59 results about "Fft fast fourier transform" patented technology

The invention relates to the technical field of audio signal processing, and discloses a high-sampling-rate audio analysis optimization method and system, a storage medium and equipment, and the method comprises the steps: upgrading an FFTW (Fast Fourier Transform) library, and building an optimized memory management mechanism; carrying out adaptive framing processing on the input audio data, and optimizing the data access efficiency by adopting a multi-stage cache system; the calculation precision of the FFT fast Fourier transform is dynamically adjusted, and the calculation of the FFT fast Fourier transform is optimized by pre-calculating and caching an FFTW plan; performing clock synchronization optimization and jitter elimination on the COAX digital audio signal; establishing a multi-dimensional result cache matrix and an intelligent multiplexing decision tree, and reducing repeated operation through intelligent cache prediction and similarity calculation; system performance indexes are monitored in real time, adaptive parameter adjustment is realized based on an optimization objective function, audio quality and system stability are monitored in combination with subjective and objective evaluation mechanisms, repeated operation is remarkably reduced, and calculation resource allocation is optimized on the premise of ensuring sound quality.

The invention discloses a data management method and device, electronic equipment and a storage medium, and belongs to the technical field of electronic equipment. The method comprises the following steps: carrying out fast Fourier transform (FFT) calculation on first data stored in an annular buffer area of the scintillation sensor, and obtaining a first calculation duration for carrying out FFT calculation on the first data; predicting a second prediction duration of the next FFT calculation based on a first prediction duration of the previous FFT calculation and the first calculation duration; determining a target window value based on the second prediction duration and an FFT calculation reference duration; and according to the target window value, storing second data collected by the scintillation sensor into the annular buffer area.

The invention discloses an equipment fault diagnosis method based on a depth Brown distance and an attention mechanism, and the method comprises the steps: obtaining fault vibration signal data, and generating corresponding time-frequency image data through fast Fourier transform and spectrum feature calculation; taking the time-frequency image data as a query sample, and combining a preset support set to construct a small sample learning task; performing feature extraction based on a preset weighted multi-scale wide kernel feature dynamic extraction network to obtain a query sample feature map and a multi-class support sample feature map; and then performing fault diagnosis based on the trained fault diagnosis model to obtain a corresponding fault diagnosis result. Wherein the fault diagnosis model comprises a global measurement module based on an attention mechanism, a local measurement module based on a depth Brownian distance and a classifier. According to the method, adaptive multi-scale feature extraction is realized, fault diagnosis is performed from local and global dimensions, and the fault diagnosis precision and reliability in a small sample scene are remarkably improved.

The invention discloses a film thickness measurement method and system based on a line scanning hyperspectral camera, and relates to the technical field of hyperspectral imaging, and the method comprises the steps: obtaining a reflection or transmission spectrum image and a dark noise image, and carrying out the denoising processing; using a hyperspectral camera and an integrating sphere to carry out radiation correction on the reflected or transmitted spectral image; acquiring a film reflectivity or transmissivity spectrum according to the transmission spectrum without the film or the standard specular reflection spectrum; and determining the number of global interference periods according to a reflectivity or transmissivity curve, and calculating by using a fast Fourier transform method or a spectrum fitting method to obtain the film thickness. Image data with space and spectrum information is acquired through a hyperspectral camera, high-precision film thickness measurement under global imaging and dynamic scanning is realized through an algorithm combining fast Fourier transform and spectrum fitting, and meanwhile, the film thickness measurement precision is improved by adopting dark noise correction and integrating sphere radiation correction. The quantitative accuracy of incident light and sample reflection or transmission light is ensured, and the detection efficiency is greatly improved.

