154 results about "Fft fast fourier transform" patented technology

Provided is a rolling bearing fault diagnosis method based on FFT coding and L-CNN, including: obtaining original bearing fault vibration data, extracting intrinsic mode components of different frequency bands in the original bearing fault vibration data, calculating a permutation entropy value corresponding to each of the intrinsic mode components, and performing wavelet threshold denoising according to the permutation entropy value to obtain a denoised reconstructed time domain signal; performing fast Fourier transform to the denoised reconstructed time domain signal to obtain a frequency domain signal and a phase angle corresponding to the time domain signal, reconstructing the frequency domain signal according to a preset rule, retaining frequency domain data of features of the phase angle, and drawing FFT-x heat maps of different fault type data according to an amplitude range; and constructing an model L-CNN, and inputting coded data into the L-CNN model, and obtaining fault diagnosis results.

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.

Multiply-accumulate processors within a tensor processing unit simultaneously execute, in each of a sequence of multiply-accumulate cycles, respective complex-data multiply operations using a shared complex data operand and respective fast-Fourier-transform parameters, each of the multiply-accumulate processors applying a new complex input data operand and respective fast-Fourier-transform parameter in each successive multiply-accumulate cycle to accumulate, as a component of a resultant fast Fourier transform, a respective sum of complex multiplication products.

Technologies directed to respiration monitoring based on noise channel state information (CSI) data are described. A method includes receiving CSI data representing channel properties of a wireless channel used by a first wireless device and a second wireless device located in a geographical region. The method generates a set of CSI samples by sampling the CSI data and removes one or more outlier CSI samples using a sparse outlier process, and removes a cluster of outlier samples using a cluster outlier process. The method determines Fast Fourier Transform (FFT) data for each channel subcarrier index and a signal-to-noise ratio (SNR) value for each channel subcarrier index, and identifies a first number of channel subcarrier indexes having highest SNR values to obtain a subset of FFT data, which represents a breathing spectrum. The method determines a respiratory rate of a user in the geographical region from the subset of the FFT data.

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.

A multi-mode surface-wave free-field inversion method based on dispersion properties of layered media addresses the inaccuracy in existing methods that ignore higher modes. A novel approach for characterizing the participation quantity of each mode is proposed based on an energy flux density, which is applied to calculate a modal participation factor through dispersion curves and the frequency-domain dynamic stiffness matrix. Next, the ground surface-wave components with dispersion properties are transferred from the time domain to the frequency domain and decomposed into harmonic components composed of individual frequencies by the Fast Fourier Transform technology. These harmonic components continue to be decoupled as multiple modes by the modal participation factors, with each single-mode component being inverted to construct single-mode surface-wave free fields. Finally, all single-mode surface-wave free fields are superimposed following the mode superposition principle to form the multi-mode surface-wave free fields.

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 power emergency unmanned aerial vehicle power transmission line defect detection method, which comprises the following steps: receiving a power transmission line image acquired by a power emergency unmanned aerial vehicle, and preprocessing the image to accurately identify and distinguish defects and backgrounds; carrying out feature extraction on the image, and obtaining statistical property features through texture analysis, a gray-level co-occurrence matrix, a gray-level difference method, discrete wavelet transform and fast Fourier transform methods; fusing and selecting the extracted features to form an optimized feature set; using the feature set to train a super-pixel segmentation model based on deep learning for power transmission line defect detection; and adopting an average threshold method to carry out confidence analysis on the deep learning model after super-pixel segmentation. Through multi-domain feature extraction optimization, high-precision defect detection and robust confidence analysis, the accuracy and efficiency of power transmission line defect detection are significantly improved.

The invention relates to a vibration signal detection system for motor state diagnosis and a method thereof, the system comprises a piezoelectric acceleration sensor, a charge transfer module, a range selection module, an amplification module, an oscilloscope acquisition module and a data analysis module which are connected in sequence, and the piezoelectric acceleration sensor is used for acquiring charges generated by vibration; the charge transfer module is used for determining charge change in the vibration process; the range selection module is used for adjusting the gain of the amplification module; the amplification module is used for amplifying the charge change signal; the oscilloscope acquisition module is used for acquiring the amplified charge change signal; and the data analysis module performs fast Fourier transform and frequency sweep sampling calculation processing on the signals acquired by the oscilloscope acquisition module to obtain a vibration frequency value. Compared with the prior art, the method detects the dynamic process of vibration, is rich in perceivable characteristic parameters, effectively improves the measurement precision of motor vibration signals, and is suitable for motor state diagnosis application based on technologies such as deep learning.

