31 results about "Time domain signal processing" patented technology

In an arrangement for receiving CDMA signals, insertion of guard intervals is rendered unnecessary and transmission efficiency loss is suppressed, along with greatly reducing the computational burden of weight calculations. Impulse responses of a transmission channel are obtained by time-domain signal processing, the impulse responses are Fourier transformed and converted into frequency domain signals, equalizing filter weights are calculated using the frequency domain impulse responses, the calculated frequency domain weights are converted to time domain weights using an inverse Fourier transform, the received signals are filtered using time-domain signal processing, and data signals are demodulated by despreading the equalized signals.

The invention discloses a channel estimation device and a channel estimation method of a nonideal synchronous single-carrier frequency division multiple access system. The channel estimation method comprises the following steps of: converting a received time domain base band signal into frequency domain data by a time domain signal processing unit, separating data of each user from the frequency domain data and outputting; acquiring a pilot frequency character in the user data from the user data by a pilot frequency position processing unit, and estimating the channel at a pilot frequency position by utilizing the pilot frequency character in the user data to obtain a channel estimation value of the pilot frequency position; carrying out time bias estimation compensation, noise reduction, filtering and time bias recovery on the channel estimation value of the pilot frequency position, then carrying out frequency bias estimation and initial phase difference compensations and outputting to the channel estimation unit of the data position; and estimating the channel estimation value of the user data by a data position processing unit according to the channel estimation value of the pilot frequency position, wherein the channel estimation value of the pilot frequency position is received from the pilot frequency position processing unit. The invention overcomes the defects of high complexity and sensitivity to time frequency bias of the traditional channel estimation algorithm.

A digital equalizer comprises a matched filter that, in conjunction with an FIR filter, assures a single peak with substantially greater energy than other peaks caused by ghosts, thereby permitting synchronization even with multiple, arbitrarily strong ghosts caused by strong multipathing, multiple transmitters, or both.

A chemical detection system performs controlled exposures to diagnose the pneumatic components and chemical sensors prior to measuring a chemical emission. A control module provides the system control and data processing to perform the diagnosis. The control module manipulates an emission sample retrieval system to provide precise exposure during the diagnostic routines. A sensor interface circuit interrogates the chemical sensors and stores the data for analysis. The chemical sensor exhibits predictable changes in response during predetermined exposure scenarios. By utilizing numerous time domain signal processing techniques, both system and sensor level fault conditions are determined.

A respiratory signal detection and time domain signal processing method and system classifies respiratory phases and determines respiratory time data useful in respiratory health determinations. The method and system analyze respiratory signals collected at multiple detection points at least one of which ensures that respiratory phases can be properly classified. Moreover, the method and system employ a time domain signal processing approach that facilitates determination of respiratory time data while realizing savings in computing power relative to frequency domain processing approaches.

The invention relates to an underwater target gammatone discrete wavelet coefficient auditory feature extraction method. Noisy data measured actually are preprocessed at first on the basis of Fourier transform and logarithm compression and in incorporation with a gammatone auditory filter bank and discrete wavelet transform to enable target signals to be approximately stable in the short time; Fourier transform is conduced on the preprocessed data, time-domain signal processing is converted into frequency-domain signal processing, auditory filtering and logarithm compression are conducted on the preprocessed data through the gammatone auditory filter bank, discrete wavelet transform is conducted on the data on which logarithm compression is conducted at last, and the dimensionality of the data is reduced. The underwater target gammatone discrete wavelet coefficient auditory feature extraction method can extract effective auditory features of underwater target radiation noise, thereby improving the correct recognition rate of the underwater target.

The invention discloses a single-vector hydrophone sound source depth estimation method based on multipath feature matching. The method comprises the steps of receiving a broadband sound pressure of target radiation and a time domain signal of a three-component particle vibration velocity, and processing the time domain signal to obtain acoustic energy flows in x, y and z directions and a sound field intensity spectrum after mean removal; estimating a target azimuth angle by utilizing the acoustic energy flows in the x direction and the y direction and synthesizing a horizontal acoustic energyflow; calculating an estimated value of a target arrival angle according to the ratio of the acoustic energy flow in the z direction to the horizontal acoustic energy flow; carrying out double spectrum analysis on the sound field intensity spectrum subjected to mean value removal by utilizing spectrum analysis to obtain a multipath time delay estimation value; calculating multipath time delay template values corresponding to different sound source depths under the arrival angle according to the estimated value of the target arrival angle in combination with the sound velocity profile; and calculating a difference value between the multipath time delay estimation value and the multipath time delay template values under different sound source depths, and taking the depth corresponding to the multipath time delay template value with the minimum difference value as a target sound source depth estimation value.

