33 results about "Fast algorithm" patented technology

The invention provides an efficient transmission algorithm for HPLC carrier communication data, which belongs to the technical field of carrier communication, and comprises the following steps of: step 1, double-link separation processing: respectively processing frame control data and load data by adopting two separated links; 2, a frame control data processing flow: carrying out improved Turbo coding on the frame control data; step 3, a load data processing flow: firstly, carrying out adaptive scrambling on load data, and adopting Turbo coding with different parameter configuration from frame control data; step 4, OFDM symbol generation and transmission: adopting an optimized fast algorithm to reduce the operand and the processing time; and step 5, receiving end processing flow: respectively adjusting frame control and load data by adopting AGC (Automatic Gain Control) and time synchronization. The algorithm is high in anti-interference capability, remarkably reduces the bit error rate, is high in transmission efficiency, can adapt to different power line channel environments and data transmission requirements, and has good universality and stability.

The invention discloses a rail profile consistency evaluation method and system based on wheel-rail matching characteristics, and relates to the technical field of railway engineering.The rail profile consistency evaluation method comprises the steps that firstly, wheel-rail contact key indexes are analyzed, the positions of wheel-rail contact points are calculated based on three-dimensional profile data, and a model is established based on the non-Hertz contact theory to solve contact stress; a dynamic equivalent taper is obtained by using an equivalent taper fast algorithm; then, an analytic hierarchy process and an entropy weight method are combined to determine an index weight, weighted summation is performed after normalization processing is performed on original index data to obtain a comprehensive evaluation index CEI, and an evaluation standard is set in combination with a line and a train type; according to the method, multiple dynamic indexes are creatively fused to construct an evaluation system, a subjective and objective combination weighting method is adopted to overcome the defect of single weighting, the constructed quantitative comprehensive evaluation indexes provide accurate support for railway full-life-cycle management, compared with a traditional method, the evaluation accuracy is greatly improved, railway transportation safety and stability are effectively guaranteed, and the method is suitable for popularization and application. And the overall benefit and reliability are improved.

The application relates to a kind of massive SAR data imaging software design methods based on fast BP algorithm, for the existing fast BP imaging algorithm, by accurately estimating the data amount in the operation process, propose to use the available memory of operation server, dynamically correct J operator, carry out sub-scene processing to sub-set, use disk temporary storage intermediate operation result, solve the memory limit problem of SAR full scene full resolution imaging of super large data on the operation server with lower memory, greatly reduce the hardware memory cost of operation server.

The invention discloses a 4D wireless spectrum map reconstruction method in a dynamic environment, and the method comprises the steps: carrying out the modeling of missing spectrum data and mixed noise into a four-dimensional tensor model according to the four dimensions of two-dimensional space, frequency and time; in order to reduce the degree of freedom of the tensor model, the model is decoupled into an incomplete spectrum map corresponding to a single radiation source through a non-negative matrix factorization algorithm. Further considering the problem of mixed noise influence and calculation complexity, proposing an optimization function based on a dynamic threshold value and a fast algorithm combining random singular value decomposition and Nesterov accelerated gradient, and solving under a non-negative matrix factorization algorithm framework; and finally, reconstructing the frequency spectrum map corresponding to each radiation source by adopting parallel computing to obtain a complete 4D frequency spectrum map. According to the method, an accurate 4D spectrum map can be obtained based on spatial sparse sampling in a dynamic time-varying environment, and the high-precision spectrum situation sensing requirement in a complex noise environment is met.

The present application discloses a tire polishing curve fitting method, including the following specific steps: scanning data is subjected to mean linear filtering, and coordinate system conversion and processing, the scanning data is converted into polar coordinate representation, the pattern groove data is extracted, and further converted back to rectangular coordinates for maximum filtering to obtain approximate data of the tire surface without the pattern groove; on the basis of data preprocessing, the present application uses logical analysis method to summarize the law of traditional genetic algorithm, proposes an optimal state genetic algorithm, and applies it to tire laser scanning data processing, the optimal state genetic algorithm has the advantages of fast algorithm convergence speed, small calculation amount and the like in processing tire scanning data and fitting tire pattern groove curve, effectively improves the algorithm search speed and accuracy, and makes up for the deficiency of tire scanning algorithm theoretical research and practical application.