The invention discloses a heart rate detection method implemented by using a composite remote photoplethysmography (rPPG), comprising the following steps: continuously capturing an input frame, the input frame having a face image; calculating a plurality of feature points in the face image to obtain a skin color mean value and storing the skin color mean value in a first queue; executing a POS algorithm and a CHROM algorithm based on the skin color mean value of the plurality of input frames in the first queue to generate a first rPPG waveform signal and a second rPPG waveform signal respectively; performing reverse merging processing on the first rPPG waveform signal and the second rPPG waveform signal to generate a merged waveform signal; performing a fast Fourier transform process on the merged waveform signal to generate a merged spectrum; and performing spectrum analysis processing on the combined spectrum to extract heart rate output.

A uniform circular array (UCA) is assisted with an analog inverse fast Fourier Fast transform (IFFT) / fast Fourier transform (FFT) precoder to reduce computational complexity in one or more line-of-sight (LoS) multiple-input multiple-output (MIMO) networks. Each port of the UCA includes a steerable miniaturized array with beam steering capability. Analog beam steering is performed via one of the analog IFFT / FFT precoder or one of the steerable miniaturized arrays in a port of the UCA, for improving one or more properties of steering one or more beams toward one or more intended destinations in the one or more LoS MIMO networks.

Reconfigurable digital logic circuits and methods of operation can be used to accelerate computation of Fast Fourier Transforms (FFT) and discrete Fourier transforms (DFT) for a range of sizes. In some embodiments, the same circuit can be reconfigurable to support FFT of any size 2k (for positive integer k) and DFT for of any size 2a*3b*5c for non-negative integers a, b, c.

The application discloses a kind of two-dimensional real-time back-projection perception imaging method, device, equipment and medium based on multi-antenna system, wherein, imaging method includes the following steps: S1, echo signal is carried out hilbert transform, frequency transfer and fast fourier transform, and echo signal spectrum is output;S2, echo signal and echo signal are carried out matched filtering, and time domain pulse compression result is output;S3, according to the imaging area and grid size calculation imaging area coordinate, according to pulse compression result, the corresponding pixel signal intensity of image is calculated by two-dimensional interpolation;Then the imaging area coordinate is used to calculate phase compensation factor, and the interpolation result is phase compensated, and finally two-dimensional range image is output and pre-stored;S4, to the multi-channel two-dimensional range image is windowed and superimposed, and two-dimensional SAR image is output in real time.The application is based on SAR simulation imaging method, can process multi-antenna echo signal, can improve angle resolution and realize real-time perception imaging of indoor environment.

The present invention discloses an automated classification method for regression test error simulation waveforms based on a Mamba neural network architecture, belonging to the field of integrated circuits. The method comprises parsing a simulation waveform file obtained from a regression test, converting a key signal waveform into a discrete sequence of integer waveforms; normalizing the numerical range of the waveform sequence to the 0-1 interval, intercepting a fixed length and inputting it into a Mamba neural network model, with the network outputting two parameters: block size and block starting position; dividing the waveform using the two characteristic parameters output by the network, calculating the thickness, degree of fluctuation, and mean characteristics of each waveform block, and calculating the overall characteristics; performing a fast Fourier transform on the waveform using integer multiples of the waveform block size as a window, and calculating frequency domain features; and merging the extracted features into a multidimensional feature vector and inputting it into a support vector machine to output a final classification result. The present invention can effectively improve the accuracy of diagnosing the cause of regression test failure, replace the manual triage process, and improve verification efficiency.

The invention discloses a speech recognition method based on an STO array and a dynamic time planning algorithm. The method includes processing speech signals using an STO array and identifying them using an improved dynamic time planning algorithm. The STO can generate a stable microwave signal in the absence of an external magnetic field. The method first pre-processes the signal in the time domain, then performs a fast Fourier transform, and then converts the power spectrum into a current signal by calculation and passes it into the STO array, obtaining the output frequency corresponding to each current segment as a feature vector. Finally, the feature vector is processed using an improved dynamic time planning algorithm to achieve recognition. The method utilizes an array constructed of nano-scale STO devices, combines the characteristics of STO such as its ability to flip without a magnetic field and high frequency adjustability, and improves the algorithm to limit the distance and increase the training library, thereby realizing a speech recognition hardware improvement system, which is expected to achieve highly integrated and high-recognition speech recognition.

