals and the reference channel signal, performing coarse estimation by searching a peak point of the amplitude of the cross-correlation function, and performing fine estimation on the peak position by using a parabola interpolation method to obtain the delay time of each channel relative to the reference channel; designing an FIR fractional delay filter; digital filtering and phase calibration; verifying a calibration effect; and calculating the phase of each channel signal at the target frequency point after calibration, and counting the standard deviation of each channel signal so as to evaluate the improvement degree of phase consistency. The method aims at overcoming the defect that traditional integral multiple sampling delay correction precision is insufficient, high-precision phase compensation of a sub-sampling point level is achieved, and therefore the performance of algorithms such as beam forming of a multi-channel sonar system is remarkably improved.

Serializer / deserializer (SerDes) modules, equalizers, and equalization techniques having robust parameter initialization may substantially reduce convergence time. One illustrative equalizer includes: a discrete-time, finite impulse response (“FIR”) filter to convert a receive signal to a filtered signal; a decision element to determine channel symbols represented by the filtered signal; and a controller. The controller is configured to, for each of multiple values in a search range, estimate a performance of the equalizer based on the channel symbols and at least one of the filtered signal or an input signal to the decision element; configured to find a centroid value based on the performance for each of the multiple parameter values in the search range; and configured to derive an initial value for the parameter from the centroid value.

A feature extraction and simulation method for sound signals of an autonomous navigation ship tunnel thruster. A digital filter is used to process measured signals to remove spike signals, and the characteristics of residual wideband floor noise signals are analyzed. A finite impulse response filter is designed, and the impulse response of the finite impulse response filter is convolved with white Gaussian noise, so that simulated noise is matched with frequency-domain characteristics of floor noise signals. A spike signal amplitude is calculated, and a group of sine wave signals having a corresponding frequency are generated as spike signals. Narrowband spike signals and wideband floor signals are superposed and synthesized into simulated tunnel thruster noise. A feasible solution is provided for research and analysis of sound signals of a tunnel thruster. The sound characteristics of the tunnel thruster are accurately extracted, a predicted sound level is improved, and a tunnel thruster sound source database is established, thus providing valuable data support for signal quality analysis of a ship autonomous navigation system, fault diagnosis and improvement of a control strategy for the tunnel thruster.

Certain disclosed embodiments pertain to suppressing interference in a wireless communication system. For example, a method of suppressing interference can include receiving one, two, or more first signals including components from a plurality of sub-channels. Each of the first signals can be processed by a Finite Impulse Response filter adapted using an LMS update algorithm,

The invention discloses a distribution network power line anti-interference communication method based on adaptive filtering, and belongs to the technical field of distribution network power line communication. According to the method, a communication signal adopting a frequency shift keying modulation mode is acquired from a power line coupler of a distribution network through a signal acquisition module, the communication signal is preprocessed by using a digital signal processing unit, spectral analysis is performed on the preprocessed signal, and characteristic parameters of interference noise are extracted; a coefficient vector of a finite impulse response adaptive filter is initialized based on the characteristic parameters, the order of the filter is in direct proportion to the reciprocal of the dominant interference frequency, fine adjustment is carried out based on noise energy distribution through a table look-up method or a linear mapping relation, and the weight coefficient of the filter is adjusted in real time in the communication process. The adjustment step length is dynamically adjusted according to the real-time estimated signal-to-noise ratio, and finally, the processed signal is output through the adaptive filter and data demodulation is carried out. The method is mainly used for improving the anti-interference capability and the communication reliability of the power private line communication of the distribution network.

The invention discloses a gate fault detection method and system, and relates to the technical field of fault diagnosis and health monitoring, and the method comprises the steps: collecting a gate vibration signal, extracting a main modal frequency, setting a sampling frequency and a passband range, designing a finite impulse response filter for filtering, and carrying out the optimization through a particle swarm algorithm, thereby obtaining an enhanced signal; extracting features in the enhanced signal for integration to obtain a feature vector, mapping the feature vector to a discrete state set by using a rule threshold matching method, and obtaining a gate state; the method comprises the following steps: acquiring historical data for sampling, constructing a state transition probability matrix, calculating a steady-state probability vector according to the state transition probability matrix, combining a gate state, generating a state sequence track, setting an influence factor and a weight by using an empirical rule, and calculating a fault occurrence probability for risk detection; according to the method, the gate fault detection precision, efficiency and reliability are remarkably improved.