The invention provides an interface interaction method and device, and the method comprises the steps: determining a first virtual article, rendering the first virtual article to a UI interface, and then setting a trigger point and a trigger point lighting effect; according to the method, key points which are uniformly distributed are found on the surface of a complex three-dimensional object through a fast algorithm in a simple mode, different trigger points are generated for different virtual objects in an adaptive mode, and trigger interaction information corresponding to the virtual objects is prompted through the light effect of the trigger points, so that a user is guided to perform corresponding trigger activity operation, and the user experience is improved. The method is suitable for running in a mobile client; further, when the user gradually clicks the plurality of trigger points, gradually revealing a plurality of attribute values of the first virtual article at the target position of the UI until the overall score of the whole first virtual article is revealed; through the interactive design, the user obtains comprehensive experience, and the participation sense and exploration experience of interaction between the user and the virtual object are improved.

This invention discloses a lossless data compression and encrypted transmission method based on federated middleware, belonging to the field of computer application technology. The method includes: performing run-length encoding on the data to be processed based on federated middleware to obtain first compressed data; processing the first compressed data using a compression algorithm based on a raw-middleware dual dictionary to obtain second compressed data. This compression algorithm uses both the raw dictionary and the middleware dual dictionary, adding only values ​​that appear at a set frequency to the dictionary; sequentially performing Huffman coding and DES processing on the second compressed data to obtain encrypted data and a key; performing RSA processing on the key to obtain an encrypted key; and transmitting the encrypted data and the encrypted key to the target end using an encrypted compression transmission plugin of an experiment-and-train-enabled architecture. This method achieves lossless data compression and encryption based on federated middleware, with fast algorithm speed and high security.

The invention provides a face recognition method and system, computer equipment and a storage medium, and belongs to the field of face recognition, and the method comprises the steps: collecting a plurality of face images of a target person under a non-ideal condition, and extracting a high-dimensional semantic feature set of the face images; through an iterative optimization process, a customized dictionary exclusive to the target person is obtained based on the feature set learning, and sparse coding and dictionary atom updating are alternately carried out in the iterative process; finally, forming a dictionary database by the customized dictionaries of all the target persons; and extracting to-be-recognized face features, calculating reconstruction errors between the to-be-recognized face features and each dictionary in the dictionary database, and judging the identity according to a minimum error principle. According to the method, the recognition accuracy and robustness under small samples are remarkably improved, the real-time performance is ensured through a fast algorithm, the dependence on a large number of training samples is reduced, and the method is suitable for actual application scenes such as access control and security and protection.

The application discloses a unit ascending and descending load working condition optimization method based on historical working conditions, and collects historical ascending and descending load working conditions by fitting calculation on screening parameters and screening according to average fitting deviation and maximum deviation limit value. In actual matching process, the starting working condition load and the ending target load are set to ensure that the operation requirements of load ascending and descending operation are met. Different business priority needs in different business scenes can be met through different optimization methods, all working conditions under the same load ascending and descending condition are screened through setting a filtering time range, the optimized working condition is ensured to be accurate and reliable according to the optimization standard, the operation parameters under the specified load condition are adjusted according to the ascending and descending load working condition after optimization and the returned index data, the operation state of the unit reaches the optimum, the general unit ascending and descending load working condition optimization method shields business differences, provides an efficient and fast algorithm, greatly saves manpower, improves the calculation efficiency and improves the accuracy of business processing data.

The present application relates to the technical field of pipeline engineering safety monitoring and state evaluation, and discloses a kind of liquid-solid two-phase flow based on tee pipeline erosion defect fast algorithm, comprising: S1, along the inner wall of the tee pipeline of metal material in liquid-solid two-phase conveying system axial and circumferential, potential erosion area is discretely divided, form several independent erosion unit, define equivalent topographic feature parameter vector for each erosion unit, for corresponding pipe wall area erosion defect geometry state is characterized;S2, sensor is arranged at the preset monitoring position of tee pipeline, and multiple-source physical response signals and the like in the running process of tee pipeline are collected;The method realizes accurate inversion and dynamic evolution prediction of erosion defect under limited information by erosion defect parameterization modeling, running response mapping construction, online rapid inversion and consistency correction, solves the problems of low calculation efficiency, poor engineering applicability and insufficient evaluation accuracy of prior art.