A method, system, and apparatus for a wireless receiver with intermediate frequency (IF) detection and local oscillator (LO) frequency correction is disclosed. According to one aspect, the wireless receiver is configured to include a LO configured to generate a local oscillator signal, the LO not being phase-locked. The wireless receiver includes a mixer configured to mix the LO signal with an amplitude shift keying (ASK) modulated signal to produce an intermediate frequency (IF) signal. The wireless receiver also includes a tuning circuit configured to estimate a frequency of the IF signal and tune the LO according to the estimated intermediate frequency, and tune the LO to compensate for IF frequency drift. The IF frequency estimation is based on a correlation of the signal in a plurality of frequency bins of a fast Fourier transform (FFT) of the IF signal.

Technologies for compilers that implement non-power of two Fast Fourier Transform (FFT) algorithms are described. The non-power of two FFT algorithm uses a recursive function to generate a hardware design of a set of compute blocks of a fixed-point digital signal processor (DSP) and routing data between the compute blocks. The compiler receives input specifying a sequence of indexes and a bit width of the fixed-point DSP and performs a process. The process splits the sequence using a recursive loop, determines a number of multiplications in the hardware design, and generates a trace graph of the non-power of two FFT algorithm. The process is entered via the recursive function and exists when the recursive loop decrements to a specified value corresponding to a Radix-3 or Radix-2. The compiler outputs data, including the hardware design, the number of multiplications in the hardware design, and the trace graph.

The present invention discloses a low-voltage intelligent broadband harmonic detection method and a detection device, belonging to the technical field of harmonic detection in power systems, including: denoising an input signal to obtain an initial signal; performing discrete wavelet transform based on the obtained number of transformation times to separate the initial signal into a low-frequency signal and a high-frequency signal; weighting the low-frequency signal based on a Hanning window to obtain a weighted signal, performing fast Fourier transform on the weighted signal to obtain a first harmonic spectrum, and performing feature extraction and spectrum correction on the first harmonic spectrum to obtain a first detection result; performing frequency reduction processing on the high-frequency signal through an orthogonal digital mixing function to obtain a frequency-reduced signal, performing band-selective fast Fourier transform on the frequency-reduced signal to obtain a second harmonic spectrum, and performing feature extraction on the second harmonic spectrum to obtain a second detection result. It overcomes the technical problem in the prior art that it is difficult to improve the real-time performance while improving the detection accuracy, and significantly improves the accuracy and real-time performance of harmonic detection.

The present application discloses a method and an electronic device for reducing echo residue. The method for reducing echo residue can be applied to the electronic device, and comprises: performing echo cancellation on a voice input signal according to an echo reference signal to obtain an echo cancellation signal; converting the echo reference signal into a reference spectrum signal of each frame by fast Fourier transform; converting the echo cancellation signal into a voice spectrum signal of each frame by fast Fourier transform; obtaining an a priori signal-to-noise ratio of a current frame by using the reference spectrum signal of the current frame and the voice spectrum signal of the current frame according to an additive noise principle; filtering the voice spectrum signal of the current frame by a Wiener filter coefficient of the current frame determined by the a priori signal-to-noise ratio of the current frame to obtain a target spectrum signal of each frame; and converting the target spectrum signal of each frame by inverse fast Fourier transform to obtain a target voice signal. Therefore, the method for reducing echo residue can accurately filter out residual echo.