The invention discloses a GNSS element signal interference suppression method and system based on double complex number modeling, and the method comprises the steps: firstly introducing a double complex number model, carrying out the modeling of a received multi-frequency multi-path signal, and obtaining a GNSS element signal; secondly, carrying out modular operation projection on the GNSS element signal to obtain time-frequency domain analysis of the element signal, and obtaining a ridge value through detection; and correcting the ridge value to obtain instantaneous frequency estimation and instantaneous frequency modulation slope estimation of the element signal interference carrier and subcarrier, and applying the instantaneous frequency estimation and the instantaneous frequency modulation slope estimation to a finite impulse response filter to obtain the finite impulse response filter based on double complex numbers. And finally, performing double complex Kalman filtering on the received element signal to obtain an interference estimation value, removing the interference estimation value from the received element signal, and taking a real part to obtain a GNSS expected signal. According to the method, the high-precision interference is estimated by using the high-precision interference parameter estimation value and the double-complex Kalman filtering, and interference suppression in a multi-frequency multi-path environment is efficiently realized.

The invention relates to the technical field of optical communication, and discloses a multi-dimensional and multi-phase-based 50G PON signal noise compensation method, which comprises the following steps: S1, generating a mixed signal, including superposing a multi-phase orthogonal pilot signal into a data signal time domain at a transmitting end according to a preset proportion lower than the power of a data signal; and S2, transmitting the mixed signal in a polarization multiplexing mode, wherein the polarization multiplexing adopts double-channel parallel transmission of an X polarization state and a Y polarization state. Multi-phase orthogonal pilot signals are superposed to a data signal time domain in a low-power proportion at a transmitting end, polarization multiplexing dual-channel transmission is adopted, a narrow-band filter is utilized at a receiving end to separate pilots and calculate channel damage parameters, and a finite impulse response filter is configured to perform linear equalization compensation. And the simplified Kalman filtering algorithm is combined to estimate the phase noise and correct the phase, so that collaborative suppression of the linear channel damage and the phase noise in the 50G PON signal is facilitated.

A method and a circuitry to perform clock and data recovery, CDR is provided. The method includes the steps of obtaining an analogue communication signal characterized by a symbol frequency Fsymbol; and performing an analogue-to-digital conversion of the analogue communication signal according to a sampling rate Fsample targeting Fsymbol*(M / L) thereby obtaining a digital signal. The method includes up-sampling the digital signal by L; filtering the up-sampled digital signal with filter coefficients of a finite impulse response, FIR, filter to perform a fractionally-spaced equalisation; and down-sampling the filtered digital signal by M resulting in a recovered digital signal. Intermediate filter coefficients are obtained for the FIR filter and a phase error is determined based on the recovered digital signal. The intermediate filter coefficients are interpolated based on the phase error to compensate for the phase error, resulting in interpolated filter coefficients; and the filter coefficients of the FIR filter are updated with the interpolated filter coefficients.

A control device which controls an operation of a compensation device which compensates for birefringence and / or polarization mode dispersion, which is received by signal light having propagated through an optical transmission line, by digital signal processing using a finite impulse response filter includes: a detection signal reception unit which receives a detection signal which is a signal indicating a detection result of a detection device which optically detects polarization fluctuation in the optical transmission line; and a setting unit which decides a setting regarding an update frequency or an update interval of the number of taps of the finite impulse response filter or an update frequency or an update interval of a tap coefficient of the finite impulse response filter, based on the detection result of the detection device.

Serializer / deserializer (SerDes) modules, equalizers, and equalization techniques having robust parameter initialization may substantially reduce convergence time. One illustrative equalizer includes: a discrete-time, finite impulse response (“FIR”) filter to convert a receive signal to a filtered signal; a decision element to determine channel symbols represented by the filtered signal; and a controller. The controller is configured to, for each of multiple values in a search range, estimate a performance of the equalizer based on the channel symbols and at least one of the filtered signal or an input signal to the decision element; configured to find a centroid value based on the performance for each of the multiple parameter values in the search range; and configured to derive an initial value for the parameter from the centroid value.