The invention relates to the technical field of electromagnetic spectrum monitoring and signal processing, and discloses a low-altitude unmanned aerial vehicle electromagnetic interference complexity early warning method and system based on a fast FFT algorithm. According to the method, space electromagnetic signals are collected in real time, FFT frequency domain analysis is carried out to obtain spectrum data, unmanned aerial vehicle signal frequency and power and left and right interference signal frequencies and interference energy are extracted based on the spectrum data, the frequency coincidence ratio and the energy coincidence ratio are calculated in an unmanned aerial vehicle system working frequency band, and objective complexity is obtained through the product of the frequency coincidence ratio and the energy coincidence ratio. And determining an electromagnetic interference complexity grade by combining a preset grade division standard look-up table, and further outputting an alarm signal and / or prompt information. The system comprises an electromagnetic signal acquisition unit, a signal processing unit and an early warning output unit, wherein the signal processing unit completes parameter extraction, overlap ratio calculation, complexity calculation and grading output. According to the scheme, complexity grading evaluation with low calculation amount is realized, and the method is suitable for real-time early warning of a low-altitude unmanned aerial vehicle scene.

The invention relates to the field of steam turbine vibration monitoring, in particular to a bending interference fringe correction method based on angular point detection and a phase correlation function. The method comprises the following steps: determining angular points in an interference fringe image based on a FAST algorithm; angular point scale and direction enhancement is carried out, and the feature discrimination degree of angular points is improved; fourier transform is carried out on the reference column and the offset column to obtain a phase correlation diagram, and the position of the maximum response value is found in the phase correlation diagram; taking the position of the maximum response value as the center, and intercepting the response value of the m * m neighborhood; fitting neighborhood data by using an interpolation function; searching a real pole value of the difference function in a peak value region, wherein the offset corresponding to the pole value is the calculated sub-pixel offset; and according to the offset, carrying out translation transformation on the image information of the offset wavelength channel, or carrying out equivalent adjustor position information. The accuracy of vibration monitoring is improved.

The application relates to a real-time splicing method for core drilling images, and belongs to the field of image processing.The method comprises the following steps: for any two adjacent core drilling images, respectively adopting a FAST algorithm to quickly detect corner points, and adopting a Harris algorithm to remove weak corner points and reserve true corner points with high response values to obtain two true corner point images; adopting a quadtree division method to realize uniform distribution of the true corner points in each true corner point image, and adopting a non-maximum suppression method to screen high-quality corner points; adopting a fast approximate nearest neighbor matcher to perform initial matching on the high-quality corner points in the two images to obtain a plurality of initial matching pairs; adopting a homography geometric consistency inlier purification algorithm based on sparse feature points to perform accurate matching on the plurality of initial matching pairs to obtain an optimized homography matrix; and splicing the two adjacent core drilling images according to the optimized homography matrix.The application guarantees the real-time performance and accuracy of the splicing of the core drilling development images.

This invention discloses a fast forward modeling optimization method for three-dimensional gravity and gravity tensor, and a further optimization method for the system. The fast forward modeling method divides the underground three-dimensional space into multiple horizontal layered media and constructs a discrete model of the underground space and observation points. Based on the model division, the forward modeling coefficient matrix and coefficient spectrum matrix of gravity and gravity tensor are calculated. Based on the coefficient spectrum matrix, a fast algorithm is used to calculate the gravity value and gravity tensor value of each depth layer corresponding to the density model. The forward modeling values ​​of each layer are superimposed to obtain the gravity forward modeling anomaly of the density model. Furthermore, based on the parity characteristics of the fast Fourier transform of real number sequences, the spatial complexity of the forward modeling coefficient matrix is ​​reduced while ensuring fast calculation efficiency, providing support for further increasing the practicality of three-dimensional gravity inversion.

This invention provides a rapid prediction method for lunar orbit rendezvous guidance, achieving high-precision and rapid prediction to meet mission requirements. The prediction method of this invention applies the gravitational field acceleration calculation method used for GPS autonomous orbit determination of Earth orbit satellites to the field of lunar orbit rendezvous. Addressing the problems that the algorithm cannot be directly applied to the design of lunar orbit rendezvous guidance strategies, improvements and upgrades are made one by one, resulting in a high-precision and rapid algorithm suitable for lunar orbit rendezvous flight control missions to meet mission requirements. Specifically, this invention is the first to transplant this algorithm to the field of lunar orbit applications, which is unprecedented. Considering the special characteristics of the lunar gravitational field, where the acceleration measures of various gravitational perturbations are of similar order and cannot be approximated by the J2 term alone, the J22 term perturbation acceleration is added to the algorithm, thereby significantly improving the computational accuracy and numerical stability of the algorithm.