The present invention relates to a vibration detection method for a circuit breaker mechanical fault, comprising the following steps: 1. magnetically adsorbing or adhering a vibration sensor to the surface of a housing at an operating mechanism of a circuit breaker under test; 2. closing the circuit breaker to excite vibration, whereupon the vibration sensor collects a vibration signal, transmits the signal to a vibration signal analysis and processing instrument, and records the vibration signal; 3. the vibration signal analysis and processing instrument obtains the magnitude of the vibration amplitude, performs a fast Fourier transform on the vibration signal within a range of 0-8000 Hz, and performs a three-layer wavelet packet decomposition on the vibration signal using a packet processing unit of an industrial computer; and 4. calculating the maximum amplitude a of the vibration, and obtaining the energy value e of each frequency band. i 5. The original data of the load vibration test of the circuit breaker during commissioning are also subjected to fast Fourier transform and three-layer wavelet packet decomposition in the range of 0-8000Hz to calculate the maximum amplitude A of the vibration and the energy E of each frequency band. i ; 6. Determine whether there is a spring fatigue loosening fault; 7. Determine whether there is a transmission mechanism jamming fault; 8. Display the fault condition.

A system for determining a trigger amplitude indicating an early sign of material fracture in a test sample includes a microphone that converts acoustic emissions emitted by the test sample into electrical signals. A load is applied to the test sample, and acoustic emissions are emitted when the load causes deformation of the test sample prior to material fracture. A control module communicates electrically with the microphone and executes instructions to monitor and filter the electrical signals generated by the microphone. The control module converts the electrical signals generated by the microphone into individual frequency components based on a Fast Fourier Transform (FFT). Each frequency component includes a peak intensity. The control module determines the trigger amplitude based on the peak intensities of the individual frequency components obtained from the FFT.

This invention relates to a method and apparatus for resolving velocity ambiguity based on constant frequency assistance. The method includes the following steps: a radar sequentially transmits a constant frequency band signal and a linear continuously modulated pulse train, and acquires the radar echo signal; both the constant frequency band echo signal and the sawtooth band echo signal are mixed to obtain a constant frequency band intermediate frequency signal and a sawtooth band intermediate frequency signal; the constant frequency band intermediate frequency signal is processed by a fast Fourier transform to obtain a target true velocity estimate; the sawtooth band intermediate frequency signal is sequentially processed by a two-dimensional fast Fourier transform, a two-dimensional constant false alarm rate (CFAR) processing, and a centroid condensation processing to obtain a target range velocity estimate; based on a velocity matching method using a Fourier rotation factor, the target true velocity estimate is matched with the target range velocity estimate to obtain the true velocity of all targets. This method not only resolves velocity ambiguity but also improves velocity accuracy, offering advantages such as high velocity measurement accuracy, high real-time performance, and simplicity.

The present application relates to the field of bark stopper, and provides a bark stopper control device with noise reduction and a method thereof, which comprises a fixing device wearable on the neck of a pet dog, a shell, a bark stopper device, a main microphone sound collection module, a vice microphone sound collection module, a differential amplifier module and a microprocessor. The main microphone sound collection module and the vice microphone sound collection module respectively collect barking sounds, amplify the barking sounds and send the amplified barking sounds to the differential amplifier module to filter environmental noise. The differential amplifier module adopts inverse sound waves to offset and filter the environmental noise, and outputs a noise-free barking sound signal to the microprocessor. The microprocessor performs fast Fourier transform to calculate frequency domain characteristics and determine whether the frequency domain characteristics conform to the barking frequency characteristics of the pet dog stored in the microprocessor. If the pet dog barks, the microprocessor controls the bark stopper device to stimulate the pet to bark. The present application solves the problem of high false triggering rate of the existing bark stopper.

In at least one embodiment, a well inspection method (600) and system (500) is disclosed. The method (600) includes transmitting (602) an acoustic signal from a well inspection tool into a casing structure, receiving (604) return signals from the casing structure to the well inspection tool, performing (606), using at least one processor associated with the well inspection tool, a Fast Fourier Transform (FFT) on a plurality of frequencies of the return signals to generate spectrogram data, determining (610) entropy spectra from the spectrogram data, and determining (612) casing loadings associated with the casing structure based at least in part on the entropy spectra.