The present disclosure provides a method for realizing a speaker array-oriented multiple filter system and a related device, belonging to the technical field of audio systems. The method includes: merging, before real-time audio processing, filters of a plurality of sound effect modules in an audio signal processing flow offline to form a finite impulse response (FIR) multiple filter network. The present disclosure places most of computation in an offline processing flow by merging the filters of the plurality of sound effect modules in offline convolution, so that the computation amount of real-time processing is greatly reduced.

Data transceivers including a transmitter configured with a digital filter, and a receiver configured with an equalizer, are equipped with logic to measure a combined pulse response to a symbol generated by the transmitter at an output of the equalizer, adjust the combined pulse response by an impulse response of the digital filter to generate an adjusted pulse response, and modify the digital filter with one or more floating taps based on the adjusted pulse response.

The invention discloses a high-precision integrated temperature sensor circuit and application, and relates to the technical field of integrated circuits, and the high-precision integrated temperature sensor circuit comprises a band-gap reference circuit, a buffer circuit, an analog-to-digital conversion circuit, a two-phase non-overlapping clock generation circuit and an FIR (Finite Impulse Response) digital filter. It needs to be explained that a key circuit sigma-delta modulator adopts an integrator cascade feed-forward structure CIFF, compared with a CIFB with a feedback structure, an STF function of an ADC of a feed-forward structure is close to 1, a peak value can appear only at a high frequency, only a very small error signal can pass through a whole loop, and therefore the stability of the analog-to-digital converter is greatly improved. Therefore, the gain of the amplifier in the first-stage integrator can be made relatively large, and noise and nonlinearity generated by the rear-stage integrator are effectively suppressed. Moreover, each stage of integrator does not process a feedback signal with high-frequency noise, so that the bandwidth requirement on the next stage of operational amplifier is reduced, the power consumption required by the CIFF structure is lower, and meanwhile, the output swing has better stability due to no feedback structure.

Aspects of the present disclosure include a biometric device configured to receive biometric signals from sensors placed on a subject, and attenuate at frequencies causing noise in the biometric signals. Aspects are directed to a finite impulse response (FIR) filter configured to attenuate noise frequencies caused by line frequencies and / or flicker frequencies. Aspects of the FIR filter may be configured based on an analog-to-digital (ADC) sampling rate.

The invention discloses a parametric array loudspeaker nonlinear distortion modeling and compensation method based on deep learning. The method comprises the following specific steps: (1) recording an audio sound signal output by a parametric array loudspeaker system and an input signal of the audio sound signal at a listening position where nonlinear distortion needs to be suppressed, and making a data set for modeling; (2) performing overall modeling on the parametric array loudspeaker system by using a neural network F, and training the neural network F by using the data set; modeling a linear part of the system by using an FIR (Finite Impulse Response) filter model Flin; (3) using the trained neural network F and the model Flin to train a neural network G as an inverse filter of the system; and (4) preprocessing an audio signal expected to be replayed through the neural network G, and inputting the preprocessed audio signal into a parametric array loudspeaker system to realize nonlinear compensation of the system. According to the method, accurate modeling and effective compensation can be carried out on the nonlinear distortion of the parametric array loudspeaker, and the nonlinear distortion of the parametric array loudspeaker is remarkably inhibited.

The invention relates to an analog-to-digital converter of an embedded filter, a driving chip and electronic equipment, and the analog-to-digital converter comprises a first analog-to-digital conversion module which is a successive approximation type analog-to-digital converter with a plurality of sampling capacitors and a plurality of sampling periods, the first analog-to-digital conversion module realizes a finite impulse response (FIR) filtering effect on an input sampling signal through charge sharing among sampling capacitors; and while part of the sampling capacitors still perform the process of sampling the input signals, the successive approximation quantization process of the signals on part of the sampling capacitors which have already been sampled is started. The analog-to-digital converter provided by the embodiment of the invention has a filtering characteristic and also has the characteristics of high bandwidth, low power consumption and small area.