The application discloses a CPU double-path acceleration method for large-scale LLM sparse matrix multiplication, and relates to the technical field of high-performance computing. The method first constructs a fast matrix multiplication algorithm lookup table, generates an optimized algorithm through random walk and performs Hensel promotion to compensate for numerical errors; then performs two-stage division and zero block identification on the weight matrix, classifies it into complete zero blocks, near-zero blocks and dense blocks; then aggregates non-zero elements for the near-zero blocks and merges dense blocks into large blocks using dynamic programming; uses multi-core CPU to concurrently perform sparse path and dense path calculation, respectively calls sparse kernels and matching fast algorithms, and finally fuses the results based on position mapping using vector instructions. The application solves the problem of low utilization of unstructured sparse matrices through double-path shunting strategy and software and hardware co-optimization, significantly improves the calculation throughput and hardware resource utilization while ensuring the model accuracy.

A kind of multi-source shortest path method based on bidirectional SPFA, comprising: according to the traffic road network map of obtained construction directed weighted graph;Obtain multi-source shortest path query request;Select specific node as pre-processing starting point, calculate the shortest distance of pre-processing starting point to all other nodes using shortest path fast algorithm, construct and initialize the evaluation function array;For each shortest path query request, empty the node scheduling queue for storing pending node and reset each auxiliary array;Based on the evaluation function array dynamic optimization node scheduling queue, calculate the shortest distance in combination with shortest path fast algorithm;Iterative processing all shortest path query requests and return query result.The present application can effectively process the directed graph containing negative weight edge but not containing negative weight ring, and is suitable for large-scale network environment under traffic road network map efficient shortest path calculation.

The application discloses a photovoltaic array maximum power point tracking method and system based on a quantum marine predator-disturbance observation fusion algorithm, and specifically is as follows: on the basis of marine predator optimization, the duty cycle of a front-stage DC-DC converter is taken as a to-be-optimized control variable, candidate duty cycles are normalized and mapped into rotation angle parameters of a parameterized quantum circuit, quantum state coding, quantum gate operation and measurement sampling are performed under a quantum computing framework, and position updating of the marine predator algorithm is corrected according to measurement results, so that global optimization of quantum computing is realized; when a search solution enters a maximum power point neighborhood, a disturbance observation method is switched to for local fine tracking; and when environmental mutation or output power deviation exceeding a threshold is detected, quantum global search is restarted. The application improves the search ability for a global maximum power point under the condition of local shadow and multi-peak power curve, has fast algorithm convergence speed, strong steady-state operation performance and a wide application range.

This invention discloses a fast algorithm for solving two-dimensional nonlinear steady-state temperature fields using an improved domain decomposition method. This algorithm divides the solution domain into multiple non-overlapping sub-regions, enabling parallel computation of the nonlinear physical field distribution in each sub-region, thus avoiding the need to construct and store large global matrices in traditional finite element methods. Compared to overlapping domain decomposition methods, this invention simplifies the sub-domain partitioning process and only considers the sub-domain boundary nodes as overlapping parts, reducing the computational scale. Compared to non-overlapping domain decomposition methods, this invention relies on Dirichlet boundary condition interaction information, resulting in faster iterative convergence. This invention uses the improved domain decomposition method to solve the finite element model of the nonlinear steady-state temperature field. The steady-state temperature field distribution in each sub-region can be computed in parallel using the multi-threaded processor of the computing platform. Compared to finite element software, this invention can improve the computational speed for solving the nonlinear steady-state temperature field distribution of a contactor by up to 3.38 times.

The invention discloses a high-precision calculation method for a partial differential equation with an interface based on an immersed interface technology, and relates to the field of partial differential equation numerical solutions. According to the method, aiming at an elliptic partial differential equation containing an interface, a homogeneous function is constructed through a potential theory to realize homogeneous processing of an interface jump condition, numerical discretization is carried out in combination with a stable generalized finite element method (SGFEM), and high-precision solution is realized on a non-body-fitted grid by utilizing a boundary integral equation fast algorithm and a singular integral processing technology. The method does not need to depend on a body-fitted grid, reduces the grid division complexity, improves the calculation efficiency and precision, and is suitable for two-dimensional and three-dimensional complex interface problems.

The invention relates to the technical field of audio processing, and discloses an automatic audio adjusting method and system based on multi-window audio mixing, a terminal and a storage medium, the method comprises the following steps: obtaining dual-track PCM data and a target window in a multi-window mode, and establishing a corresponding relation according to the dual-track PCM data and the target window to obtain a corresponding relation table; obtaining a basic gain, and based on the corresponding relation table, performing dynamic calculation on the dual-track PCM data according to a preset sound mixing rule and the basic gain to obtain a target gain weight; and obtaining mixed dual-channel PCM data, and carrying out sound mixing adjustment processing on a sampling value of the mixed dual-channel PCM data according to a preset fast algorithm and the target gain weight to obtain target mixed dual-channel PCM data. According to the invention, sound mixing adjustment is carried out on the mixed dual-track PCM data through the target gain weight, and adaptive audio adjustment in a multi-window mode is realized.