The invention relates to a computer-implemented method for evaluating and optionally monitoring or controlling a surface texture, comprising the steps of providing image data of a surface to a processing device via an input channel, extracting a plurality of parallel lines from the processed image data by using a pattern recognition algorithm, stitching at least two extracted parallel lines, and calculating a wavelength spectrum of each formed stitched line by means of a fast Fourier transform, and deriving at least one texture parameter of the surface from the provided image data by providing at least one texture parameter via an output channel. Furthermore, the invention relates to a system comprising an input channel connected to a processing device, a processing device configured to derive and optionally monitor or control at least one texture parameter of a surface, an output device, and optionally at least one surface preparation device. Finally, the invention relates to a computer program product for evaluating and optionally monitoring or controlling a surface texture, comprising a data carrier storing a program code to be executed by a processor.

This invention discloses a mixed hepatocyte terahertz quantitative detection system, electronic device, and medium, comprising: a spectral preprocessing module for acquiring a mixed hepatocyte time-domain spectrum and converting it into a mixed hepatocyte terahertz frequency-domain spectrum using a fast Fourier transform; calculating the refractive index and absorption coefficient to obtain frequency-domain signals of the refractive index and absorption coefficient, and processing them using Gram angle sum field and Gram angle difference field to obtain Gram angle sum field map and Gram angle difference field map; an image feature extraction module for extracting gradient features from the Gram angle sum field map and Gram angle difference field map using gradient histograms; extracting grayscale features from the Gram angle sum field map and Gram angle difference field map using grayscale histograms; fusing the gradient features and grayscale features to obtain image features; and a hepatocyte cancer cell content quantitative detection module for inputting the image features into a pre-trained hepatocyte cancer cell content quantitative detection model to obtain the proportion of hepatocyte cancer cells.

A receiver according to the present disclosure includes: a fast fourier transform (FFT) processor configured to receive a signal including a plurality of first symbols, and configured to output a plurality of second symbols corresponding to a result of performing a fast fourier transform operation on the signal; a FFT reorder buffer memory configured to store a plurality of third symbols in which the plurality of second symbols are reordered according to a natural order; and a FFT buffer controller configured to control the FFT reorder buffer memory to read the plurality of third symbols according to a circular shift order in which bits of addresses of the FFT reorder buffer memory are circularly shifted.

A signal processing device for an inverse sparse fast Fourier transform performing permutation and filtering is disclosed. The signal processing device acquires a signal and converts the acquired signal into a time domain. The signal processing device comprises an input counter configured to give an index to the acquired signal; an address ROM configured to store signal information based on a predetermined first permutation parameter and a predetermined second permutation parameter used for a data order change; a comparator configured to check whether the index given to the acquired signal matches the signal information stored in the address ROM; an address counter configured to transmit an output signal to the address ROM when the comparator acquires a matching signal, and count a number of transmissions; a window memory configured to acquire different signals from the address ROM and output different window coefficients replaced in a minimal signed digit (MSD) representation representing a number in limited nonzero digits; and two multipliers configured to multiply the acquired signals by the window coefficients and output the signals.

The application provides a Fourier transform bit-reversal permutation sequence generating method and device, which comprises the following steps: determining an input order N of an input sequence of a current Fourier transform, and obtaining a number of the input sequence of the input order N to be inversed according to the input order N and a database, wherein the database stores sequence number orders of bit-reversal permutation sequences of reference orders; and processing the input sequence according to the number of the input order to be inversed to obtain an N-order bit-reversal permutation sequence. The application improves the generating rate of the bit-reversal permutation sequence by using the bit-reversal permutation of the reference order, and further optimizes the performance of the fast Fourier transform.