The invention provides a gammachirp cepstrum coefficient auditory feature extraction method of underwater targets. On the bases of Fourier conversion and logarithmic compression, a gammachirp auditory filter set is combined, preprocessing is carried out on measured noise data at first, a target signal can be expressed as approximately stable in short time, then Fourier conversion is carried out on the preprocessed data, a time-domain signal is converted into a frequency domain signal to be processed, auditory filtering and logarithmic compression are carried out on the frequency domain signal through the gammachirp auditory filter set, discrete cosine transformation is carried out on the data after logarithmic compression at last, and the number of dimensions of the data is reduced. According to the gammachirp cepstrum coefficient auditory feature extraction method of the underwater targets through gammachirp frequency auditory perception, effective auditory features of underwater target radiation noise can be extracted, and therefore the correct recognition rate of the underwater targets is increased.

The present invention discloses a signal processing method and a data processing method and apparatus. A time-domain to frequency-domain signal processing method includes: pre-processing time-domain data; pre-rotating the pre-processed data by using a rotation factor a·WNn+0.5; performing a discrete Fourier transform (DFT) of N / 4 points on the pre-rotated data; and post-rotating the data transformed by the DFT by using a rotation factor b·WNn+0.5 to obtain frequency-domain data. A frequency-domain to time-domain signal processing method includes: twiddling frequency-domain data; pre-rotating the twiddled data by using a rotation factor c·WNn+0.5; performing a DFT of N / 4 points on the pre-rotated data; and post-rotating the data transformed by the DFT by using a rotation factor d·WNn+0.5; and post-processing the post-rotated data to obtain time-domain data. The present invention increases the efficiency of signal processing.

The invention discloses a time-domain signal processing method for through casing differential resistivity logging. The time-domain signal processing method comprises the steps that transient electromagnetic induction received waveforms at four moments of forward turn-on, forward turn-off, reverse turn-on and reverse turn-off are obtained; the transient electromagnetic induction received waveformsat the adjacent depth points subtract to obtain the responding difference waveform 1, the responding difference waveform 2 and the responding difference waveform 3; the responding difference at the coupling position is replaced through the responding difference at the adjacent depth points, so that the coupling influence is removed; the maximum values of the responding difference waveform 1, theresponding difference waveform 2 and the responding difference waveform 3 at the four moments are selected, and the maximum values are converted to stratum conductivity difference curves; the stratumconductivity difference curve at any moment in any responding difference waveform is selected and integrated to obtain a stratum conductivity curve of the measured well section; the same method is applied to other moments of the responding difference waveforms to generate the stratum conductivity curve of the corresponding well section; the time-domain signal processing method is applied to the four moments of the other two responding difference waveforms to generate the stratum conductivity curve of the corresponding well section; and all the stratum conductivity curves are weighted and added, and the reciprocal value is taken to obtain the stratum conductivity curve.

The invention provides a human body existence induction detection method and device based on Doppler radar, and a storage medium. The method comprises the following steps: performing signal pretreatment on an intermediate frequency signal sampled in an induction range; judging whether a moving object exists in the current space or not through the human body motion detection signal; performing time-domain signal processing and analysis on the micro-motion and respiratory frequency range signals, and judging whether human body micro-motion or respiratory frequency exists in the current space or not; converting the time domain signal after signal pretreatment into a frequency domain signal, extracting a human body respiratory frequency signal through processing and spectral analysis of the frequency domain signal, and judging whether a human body exists in the current space or not; and according to the human body motion detection, the time domain breathing signal detection and the frequency domain breathing signal detection, judging the existence state of the human body in the current sensing range. According to the invention, interference signals can be effectively filtered, and the accuracy and sensitivity of human body existence detection are improved.