The application discloses a high-precision ADC linearity test method and system, comprising the following steps: inputting a plurality of signal differences to an ADC through a control signal generator, a voltage source, an operator and a channel of a multiplexer, and obtaining a group of output code bits of each signal difference; summing and subtracting two preset signal differences, and summing and subtracting the output code bits of the two preset signal differences, to obtain summing and subtracting results; determining a multivariate linear equation group according to a preset segmented nonlinear model containing a parameter to be solved, the summing and subtracting results and the output code bits; obtaining an optimal solution by solving the equation group, and determining integral nonlinear errors and differential nonlinear errors of the ADC according to the optimal solution and the preset segmented nonlinear model. The application can calculate common-mode and differential-mode of integral nonlinearity and differential nonlinearity, can reduce the precision requirement of an input signal, can greatly shorten test time and sampling points, and has simple system structure, fast algorithm running speed and wide application prospect.

This invention relates to the field of capacitance calculation technology and discloses a fast algorithm for extracting parasitic capacitance in large-scale integrated circuits. This method combines the method of moments (MoM), a fast multipole algorithm for layered dielectrics, and overlapping region decomposition preprocessing techniques to construct a complete parasitic capacitance extraction solution. By directly introducing the Green's function for the layered dielectric, the numerical solution strictly satisfies the electric field transport conditions at the dielectric interface, and the electrostatic problem in the layered dielectric is transformed into boundary integral equations defined on the interconnect surface. Subsequently, the MoM is used to discretize these boundary integral equations, resulting in a large-scale dense system of linear algebraic equations. To improve solution efficiency, an efficient preprocessing strategy based on overlapping region decomposition is further designed, and combined with the matrix-free minimum residual iteration method and the layered fast multipole algorithm, achieving efficient solution with low computational and storage overhead.

The application discloses a reinforced concrete structure improvement time domain synthetic aperture imaging fast algorithm, and steps are as follows: a reinforced concrete two-dimensional finite element simulation model is established, and a half diffusion angle is calculated; simulation testing is carried out on an ultrasonic probe in the reinforced concrete two-dimensional finite element simulation model, and full matrix data are formed; the reinforced concrete two-dimensional finite element simulation model is pixelated, and a diffusion angle factor is calculated; whether synthetic aperture processing is carried out is compared according to the half diffusion angle in step one and the diffusion angle factor in step three; and imaging processing is carried out on the full matrix data in step two according to a time domain synthetic aperture full focusing algorithm. The application has the beneficial effects that the application determines the diffusion angle factor of each pixel point to each transmission ultrasonic probe, the area outside the diffusion angle of the ultrasonic probe is not subjected to sound path calculation and amplitude superposition, the algorithm efficiency is greatly improved, meanwhile, imaging of the pseudo defects outside the diffusion angle is avoided. The smaller the diffusion angle is, the more the data quantity is, and the more obvious the algorithm acceleration effect is.

The present application relates to the technical field of wireless communication, in particular to an antenna radiation and mutual coupling collaborative optimization system based on a time-domain hybrid fast algorithm. The antenna radiation and mutual coupling collaborative optimization system based on the time-domain hybrid fast algorithm is applied to a UAV group communication system, and comprises an antenna array unit, a data acquisition unit, a time-domain hybrid fast algorithm unit, a mutual coupling calculation unit, an optimization control unit and a communication coordination unit. In the present application, the three-dimensional geographic coordinates, attitude angle data and signal strength of the UAV group are acquired in real time by the data acquisition unit, and the real-time mutual coupling coefficient analysis of the mutual coupling calculation unit is combined, so that the system can dynamically perceive the formation mode change and trigger the optimization instruction, and the optimization control unit compares the preset threshold value, preferentially adjusts the node with the largest deviation degree, ensures that the antenna spacing and the radiation pattern are always adapted to the dynamic environment, reduces the mutual coupling effect, and significantly improves the communication stability.