The invention discloses a track multivariable measurement and state evaluation method based on fusion physical modeling and data driving, and belongs to the technical field of railway safety monitoring. The method comprises the following steps: firstly, constructing a mechanical and dynamic model, and optimizing a model structure by utilizing symmetry constraint and boundary conditions; secondly, identifying and updating model parameters by utilizing a reverse modeling technology in combination with historical and real-time measurement data; in the feature extraction stage, fast Fourier transform is adopted to extract time features sensitive to dynamic changes, and deep fusion characterization of multivariable signals of the system is achieved by combining the learning speed of the long and short-term memory network or space features with unchanged scales. And finally, comprehensive evaluation and anomaly recognition of the structure or equipment state are realized by fusing physical mechanism constraints and data-driven learning results. The method has the advantages of being high in modeling precision, high in universality and good in real-time performance, is suitable for the field of multivariable measurement and state monitoring, achieves effective monitoring and evaluation of the track state, and improves the application effect of intelligent railway infrastructures.

The present application relates to closed-loop real-time SSVEP-based head-up display using deep learning to control features in a vehicle. A vehicle system includes a controller programmed to display a plurality of icons on a HUD of the vehicle, receive EEG data from a driver of the vehicle, perform a fast Fourier transform of the EEG data to obtain an EEG spectrum, input the EEG spectrum into a trained machine learning model, determine which icon of the plurality of icons the driver is viewing based on an output of the trained machine learning model, and perform one or more vehicle operations based on the output of the trained machine learning model.

A method of equalizing a plurality of single ended channels in a data communication network is disclosed. The method includes receiving real symmetrical input values over each of the plurality of single ended channels at an input of a frequency domain equalizer. Further, the method includes processing the received real symmetrical input values using a plurality of Fast Fourier Transform (FFT) implementations of the frequency domain equalizer. The method further includes processing the outputs of the plurality of FFT implementations using a matrix inversion implementation of the frequency domain equalizer. Furthermore, the method includes processing an output of the matrix inversion implementation using a plurality of Inverse FFT implementations, where each of the plurality of single ended channels is assigned to one of the plurality of Inverse FFT implementations.

Exemplary systems, methods, and computer-accessible medium are provided that can optimize a design of an object. Thus, exemplary systems, methods, and computer-accessible medium can be provided that can apply a fast Fourier transform and / or non-uniform fast Fourier transform to generate continuous and discrete point structures with one or more arbitrary statistical correlations.

A device for detecting and quantifying lung function includes a piezoelectric sensor configured for attachment to a mammalian chest wall and to feed signals to an ADC providing digitized signals to a processor. The processor firmware extracts inspiration and expiration times from the digitized signals and generates an I / E ratio from them. The processor has firmware to detect wheezing sounds in the signals. The device has an analog event detector configured to wake-up the processor upon detection of candidate wheeze sounds in the signals. In embodiments, the analog event detector includes bandpass filters coupled to a modeling circuit feeding a correlation circuit, the filters having bandpass adjusted by feedback from a circuit within the analog event detector. In an embodiment, the device uses an FFT with a gated recurrent unit (GRU) with partial reset (GRUPR) neural network to detect wheezes.

The present invention relates to a time-varying parameter video SAR imaging method for large squint, including: Step S1: Transmit signals using a time-varying parameter system, and perform dechirping and residual video phase removal processing on the echo signals of the transmitted signals; Step S2: Calculate the azimuth angle estimation values corresponding to each frame in the time-varying parameter video SAR image and the azimuth angle estimation value corresponding to the large frame; Step S3: Calculate the accurate azimuth angle values corresponding to each frame within the large frame and the accurate azimuth angle value corresponding to the large frame according to the azimuth resolution and the azimuth angle estimation value corresponding to the large frame; Step S4: Divide the echo signals processed in Step S1 according to the accurate azimuth angle value corresponding to the large frame to obtain large frames, and perform range interpolation and azimuth interpolation on the data of each large frame in sequence; Step S5: Perform data extraction and two-dimensional fast Fourier transform on the data of each frame in the large frames after interpolation processing in sequence; Step S6: Perform geometric distortion correction and coordinate system rotation correction on the imaging results of Step S5.