In order to improve the accuracy of modulation recognition, the invention provides a signal modulation recognition algorithm based on data enhancement and a convolutional neural network. The method comprises the following steps: firstly, processing a time domain signal in a data set RML2016.10a into a constellation diagram, and dividing pictures into a training set and a test set according to a proportion of 8: 2; secondly, processing the training sets by using four data enhancement methods of rotation, random erasing, overturning and CutMix to obtain four enhanced training sets; respectively inputting the four types of enhanced training sets into a GoogleNet network for training, and continuously optimizing network parameters according to back propagation to obtain a trained network; and finally, sending the test set into the trained GoogleNet network for testing, drawing a curve of which the correct rate changes along with the signal-to-noise ratio, and comparing the improvement effects of different data enhancement methods on the correct recognition rate to obtain an optimal data enhancement method. Compared with other modulation recognition algorithms without data enhancement, the method has the advantages that the risk of model overfitting is reduced, and the generalization ability of the model is improved.

A digital equalizer comprises a matched filter that, in conjunction with an FIR filter, assures a single peak with substantially greater energy than other peaks caused by ghosts, thereby permitting synchronization even with multiple, arbitrarily strong ghosts caused by strong multipathing, multiple transmitters, or both.

The invention discloses a wind profile radar rainfall and non-rainfall adaptive detection system and method. The system comprises system control module, a signal processing module, a digital intermediate frequency receiver plate, an industrial control computer, a data terminal computer and a data processing module. The system control module controls the atmosphere wind field detection process. The digital intermediate frequency receiver plate receives a radio echo signal and obtains domain signals in digital processing. The signal processing module processed the domain signals into atmosphere wind field power spectrum signals. The data processing module processes and analyzes the atmosphere wind field power spectrum signals and automatically configures corresponding detection parameters. The established adaptive detection system automatically determines whether there is rainfall or not and configures corresponding detection parameters in the detection process through a wind profile radar, so that the adaptive detection of the atmosphere wind field in rainfall or non-rainfall weather is achieved, the atmosphere wind field information under different weather conditions can be accurately measured, and better application in meteorological research and weather forecast is achieved.

A chemical detection system performs controlled exposures to diagnose the pneumatic components and chemical sensors prior to measuring a chemical emission. A control module provides the system control and data processing to perform the diagnosis. The control module manipulates an emission sample retrieval system to provide precise exposure during the diagnostic routines. A sensor interface circuit interrogates the chemical sensors and stores the data for analysis. The chemical sensor exhibits predictable changes in response during predetermined exposure scenarios. By utilizing numerous time domain signal processing techniques, both system and sensor level fault conditions are determined.

The invention relates to artificial intelligence, and provides an audio noise reduction method and device, equipment and a storage medium. The method comprises the following steps: pre-processing noise frequency to obtain frequency spectrum information, processing the frequency spectrum information based on a frequency domain signal processing network to obtain frequency spectrum mask features, acquiring time-frequency features according to the frequency spectrum information and the frequency spectrum mask features, processing the time-frequency features based on a time domain signal processing network to obtain time-frequency mask features, generating a predicted audio according to the time-frequency features and the time-frequency mask features, adjusting network parameters of a preset learner based on the predicted audio and the pure audio to obtain a noise reduction model, acquiring a request audio, and performing noise reduction processing on the request audio based on the noise reduction model to obtain a target audio. According to the method, the noise reduction accuracy and real-time performance of the request audio can be improved. In addition, the invention also relates to a block chain technology, and the target audio can be stored in a block chain.

The invention relates to a method for detecting the harmonic current signal strength of a traction converter. The method comprises the steps of acquiring an output current signal of a traction converter; amplifying and filtering the output current signal; performing analog-digital conversion on the output signal to obtain a digital signal; setting the center frequency, passband and cutoff frequency of a digital band-pass filter, and processing the digital signal using digital band-pass filter; and obtaining the RMS of the output signal of the digital band-pass filter by using a sliding windowcalculator, and then obtaining a signal strength value of the traction converter. The method for detecting the harmonic current signal intensity of the traction converter in the invention performs pure time domain signal processing on the signal, and the processing process is simpler. The characteristics of the digital band-pass filter in the filtering process are basically not affected by environmental factors. In addition, the sliding window calculator is used to process the data, the change of the input signal can be tracked in real time, and the defect of failing to respond well to an abrupt signal can be solved.

The present invention discloses a signal processing method and a data processing method and apparatus. A time-domain to frequency-domain signal processing method includes: pre-processing time-domain data; pre-rotating the pre-processed data by using a rotation factor a·WNn+0.5; performing a discrete Fourier transform (DFT) of N / 4 points on the pre-rotated data; and post-rotating the data transformed by the DFT by using a rotation factor b·WNk+0.5 to obtain frequency-domain data. A frequency-domain to time-domain signal processing method includes: twiddling frequency-domain data; pre-rotating the twiddled data by using a rotation factor c·WNk+0.5; performing a DFT of N / 4 points on the pre-rotated data; and post-rotating the data transformed by the DFT by using a rotation factor d·WNn+0.5; and post-processing the post-rotated data to obtain time-domain data. The present invention increases the efficiency of signal processing.

