11 results about "Discrete transform" patented technology

The invention discloses a communication method for realizing orthogonal time chirp space modulation based on discrete Fresnel transform, which is suitable for a mobile scene, and is characterized in that a data symbol is modulated on a two-dimensional complex chirp carrier on a delay-Fresnel Doppler plane, and the system performance is improved by using the interference resistance of the chirp wave. The system for realizing orthogonal time chirp spatial modulation based on discrete Fresnel transform provided by the invention has better bit error rate performance under a time-varying channel, especially under a high signal-to-noise ratio condition, is especially suitable for high-speed mobile application, and only increases a small amount of phase rotation complexity compared with OTFS.

The present application relates to the technical field of data transmission, and is a multi-path underwater acoustic signal transmission time calculation method based on reinforcement learning, specifically comprising: collecting a wideband M sequence burst signal, and performing discrete transformation and signal pre-enhancement processing on the collected multi-path carrier original data, and performing multi-dimensional feature extraction on waveform regularity features, energy clustering nonlinear mutation features and sound field geometric evolution features; calculating the propagation clock drift rate of the current signal transmission path, cross-medium correcting the propagation clock drift rate based on an environmental feedback model to obtain the arrival deviation of the actual underwater acoustic signal; based on the arrival deviation, dynamically updating the receiving decision window length of the data transmission link, and feeding back to the communication carrier demodulation engine in real time for time step synchronization. The present application solves the problem of poor reliability of sound signal analysis under high dynamics and extreme conditions in the prior art when the hydrological conditions change dramatically for a long time.

The application discloses a kind of digital hybrid coding methods based on large model, including the following steps: S1, pre-processing to be encoded data;S2, feature learning method driven by diffusion model is used to feature coding to pre-processing data;S3, neural network coding is carried out to feature coding data, and based on variable bit rate quantization method dynamically adjusts encoding bit number;S4, adaptive entropy coding is carried out to neural network coding data, based on normalized stream entropy coding method carries out probability density transformation;S5, discrete transform coding is carried out to entropy coding data, and hierarchical sub-block quantization method is used to execute hierarchical quantization to different frequency components;S6, based on A3C optimization transform coding data's code length distribution and entropy coding parameter, extract lightweight coding model from diffusion model using knowledge distillation method, generate final optimization coding data.The application improves data compression efficiency and coding quality significantly by hybrid coding and dynamic optimization strategy.

The invention discloses a thermal superstructure manufacturing method, device and system based on discrete transformation thermology, and belongs to the technical field of heat conduction and heat flow regulation and control. The method comprises the steps of performing discrete simplex mesh generation on a design domain to obtain a mesh, and appointing a hard constraint for an internal function boundary according to a regulation and control function; piecewise linear mapping is defined on the grid, optimization solving is carried out through two stages, the first stage punishes a negative Jacobian determinant to eliminate folding to obtain bijection mapping, and the second stage minimizes conformal distortion to suppress anisotropy; and deducing a thermal conductivity tensor field of a physical domain by utilizing a Jacobian matrix J, and finally carrying out microstructure matching filling and adopting additive manufacturing. The problems of folding and extreme parameters easily occurring in complex geometric transformation thermal design are solved, efficient thermal management and omni-directional thermal regulation and control under any complex shape can be achieved, and the experimental verification error is smaller than 5%.

The application discloses a lightning disturbance discrimination method for flexible HVDC transmission line based on instantaneous frequency characteristics, and specifically comprises the following steps: step 1, extracting voltage and current data in a time window from 1ms before protection starting to 1.0ms after protection starting, and obtaining line mode voltage forward and reverse traveling waves; step 2, performing discrete S transform on the line mode voltage reverse traveling wave obtained in step 1 to obtain a mode time-frequency matrix, and extracting an amplitude-frequency curve at a fault occurrence moment; step 3, obtaining a maximum value number Q of the instantaneous amplitude-frequency curve, if Q=1, it is lightning disturbance, and the discrimination ends; if Q>1, it is a fault, and step 4 is entered; step 4, defining a frequency of a point with the maximum amplitude in the amplitude-frequency curve as a main frequency F1, comparing the main frequency F1 with a threshold value F set , and judging a fault type according to a comparison result. The discrimination method provided by the application is simple in calculation, and can accurately judge lightning disturbance and lightning fault.

The application discloses a point cloud 3D target detection method and model based on a discrete Transform, and the method comprises the following steps: S1, collecting point cloud data frames of objects in real time; S2, performing point cloud voxelization on the point cloud data frames to obtain initial voxels; S3, extracting voxel features containing dynamic information and static information from the initial voxels through a 3D backbone network based on a discrete Transform; S4, mapping the voxel features finally output in the step S3 to a BEV space to obtain corresponding 2D BEV features; and S5, sending the 2D BEV features to a 3D target detector through a Neck network to perform 3D target detection, and obtaining object attribute information of objects in a 3D space.