A system includes a processor and a non-transitory computer-readable medium storing machine instructions that cause the processor to perform a first fast Fourier transform (FFT) on received radar data to obtain a range-antenna data array and to perform a second FFT on the range-antenna data array to obtain a range-Doppler-antenna data cube. The processor performs peak detection on the range-Doppler-antenna data cube based on object information to obtain a subset that includes confirmed peaks and candidate peaks. The processor performs angle of arrival calculations for the subset of the range-Doppler-antenna data cube, and filters candidate peaks in the subset to obtain a point cloud representative of an environment. In some implementations, the confirmed peaks are detected based on a default threshold value, the candidate peaks are detected based on at least one adapted threshold value, and the at least one adapted threshold value is determined based on the object information.

Provided are a method for a first device to perform wireless communication and a device supporting same. The first device can: transmit a first sensing signal block including M samples; receive a second sensing signal block that is a reflection of the first sensing signal from a second device; convert the second sensing signal block into a third sensing signal block on the basis of the delay spread; acquire a fourth sensing signal block by copying the third sensing signal block N times; and perform an N*M-point fast Fourier transform (FFT) on the fourth sensing signal block.

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.

A device for detecting and analyzing vital fields includes: a dielectric barrier discharge array fabricated on a thin substrate with low dielectric loss; an air permeable sheet for electrical insulation from the skin; a transformer for generating sufficient AC voltage to cause air breakdown in the array; a signal transformer and bypass capacitor for isolating the radio frequency current from the plasma discharge; circuitry for amplification and narrow-band spectrum analysis of the plasma discharge current. The amplified signal from the plasma discharge current is gated to include only signal from the part of the drive waveform where plasma discharge predominantly occurs. Frequency converters reduce the complexity of narrow-band spectrum analysis; spectrum analysis is done by Fast Fourier Transform analysis of the frequency converter outputs. The different FFT results are compared and analyzed to aid the user with the correct array placement on the body, and the detection of medical conditions.

Provided are a jamming signal generation method and system. The method includes receiving a synthetic aperture radar (SAR) transmission signal by an SAR, determining a first form and position of a noise patch in a predefined coordinate system, transforming the predefined coordinate system into an SAR image formation plane (IFP) coordinate system, based on a coordinate system transformation function, determining a second form and position transformed from the first form and position of the noise patch in an SAR image using the SAR IFP coordinate system, generating a first reflectivity map model, based on the second form and position of the noise patch, generating a second reflectivity map model by performing two-dimensional fast Fourier transformation on the first reflectivity map model, and generating an SAR jamming signal based on a convolutional product of the second reflectivity map model and a reference signal.

The present invention relates to a method for determining an inharmonic interference frequency of an asynchronous machine connected to a power supply network. In this process, (210) a frequency band above a network frequency f is selected. Netz of the three-phase network in which the occurrence of the inharmonic disturbance frequency is expected to occur. Furthermore, (220) N samples of a current flowing between the asynchronous machine and the supply network are recorded over several periods of the network frequency at a data rate f. s A first Fast Fourier Transform Y1 is generated and a first Fast Fourier Transform is performed with N1 samples (230), where N1 < N. A second Fast Fourier Transform Y2 is also performed with N1 samples (240), where the first sample used for the second Fast Fourier Transform is a later sample than the first sample used for the second Fast Fourier Transform. The interference frequency f is calculated (250) as follows: f = fs | arg ( Y 2 ) − arg ( Y 1 ) | 2 π

The invention discloses a generator stator winding dynamic turn-to-turn short circuit fault detection method and device, and relates to the technical field of generator state monitoring and fault diagnosis, and the method comprises the steps: measuring a generator rotor vibration signal in real time; transforming the vibration signal from a time domain signal to a frequency domain signal by using fast Fourier transform; and comparing the collected time domain signal and the converted frequency domain signal with each component of the frequency spectrum of the vibration signal under the normal condition, and judging whether the generator has a winding dynamic turn-to-turn short circuit fault or not. Whether the dynamic turn-to-turn short circuit fault of the stator winding occurs in the generator is identified by detecting the rotor vibration of the generator. The method is simple and easy to implement, overcomes the defects of winding dynamic turn-to-turn short circuit fault detection at present, is obvious in detection characteristic and good in effect, and provides reference for detection and diagnosis of generator stator winding dynamic turn-to-turn short circuit faults.

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.

In certain embodiments, a surgical handpiece system includes a phacoemulsification tip, a fluid management system, an ultrasonic drive system, and a controller. The phacoemulsification tip is attached to a shaft. The fluid management system is configured to manage inflow and outflow of fluid from an ocular surgical site. The ultrasonic drive system is configured to generate torsional and longitudinal vibrations in the phacoemulsification tip. The controller is configured to analyze applied voltage and current to the ultrasonic drive system using Fast Fourier Transforms (FFTs), and tune applied frequencies of the torsional and longitudinal vibrations according to at least one resonant frequency.