The invention discloses a shoe material nesting method, device and equipment based on polygonal scanning lines and a medium, and relates to the technical field of shoe material processing. Shoe material part graphs are preprocessed by adopting a Douglas graph simplification algorithm; aiming at polygon features of the part, forming a combination body in a form of self or 180-degree rotation, constructing an NFP through a fast NFP algorithm based on a trajectory, and sampling and selecting points; calculating an assembly translation vector by means of geometric Boolean operation and a quadtree algorithm; a single-row rectangular block array scheme is adopted, an optimal array is selected for placement based on density and height comprehensive evaluation, a removal backtracking mode is adopted for the last column or row, a flattening calibration error threshold value is set, and non-overlapping compact placement of parts is achieved so as to minimize the length of a mother board. According to the method, through multi-link optimization, the material utilization rate and calculation efficiency of shoe material sleeving are greatly improved, the sleeving stability and adaptability are enhanced, material waste is effectively reduced, different scene requirements are met, and the processing cost is reduced.

The invention relates to the technical field of digital image processing, in particular to a quaternion representation-based color image denoising method for special affine matrix wavelets, which comprises the following steps of: for a to-be-denoised color image, firstly, enabling R, G and B components of the color image to correspond to three imaginary parts of a quaternion so as to represent the three imaginary parts as quaternion signals; secondly, mapping the quaternion signal into a second-order complex matrix value signal through an equidistant operator, decomposing the matrix value signal by using multi-resolution analysis related to special affine convolution in a matrix value function space, performing threshold processing on detail coefficients, reconstructing the processed coefficients by using a fast algorithm, and finally obtaining a reconstructed quaternion signal; and finally, restoring the matrix value signal into a quaternion signal through inverse mapping of an equidistant operator, reading component values of each channel, and outputting a denoised color image. According to the method, the color image is processed as a whole, the complexity of quaternion convolution is avoided, and the defects in the prior art are overcome.

This invention relates to a fast method for estimating the direction of arrival (DOA) of mixed polarization signals with enhanced separation, comprising the following steps: multi-polarization array arrangement; multi-polarization array output modeling; fast estimation of the DOA of partially polarized signals; elimination of low-precision DOA of fully polarized signals; initialization of the oblique projection matrix; and estimation of the DOA of fully polarized signals based on oblique projection iteration. The advantages of this invention are: firstly, the method eliminates the influence of leakage from fully polarized signals and improves the accuracy of the oblique projection matrix through iterative calculation, thereby enhancing the separation between fully polarized and partially polarized signals; secondly, the method fully utilizes the characteristics of mixed polarization signals, resulting in high DOA estimation accuracy; and finally, the method does not require spatial domain search, thus exhibiting fast algorithm execution speed.

The invention discloses an order-driven mixed loading tray stereoscopic warehouse sorting optimization method, which is based on a sorting system comprising a stereoscopic warehouse, a secondary stock area, an RGV conveying system and a disassembly sorting robot, and comprises the following steps: acquiring order and inventory data through a warehouse management system; a hierarchical optimization mathematical model with the maximum order completion number as a first priority and the minimum tray call-in number as a second priority is constructed, an optimal tray combination is solved by adopting a two-stage improved greedy heuristic algorithm, tray call-in and sorting operation is executed, invalid SKU merging and clearance are performed on the remaining trays after sorting, and finally, the optimal tray combination is obtained. After the cache space is released, loop iteration optimization is carried out until all orders are completed; according to the method, the warehouse-in and warehouse-out frequency of the stereoscopic warehouse is remarkably reduced, the cache space utilization rate and the order fulfillment efficiency are improved, the algorithm solving speed is high, the real-time scheduling requirement is met, and the method is suitable for zero-removal sorting scheduling of the large-scale automatic stereoscopic warehouse.

The application discloses an ECG signal adaptive threshold wavelet filtering method and device, which is applied to ECG signal measurement, and adjusts the wavelet threshold of each layer of wavelet filtering from an initial value by a set step length, and calculates a self-correlation function according to a fast algorithm of the self-correlation function. After each filtering, the self-correlation value of the filtering result is recorded, and when the self-correlation value reaches a maximum value, the corresponding wavelet threshold is recorded as an optimal wavelet threshold. The self-correlation function is calculated from the sequence correlation of the signal itself after denoising according to the correlation and self-correlation characteristics of adjacent time instants of the ECG signal. Finally, the optimal wavelet threshold is used for adaptive filtering of the ECG signal. The application selects the optimal wavelet threshold of the wavelet filtering through the calculation result of the self-correlation function, can evaluate the filtering effect of the wavelet filtering method in the case that there is no clean and noise-free reference signal, and further optimizes the wavelet threshold parameter, and can better retain useful information and obtain a higher signal-to-noise ratio.