Systems and methods for digital predistortion (DPD) are disclosed herein. In an example embodiment, a digital front-end circuit includes a digital predistortion (DPD) block having a first input terminal and first output terminal, a PA having a second input terminal and second output terminal, and a transmitter coupling the first output terminal at least indirectly with the second input terminal. The DPD block is configured to receive a first input signal and to provide a first output signal having first and second components at the first output terminal. The DPD block includes a main distortion kernel that is configured to generate the first component, and a nonlinear memory kernel that is configured to generate the second component. The nonlinear memory kernel is configured to perform processing at least in part by a nonlinear envelope modulator including a linear finite impulse response (FIR) filter.

The invention belongs to the technical field of ground penetrating radar signal processing, and relates to a ground penetrating radar signal denoising method based on optimal proportion-kurtosis joint masking, which comprises the following steps: carrying out short-time Fourier transform on a single-channel ground penetrating radar echo signal to obtain a complex time-frequency graph and a power spectrum thereof; calculating an optimal proportion masking index; calculating the frequency domain kurtosis of each frame according to the amplitude of the complex time-frequency graph in the time-frequency domain, and adaptively determining a kurtosis threshold; constructing an optimal proportion masking matrix, constructing a kurtosis masking matrix by using the kurtosis threshold, and multiplying the optimal proportion masking matrix and the kurtosis masking matrix point by point to obtain a final masking matrix; the final masking matrix is multiplied by the complex time-frequency graph, then inverse short-time Fourier transform is executed, and a preliminary denoising time-domain signal is reconstructed; and applying zero-phase finite impulse response band-pass filtering to obtain a final high-signal-to-noise-ratio ground penetrating radar signal. The method does not need to additionally collect a reference channel, is low in calculation complexity, and can remarkably improve the signal-to-noise ratio of the ground penetrating radar data and the target identifiability.

A system for beamforming and filtering. In some embodiments, the system includes an array of antenna elements; and a front-end circuit connected to the antenna elements, the front-end circuit including a plurality of delay elements. The delay elements may be configured to provide beam forming; and to operate as delay elements in a finite impulse response filter.

The invention provides a digital beam forming method and device based on multiple time delays and scale correction, and the method comprises the steps: determining a reference time delay group based on a plurality of reference positions divided from a corresponding breadth range in a distance direction; on the basis of the reference time delay group, performing finite impulse response (FIR) time delay filtering processing, scale transformation processing and pulse compression processing on an echo signal in sequence; and on the basis of an error compensation function, receiving scanning SCORE weighting is carried out on the signal after pulse compression, and a digital beam forming DBF composite signal is obtained. Therefore, the problems of inter-channel time delay and scale mismatch caused by view angle change in a large-breadth SAR system are effectively suppressed, the signal-to-noise ratio and the target positioning precision are improved, meanwhile, residual phase errors introduced by scale change are eliminated through an error compensation mechanism, and finally high-precision digital beam forming is achieved.

The invention discloses a sound signal feature extraction method based on loudness. The method comprises the steps that a signal acquisition module acquires and stores sound signals of a rolling bearing in real time, acquires original sound signals and transmits the original sound signals to a computer end; acquiring a loudness time spectrum of the sound signals by calculating the loudness of each intercepted short-time signal by adopting a time domain short-time slip interception method on the collected original sound signals; identifying and extracting a pulse component in the loudness time spectrum, analyzing the short-time signal characteristic loudness corresponding to the pulse component, designing an optimal finite impulse response filter by taking the maximum characteristic as a parameter basis, and filtering the original sound signal; and separating a low-frequency component from a high-frequency carrier in the signal by using a Hilbert transform envelope analysis method, and extracting a low-frequency characteristic frequency closely related to the fault characteristics of the rolling bearing, thereby realizing accurate diagnosis of the bearing fault.

An equalizer circuit includes: an analog front end circuit configured to receive an analog input signal from a transmission line; an analog finite impulse response filter circuit including: a sample and hold circuit configured to sample an output of the analog front end circuit; and a weighting circuit configured to weight the output of the analog front end circuit to generate a feedforward signal; and a decision feedback equalizer circuit configured to receive an output of the analog front end circuit and the feedforward signal.

