40 results about "Fft fast fourier transform" patented technology

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.

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 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.

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.

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.

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 method, system and sensor apparatus for estimating RPM of rotating machinery, can involve acquiring vibration data from an accelerometer sensor mounted on the rotating machinery and detecting vibration signals from the acquired vibration data. A Fast Fourier Transform (FFT) can be performed on the detected vibration signals for conversion of the detected vibration signals from a time domain to a frequency domain. An RPM of the rotating machinery can be estimated from the frequency domain, and fault frequences can be calculated using the estimated RPM and a bearing configuration provided by a user. A health diagnosis of the rotating machinery can be based on the calculated fault frequencies and an analysis of the detected vibration signals. In an embodiment, accelerometer sensor can be implemented as a MEMS capacitive accelerometer sensor.

This invention relates to a method for estimating the state of health (SOH) of lithium batteries under dynamic operating conditions based on variational mode decomposition (VMD). The method involves conducting lithium battery aging tests, performing dynamic operating condition cycles and standard operating condition discharge cycles on a reference lithium battery, and collecting time-series data on voltage, current, operating time, and temperature. The SOH sequence data and first-order difference SOH sequence data of the reference lithium battery are calculated using the ampere-hour integral method. Variational mode decomposition is then performed on the voltage, current, and temperature time-series data during the dynamic cycle operation. Furthermore, a fast Fourier transform (FFT) is applied to the decomposition results to extract health features from the frequency domain data. Finally, a long short-term memory (LSM) neural network is constructed and trained to achieve the estimation of the lithium battery's SOH under dynamic operating conditions. This method is more closely aligned with the actual operating conditions of lithium batteries and achieves accurate lithium battery SOH estimation.

The present disclosure relates to compensating for temperature variation of a mixer. Embodiments herein may include performing a single-point Fast Fourier Transform (FFT) (or complex downconversion with DC average) for a number of samples to obtain a transform for each of the number of samples, phase aligning a set of phases associated with each transform, and averaging each transform to generate an analog-to-digital converter (ADC) power value. Further, the disclosed embodiments may include generating a compensation value based on the analog-to-digital converter power value and applying the compensation value to the calibration circuit of the mixer to compensate for a second-order intermodulation product.

The application provides a power device damage evaluation method based on an electromagnetic acoustic emission signal attenuation coefficient spectrum, which comprises the following steps: recording electromagnetic acoustic emission signals sampled at first and second monitoring points; finding minimum values of each electromagnetic acoustic emission signal, dividing the corresponding electromagnetic acoustic emission signal by taking adjacent minimum values as time windows, and performing fast Fourier transform on the windowed and divided signals to obtain an amplitude-frequency curve of each electromagnetic acoustic emission signal; matching the amplitude-frequency curve according to signal theoretical propagation time, respectively calculating attenuation coefficients of the matched amplitude-frequency curves according to time window sequences, and obtaining an attenuation coefficient time-varying curve; calculating an average value of the attenuation coefficient time-varying curve to obtain an attenuation coefficient spectrum of a single measurement, and calculating a center frequency of the attenuation coefficient spectrum; repeating the above process, and if the center frequency deviates by more than a threshold value after each repetition, it is determined that the power device is damaged. The application realizes online monitoring and evaluation of the health state of the power device by using the above scheme.

A failure sign determining device includes an acquirer to acquire pieces of sensor data based on respective values measured by multiple sensors, an FFT processor to execute fast Fourier transform on each of the pieces of sensor data and thereby generate a piece of frequency spectrum data, and a determiner to determine the existence of a failure sign on the basis of comparison between the piece of frequency spectrum data and a spectrum range defined for the sensor. The determiner, only when determining that a failure sign exists, transmits at least either of the piece of frequency spectrum data and the piece of sensor data to an analysis apparatus.

The invention belongs to the related technical field of federal recommendation, and particularly relates to a federal recommendation method based on knowledge purification under the guidance of data enhancement, which comprises the following steps: each client performs local data enhancement by using a sequence cutting strategy, converts user interaction data from a time domain to a frequency domain through fast fourier transform, and sends the user interaction data to a database; the frequency domain representation of each commodity and the frequency domain mask, used for low-pass filtering, of the client side are subjected to point multiplication, the representation obtained after point multiplication is input into an adaptive filter layer, different frequency component feature values in the representation are modulated, and it is ensured that higher-quality knowledge is obtained through model training. In the aspect of client parameter aggregation, a supernetwork-driven personalized aggregation strategy is introduced, the strategy dynamically generates aggregation weights specific to the clients under the condition of frequency domain representation and cut-off frequency distribution between different clients, and propagation of noisy knowledge between the clients in the global aggregation process is relieved. According to the method, the problem of serious sparsity of federal learning scene data is effectively relieved.

This invention proposes a tremor symptom prediction system and method. The prediction system includes: a light-emitting unit configured to emit a detection light to illuminate a skin area of ​​a subject, wherein the detection light is partially reflected by the skin area to form reflected light, and / or partially transmitted by the skin area to form transmitted light; a photosensitive unit configured to receive the reflected light and / or the transmitted light to generate an intensity signal of the reflected light and / or the transmitted light in the time domain; and a signal processing unit configured to process and analyze the intensity signal in the time domain, wherein the signal processing unit uses a fast Fourier transform to convert the intensity signal in the time domain into an intensity signal in the frequency domain, and determines whether the intensity of the intensity signal in the frequency domain exceeds a threshold within a first default frequency range to determine whether the subject has tremor symptoms. This invention allows subjects to easily detect tremor symptoms.