Embodiments of the present specification provide a method for constructing a processing circuit for a target transform. The target transform is a discrete transform or its inverse transform that transforms an input coefficient sequence into an output coefficient sequence based on a rotation factor. The method includes, for a K-point input coefficient sequence to be processed, determining a plurality of candidate decomposition points corresponding to a k-bit coefficient index. Then, starting from a low-bit decomposition point, for each candidate decomposition point, determining the minimum storage cost under each candidate decomposition point according to a decomposition cost evaluation function through recursive index bit number decomposition for several levels, so as to determine a target decomposition mode of the k-bit coefficient index with the minimum storage cost. The decomposition cost evaluation function limits the storage cost to include the cost of a (n-p)th order first transform, the cost of a pth order second transform, and the local cost for inter-level rotation factor multiplication. According to the target decomposition mode, a corresponding memory for the rotation factor is allocated to form a processing circuit.

The application discloses a power quality disturbance feature extraction method and system based on segmented multi-resolution S transform, relates to the technical field of power quality monitoring, and aims to solve the problem that traditional time-frequency analysis methods are difficult to accurately capture power quality disturbance features in different frequency bands due to fixed resolution. The application comprises establishing a mathematical model of power quality disturbance signals, including various single and composite disturbance models; discretizing the signals based on continuous S transform and applying one-dimensional discrete S transform; dividing the frequency bands into three segments, i.e., low, medium and high, according to disturbance frequency characteristics; introducing a Gaussian window function with different adjustment factors into each frequency band to adaptively adjust the time-frequency resolution; combining S transform with the window function to obtain a discrete expression of segmented multi-resolution S transform; and extracting disturbance feature parameters based on the time-frequency matrix obtained through transformation. The technical scheme realizes adaptive optimization of time-frequency resolution, and improves the extraction accuracy and reliability of complex power quality disturbance features.

The invention provides an SOTFS modulation V2V communication method based on bionic cluster resonance and pheromone memory, and relates to the technical field of wireless communication, and the method comprises the steps: receiving an SOTFS signal of a neighbor vehicle, and estimating a delay-Doppler channel response and a Doppler mass center; calculating a resonance score reflecting link quality and motion consistency based on the information; updating a pheromone memory for evaluating the long-term stability of the link according to the score; based on the resonance score and pheromone memory, determining an optimal subcarrier resource mapping scheme and feeding back the optimal subcarrier resource mapping scheme to the transmitting end; according to the scheme, a transmitting end arranges symbols embedded with digital pheromone signatures in a delay-Doppler domain, and generates self-adaptive SOTFS signals through inverse discrete ZAK transform modulation for transmission. Through deep fusion of bionic cluster intelligence and delay-Doppler domain signal processing, distributed, high-reliability and low-delay inter-vehicle cooperative communication in a high-dynamic vehicle-mounted environment is realized.

Embodiments of the present specification provide a method for storing or reading a rotation factor in a target transform. The target transform is a discrete transform or its inverse transform that transforms an input coefficient sequence into an output coefficient sequence based on a rotation factor. The method includes determining a target rotation factor to be stored, whose power is a result of a multiplication of a first factor of a first number of bits and a second factor of a second number of bits modulo a target value; and storing the target rotation factor by a two-level storage manner, the two-level storage manner including storing the target rotation factor at a first address in a rotation factor storage, wherein the rotation factor storage includes a first number of first storage units, the first number being a number of different modulo multiplication results generated by the first factor of the first number of bits and the second factor of the second number of bits; and storing an index value pointing to the first address at a second address in an index storage, wherein the index storage includes a target value of second storage units, the second address corresponding to the power of the target rotation factor; and the target value is greater than the first number.

The invention discloses an electric energy quality disturbance feature extraction method and system based on segmented multi-resolution S transformation, relates to the technical field of electric energy quality monitoring, and aims to solve the problem that electric energy quality disturbance features of different frequency bands are difficult to accurately capture due to fixed resolution in a traditional time-frequency analysis method. The method comprises the following steps: establishing mathematical models of power quality disturbance signals, wherein the mathematical models comprise multiple single and composite disturbance models; discretizing the signal based on continuous S-transform and applying one-dimensional discrete S-transform; dividing a frequency band into a low section, a middle section and a high section according to disturbance frequency characteristics; gaussian window functions containing different adjustment factors are respectively introduced into each frequency band so as to adaptively adjust the time-frequency resolution; combining S transformation with the window function to obtain a discrete expression of segmented multi-resolution S transformation; and extracting disturbance characteristic parameters based on the transformed time-frequency matrix. According to the technical scheme, self-adaptive optimization of the time-frequency resolution is realized, and the extraction precision and reliability of complex power quality disturbance characteristics are improved.