The invention relates to a road cavity detection and identification method and system based on multichannel optical fiber sensing. The method comprises the following steps: acquiring and storing Rayleigh scattering light time domain signals which are acquired by a DAS underground sensing system at different positions and different time periods of a detection road section and contain active knocking signals; determining a frequency range of the active knocking signal according to a frequency spectrum obtained after the Rayleigh scattering light time domain signal is subjected to fast Fourier transform processing; carrying out filtering processing on the Rayleigh scattering light time domain signal by adopting a finite impulse response band-pass filter to obtain a filtered signal; the filtered signal is input into a PhaseNetDAS model for seismic phase pickup, and an active source seismic phase is obtained; associating the active source seismic facies with the active source event to obtain a seismic facies report including event latitude and longitude, time and seismic facies arrival time; and inverting the velocity structure of the underground medium by using the seismic phase report by using a tomography method, and determining a road cavity detection and recognition result, thereby improving the accuracy of road cavity detection.

The invention discloses a bearing fault diagnosis method based on feature mode decomposition and heterogeneous model fusion, and belongs to the technical field of mechanical fault diagnosis. An original vibration signal of the rolling bearing is collected; independent of any bearing geometric parameter or fault characteristic frequency information, a finite impulse response (FIR) filter is iteratively optimized to maximize a correlation kurtosis (CK) value, and a plurality of intrinsic mode functions (IMF) are adaptively decomposed; selecting first M IMFs with the highest CK value, extracting time domain, frequency domain and nonlinear complexity features of the IMFs, generating high-order derivative features by adopting depth feature synthesis DFS, and constructing an enhanced fusion feature vector; and finally, inputting a stacked integrated classifier consisting of six types of heterogeneous basic learners and an XGBoost element learner, and outputting a fault diagnosis result. According to the method, high-precision and high-robustness diagnosis can still be realized under the working conditions of speed change, strong noise and weak faults.

Example embodiments describe a method and a circuitry to perform clock and data recovery, CDR. The method comprises the steps of obtaining an analogue communication signal characterized by a symbol frequency Fsymbol; performing an analogue-to-digital conversion of the analogue communication signal according to a sampling rate Fsample targeting Fsymbol *(M / L) thereby obtaining a digital signal; up-sampling the digital signal by L; filtering the up-sampled digital signal with filter coefficients of a finite impulse response, FIR, filter to perform a fractionally-spaced equalisation; down-sampling the filtered digital signal by M resulting in a recovered digital signal; obtaining intermediate filter coefficients for the FIR filter; determining a phase error based on the recovered digital signal; interpolating the intermediate filter coefficients based on the phase error to compensate for the phase error, resulting in interpolated filter coefficients; and updating the filter coefficients of the FIR filter with the interpolated filter coefficients.

The invention relates to the technical field of wireless communication, and discloses a novel channel estimation method based on residual frequency offset elimination, which comprises the following steps of: despreading descrambled pilot frequency data to obtain a channel estimation value after noise smoothing, and transmitting the channel estimation value to an FIR (Finite Impulse Response) filter to generate a noise suppression channel estimation signal; phase-frequency response of the noise suppression channel estimation signal is obtained through calculation, conjugate multiplication and smoothing are conducted on the phase-frequency response of the noise suppression channel estimation signal and the phase-frequency response of the FIR filter, a residual frequency offset estimation signal for suppressing the noise influence is obtained and compensated to the noise suppression channel estimation signal output by the FIR filter, and a noise suppression channel estimation value for eliminating the residual frequency offset influence is obtained. And balancing with the service de-spreading signal compensated by the residual frequency offset estimation signal to obtain a final output signal. According to the method, the phase-frequency response characteristics of the filter are deeply analyzed, the FIR filter is used for improving the signal-to-noise ratio, meanwhile, the residual frequency offset is estimated through the phase-frequency characteristics of the FIR filter, finally, the phase error is compensated for, an accurate channel estimation value is obtained, and the signal detection precision is improved.

An integrated circuit includes a continuous time delta sigma analog-to-digital converter (CTDS ADC) and a test circuit for testing the CTDS ADC. The test circuit converts multibit digital reference data to a single-bit digital stream. The test circuit then passes the single-bit digital stream to a finite impulse response digital-to-analog converter (FIR DAC). The FIR DAC converts the single-bit digital stream to an analog test signal. The analog test signal is then passed to the CTDS ADC. The CTDS ADC converts the analog test signal to digital test data. The test circuit analyzes the digital test data to determine the accuracy of the CTDS ADC.