To provide a signal processing device or the like that can estimate a data sequence including a signal with an unknown frequency band from among received signals having a small S / N ratio.A signal processing device 2A includes an A / D converter 215 that converts signals received by the flying object over a predetermined period of time by varying a time into a time-domain data sequence for each time, a fast Fourier transform (FFT) processing device 221 that performs FFT processing on the time-domain data sequence for each time with a plurality of different FFT points and outputs a frequency-domain FFT result data sequence at each FFT point, a correlation calculation device 222 that calculates a correlation between the frequency-domain FFT result data sequences at different times with the same FFT point for each segment based on a frequency resolution unit based on a sampling frequency of the A / D converter and the same FFT point and that performs the calculation for each of the plurality of different FFT points, and a data sequence selecting device 223 that selects a data sequence having the correlation equal to or greater than a threshold value.

Systems and methods for rendering a virtual three-dimensional space scene that includes location of one or more sources of intangible attributes are described. An exemplar method includes: (i) obtaining a first type of dataset; (ii) obtaining a second type of dataset and an offset distance; (iii) performing a fast Fourier transformation the second type of dataset to produce a frequency domain dataset; (iv) identifying one or more of the intangible attribute signals in a real space; and (v) spatializing the first type of dataset and offset to create a first type of spatialized dataset and spatialized offset; (vi) spatializing the second type of dataset to create a second type of spatialized dataset; (vii) aligning, using the spatialized offset, the first type of spatialized dataset with the second type of spatialized dataset to create an enhanced three-dimensional spatialized environment; and (viii) rendering the enhanced three-dimensional spatialized environment on a display component.

The application belongs to the field of edge computing acceleration, and relates to a computing acceleration method for cooperation of fast Fourier transform and neural network inference, wherein, at the operator deployment level, a computing method mixed with DFT discrete Fourier transform and FFT fast Fourier transform based on butterfly computing merging and tensor mapping strategy is deployed; at the interface integration level, a bus interface of a register access path in a tensor accelerator control path is reconstructed in a light weight manner to adapt to an edge computing platform; and at the operation level, a self-defined instruction is introduced into a tensor computing unit to enable the accelerator to independently complete a whole process task of FFT signal processing and NN intelligent identification. The application expands the operation instruction set on the hardware, avoids delay overhead caused by a large amount of intermediate data returned to the processor, and thus guarantees efficient execution of the FFT and the neural network task on the unified hardware, and meets multiple requirements of strong real-time performance, high precision and low power consumption.

The application discloses a three-dimensional neural network processing method, an image processing method, an image processing system and a storage medium, and belongs to the technical fields of neural networks and image processing. The three-dimensional neural network processing method based on a block circulant matrix model overcomes the irregular memory and calculation problems existing in the previous pruning and other model compression methods by constructing a block circulant matrix model, calculating an acceleration model and a full frequency domain model, and proposes to compress a three-dimensional neural network 3D CNN by using the block circulant matrix, and further utilizes fast Fourier transform FFT to accelerate calculation, so that the storage and calculation compression effects are significantly achieved on the premise of keeping the model structure regular. On this basis, the activation, batch normalization and pooling operations in the frequency domain are introduced, the frequent time domain / frequency domain switching overhead caused by the fast Fourier transform FFT is further eliminated, so that full frequency domain calculation is realized, and the calculation overhead during 3D CNN model reasoning is further reduced.

The application provides a homomorphic convolution acceleration method based on approximate fast Fourier transform, and belongs to the technical field of algorithm optimization of privacy calculation.The method mainly comprises client encryption, server-side calculation and client decryption, uses the fault tolerance feature of homomorphic convolution to perform optimized calculation on the homomorphic convolution, replaces the number theory transform NTT with fast Fourier transform FFT, and introduces an approximate method to further reduce the bit width, so as to reduce the hardware cost of each operation; in the process of determining the approximate FFT bit width, a multi-objective design space exploration method is adopted, different bit widths are used in multiple stages of fast Fourier transform, a space evaluation method based on a lookup table is designed, and multi-objective space exploration is performed on the space evaluation method, so that a design balance between calculation accuracy and power consumption is realized. The application is suitable for any convolution layer, reduces the overall overhead of homomorphic convolution, improves the calculation efficiency, and has a wide application prospect.

A method to classify heart murmurs as benign or pathologic. A digitized acoustic heart signature of a patient is captured on a computing device and processed using Fast Fourier Transformation to identify a plurality of component frequency waveforms, each having a power value. Based on the waveforms' power values, they are classified into a primary frequency waveform, harmonic frequency waveforms, and non-harmonic frequency waveforms. The heart murmur of the patient is classified using a ratio of the power values of the harmonic waveforms as a portion of the composite power value of all the waveforms, and an interface indication is provided to the user of the computing device. A computing device and software program per the invention are also disclose.