The invention discloses a method for estimating the laying depth of a vector hydrophone, and the method comprises the steps: receiving time domain signals of broadband sound pressure and three-component particle vibration velocity radiated by a sound source, and processing the time domain signals to obtain sound energy flows in x, y and z directions; estimating a sound source azimuth angle by using the sound energy flows in the x direction and the y direction and synthesizing a horizontal sound energy flow; estimating the sound source arrival angle according to the ratio of the sound energy flow in the z direction to the horizontal sound energy flow; calculating time delay template values of direct waves and seabed reflected waves corresponding to different vector hydrophone depths under the arrival angle according to the sound source arrival angle estimated value and the sound velocity profile; obtaining an arrival time delay estimation value of the direct wave and the seabed reflected wave; and calculating the difference value between the arrival time delay estimation value of the direct wave and the seabed reflection wave and the time delay template value, and taking the depth corresponding to the time delay template value with the minimum difference value as the laying depth estimation value of the vector hydrophone.

The invention discloses a time-domain signal processing method for differential resistivity logging through casing: acquiring transient electromagnetic induction receiving waveforms at four moments of forward conduction, forward turn-off, reverse conduction and reverse turn-off; Response difference waveforms 1, 2, and 3 are obtained by subtracting the received waveforms of electromagnetic induction at adjacent depth points; the response difference of adjacent depth points replaces the response difference at the collar to remove the influence of the collar; respectively select the response difference waveforms 1 and 2 at four times , 3, the maximum value is converted into the formation conductivity difference curve; the formation conductivity difference curve at any time in any response difference waveform is integrated to obtain the formation conductivity curve of the measured well section; the same The method is applied to other moments of the response difference waveform to generate the formation conductivity curve of the corresponding well section; the above method is applied to the other two response difference waveforms at four moments to generate the formation conductivity curve of the corresponding well section; The curves are weighted and added together, and the reciprocal is taken to obtain the formation resistivity curve.

Embodiments include digital signal processing units, a transmitting device for a wireless communication system and methods of processing a composite time domain signal having a plurality of parallel and independent signals that collectively form a parallel communication. It is proposed a new waveform configuration suitable for 5G and that is able to reduce out-of-band (OOB) emissions which are received on a first time domain signal associated to a first sub-band where the OOB emissions originate from an OFDM time domain signal associated with a second sub-band adjacent to the first sub-band. The proposed solution is partly based on filtered-OFDM with the exception that sub-band filtering is not performed on all the samples of the stream of OFDM symbols. Instead, filtering is performed only, for each OFDM time domain signal, where transition occurs between consecutive OFDM symbols.

The invention discloses a wind profile radar rainfall and non-rainfall adaptive detection system and method. The system comprises system control module, a signal processing module, a digital intermediate frequency receiver plate, an industrial control computer, a data terminal computer and a data processing module. The system control module controls the atmosphere wind field detection process. The digital intermediate frequency receiver plate receives a radio echo signal and obtains domain signals in digital processing. The signal processing module processed the domain signals into atmosphere wind field power spectrum signals. The data processing module processes and analyzes the atmosphere wind field power spectrum signals and automatically configures corresponding detection parameters. The established adaptive detection system automatically determines whether there is rainfall or not and configures corresponding detection parameters in the detection process through a wind profile radar, so that the adaptive detection of the atmosphere wind field in rainfall or non-rainfall weather is achieved, the atmosphere wind field information under different weather conditions can be accurately measured, and better application in meteorological research and weather forecast is achieved.

The invention discloses a computing device and an electronic device. The computing device includes several computing modules, each of which includes several neuron clusters, and the computing modules are configured as follows: weighted by a first weight matrix, the the input pulse train of the block is projected to the first neuron population through polysynaptic projections, wherein the polysynaptic projections have at least two different synaptic time constants and the two different synaptic time constants are both positive, Or at least two different synaptic transmission delays. In order to realize time-domain convolution in the spiking neural network with low hardware resource consumption, the present invention discloses the multi-synaptic projection technology with different synaptic time constants, and further proposes a method based on residual connection, jumping Waveform-aware spiking neural networks for time-domain signal processing characterized by connections etc. Through these technical means, the performance gap between the SNN and the ANN is bridged, and the SNN whose performance reaches or approaches that of the ANN is obtained.