In one aspect, an apparatus includes: a fast Fourier transform (FFT) engine to receive and convert a plurality of orthogonal frequency division multiplexing (OFDM) samples into a plurality of frequency carriers; a detector coupled to the FFT engine to determine a channel estimate for a first frequency carrier using a first channel estimate for the first frequency carrier and a plurality of other channel estimates, each of the plurality of other channel estimates for one of a plurality of neighboring frequency carriers within an evaluation window, and determine a log likelihood ratio (LLR) for the first frequency carrier using the channel estimate for the first frequency carrier; and a decoder coupled to the detector to decode a first OFDM symbol comprising the first frequency carrier using the LLR for the first frequency carrier.

Aspects and implementations disclosed are directed to systems and techniques protecting cryptographic operations that involve computing a discrete transform (DT) of a polynomial by randomizing basis vectors of a finite field, identifying a first auxiliary polynomial and a second auxiliary polynomial, computing the DT of the polynomial using the randomized basis vectors, the DT of the first auxiliary polynomial, and the DT of the second auxiliary polynomial, and computing a plaintext output corresponding to the ciphertext input using the DT of the polynomial. Further protection techniques include masking the polynomial and computing the DT of the polynomial using the DT of the masked polynomial.

The invention relates to the technical field of gas detection, and discloses a gas detection method and device for an infrared gas analyzer, and the method comprises the steps: obtaining the light cutting frequency of a light cutting device, capturing a photoelectric signal according to the light cutting frequency, determining a square wave signal, and if the square wave signal triggers an interrupt signal, judging a sampling mark of the infrared gas analyzer, if the sampling mark is true, a capacitance detector is called in a preset sampling period to convert the light quantity difference between the measuring gas chamber and the reference gas chamber into an electric signal; the sampling mark is changed to be false, the interrupt signal is eliminated, the electric signal is subjected to fast Fourier transform algorithm calculation to obtain a target signal amplitude value, the target gas concentration of the detected gas is obtained through the target signal amplitude value and a preset corresponding relation, and the preset corresponding relation represents the corresponding relation between the signal amplitude value and the gas concentration; the gas detection method for the infrared gas analyzer, which is more practical and more accurate, is provided by the method.

The invention discloses a two-dimensional real-time back projection sensing imaging method, device, equipment and medium based on a multi-antenna system, and the imaging method comprises the following steps: S1, carrying out Hilbert transform, frequency shift and fast Fourier transform on an echo signal, and outputting an echo signal frequency spectrum; s2, performing matched filtering on the sending signal and the echo signal, and outputting a time domain pulse compression result; s3, calculating the coordinates of the imaging area according to the imaging area and the grid size, and calculating the pixel signal intensity corresponding to the image through two-dimensional interpolation according to the pulse compression result; calculating a phase compensation factor by using the coordinates of the imaging area, performing phase compensation on an interpolation result, and finally outputting and pre-storing a two-dimensional range profile; and S4, windowing and superposing the multi-channel two-dimensional range profile, and outputting a two-dimensional SAR image in real time. Based on the SAR simulation imaging method, multi-antenna echo signals can be processed, the angle resolution can be improved, and real-time sensing imaging of the indoor environment can be achieved.

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.

Described herein is a system and method for calculating variable refresh rate (VRR) flicker of a display used for information handling systems. VRR display data is provided to the display which generates a raw optical waveform. The raw optical waveform is captured by an optical sensor. The captured raw optical waveform is weighted using an inverse Fast Fourier Transform from a Temporal Contrast Sensitivity Function (TCSF). Calculating the flicker value of the weighted optical waveform over a defined moving window is performed. The flicker average and flicker maximum of the flicker value is used to determine a VRR flicker value.

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.

Reducing noise and dose (radiation or contrast) for perfusion imaging in Computed Tomography Perfusion (CTP), Positron Emission Tomography (PET), Single Photon Emission Computed Tomography (SPECT), and Magnetic Resonance Imaging (MRI) medical scanning devices by using a k-space based method. The time sequence of images from the scanner data set is converted as necessary, such as using a 2D Fast Fourier Transform (FFT), into a k-space having multiple timeframes. View-shared averaging is performed to reduce noise and preserve spatial and temporal resolutions of CTP, PET, SPECT and MRI data by progressively increasing the number of time frames for view-shared averaging for more distant regions of “k-space”, before converting the data, such as through a 2D FFT into a time sequence of noise reduced images.