Embodiments include digital signal processing units, a transmitting device for a wireless communication system and methods of processing a composite time domain signal having a plurality of parallel and independent signals that collectively form a parallel communication. It is proposed a new waveform configuration suitable for 5G and that is able to reduce out-of-band (OOB) emissions which are received on a first time domain signal associated to a first sub-band where the OOB emissions originate from an OFDM time domain signal associated with a second sub-band adjacent to the first sub-band. The proposed solution is partly based on filtered-OFDM with the exception that sub-band filtering is not performed on all the samples of the stream of OFDM symbols. Instead, filtering is performed only, for each OFDM time domain signal, where transition occurs between consecutive OFDM symbols.

A method is provided for processing a radio frequency (RF) signal output by a device under test (DUT), the RF signal having first comb lines in a predetermined first order. The method includes mixing and filtering the RF signal with a multi-tone local oscillator (LO) signal to provide an intermediate frequency (IF) signal having second comb lines corresponding to the first comb lines, where the mixing operation scrambles in frequency the first comb lines of the RF signal such that the second comb lines of the IF signal are in a second order different from the predetermined first order; digitizing the IF signal at a predetermined sampling rate; and descrambling the digitized IF signal with time domain signal processing such that the second comb lines of the digitized IF signal are arranged in the predetermined first order.

The invention relates to an underwater target gammatone discrete wavelet coefficient auditory feature extraction method. Noisy data measured actually are preprocessed at first on the basis of Fourier transform and logarithm compression and in incorporation with a gammatone auditory filter bank and discrete wavelet transform to enable target signals to be approximately stable in the short time; Fourier transform is conduced on the preprocessed data, time-domain signal processing is converted into frequency-domain signal processing, auditory filtering and logarithm compression are conducted on the preprocessed data through the gammatone auditory filter bank, discrete wavelet transform is conducted on the data on which logarithm compression is conducted at last, and the dimensionality of the data is reduced. The underwater target gammatone discrete wavelet coefficient auditory feature extraction method can extract effective auditory features of underwater target radiation noise, thereby improving the correct recognition rate of the underwater target.

The invention discloses a device for realizing long time domain signal processing. The device stores a Bragg acousto-optic relevant optical signal in an optical storage array and a storage medium through optical storage technology, and then reads the stored optical signal for signal processing. The technology aims to the technical field of the relevant operation of a long time domain signal. The device has the outstanding advantage that: the long time domain signal, particularly a signal with the time-bandwidth product more than 10 can be processed through the method.

A method for extracting auditory features of underwater target gammachirp cepstrum coefficients proposed by the present invention is based on Fourier transform and logarithmic compression, combined with gammachirp auditory filter banks, firstly preprocesses the measured noise data to make the target The signal is expressed as approximately stable in a short period of time, and then Fourier transform is performed on the preprocessed data, and the time-domain signal processing is converted into a frequency-domain signal for processing, and then it is auditory filtered through the gammachirp auditory filter bank and used Logarithmic compression, and finally perform discrete cosine transform on the logarithmically compressed data to reduce its dimensionality. This feature extraction method based on the gammachirp frequency auditory perception cepstral coefficient can extract effective auditory features of underwater target radiation noise, thereby improving the correct recognition rate of underwater targets.

Embodiments of the present invention provide a channel estimation method, device, and receiver. The channel estimation method is used for a receiving end based on a DFT-s-OFDM system, including: receiving the first time signal sent by the transmitting end of the DFT-s-OFDM system Domain signal, the first time domain signal is the transmission signal obtained by the sending end using a preset PTRS configuration method, the preset PTRS configuration method includes inserting PTRS before performing DFT on the PUSCH data; performing time domain signal on the first time domain signal processing to obtain a PTRS time-domain signal for channel estimation; perform channel estimation according to the PTRS time-domain signal, and obtain a channel response at a frequency domain position where the PTRS is located. Therefore, the present invention can directly estimate the frequency domain channel response of the time-frequency resource position where the PTRS signal is located in the DFT-s-OFDM system, and improves the channel estimation capability based on the DFT-s-OFDM system.