18 results about "Variable window" patented technology

The invention relates to the technical field of electric digital data processing, and discloses a data processing system for message management, which comprises a look-ahead buffer unit for maintaining a sliding window with variable window size parameters and pre-reading a message sequence; the mapping logic circuit is used for converting the resource identifier into a resource request mask; the state register is used for storing a global occupancy bitmap for representing resource occupancy; the scheduling controller is used for distributing messages according to bit operation results, counting bitmap setting quantity based on the population counting instruction to generate a resource saturation index, and then adjusting window size parameters in a negative feedback mode. The resource contention entropy value is directly sensed by utilizing a hardware instruction, nanosecond-level self-adaptive breathing control of a scheduling window is realized, and the service life of the scheduling window is prolonged. The problem of physical computing power collapse caused by bitmap scanning jitter in a high-concurrency scene is solved.

This invention provides a rotation-aware enhanced variable window attention super-resolution method, belonging to the field of image processing technology. It includes acquiring and preprocessing the original remote sensing image of the target object, segmenting it into several basic windows, extracting feature vectors, using quadrilaterals to predict the basic parameters of the projective transformation matrix based on the extracted feature vectors to obtain the reconstructed projective transformation matrix, extracting the rotation angle difference between any two quadrilaterals as a rotation-aware term, establishing a variable window attention mechanism, embedding the variable window attention mechanism into a SwinIR network to build a high-precision super-resolution model architecture, training the high-precision super-resolution model, inputting real-time remote sensing images into the high-precision super-resolution model, and outputting a high-resolution image containing the target sampling area. By combining the variable window attention mechanism with the rotation-aware mechanism, the super-resolution reconstruction accuracy and geometric consistency of rotated objects are significantly improved while maintaining computational efficiency.

The invention discloses a weight self-adaptive adjusting system and method based on posture recognition, and particularly relates to the technical field of man-machine cooperation and wearable robotics.The method comprises the steps that firstly, multi-modal data are obtained through an IMU and a visual camera device, and PTP clock synchronization, coordinate system calibration and Kalman filtering processing are completed; then, the system measures the action rhythm and the sensing credibility according to indexes such as KLE, LMPL, BDR and SAC, self-adaptive switching is conducted between a constant window sliding window mechanism and a variable window sliding window mechanism, and the window length is calculated in combination with the rate level under the variable window mechanism; the time sequence modeling adopts an LSTM / GRU network supporting variable-length input and a mask mechanism, and outputs an attitude evolution trend, load response pre-judgment and sudden action risks; and the control end generates a feed-forward adjustment instruction of multi-actuator cooperation based on a prediction result, and realizes self-correction and individualized parameter self-adaption through feedback monitoring.

The present application relates to a method and device for identifying broadband oscillations with a multi-band variable window length, wherein the method comprises: forming a frequency test set of a target frequency band based on multiple frequency test points in the target frequency band; calculating a window length corresponding to a single oscillation mode that satisfies a preset minimum condition; calculating a window length corresponding to a single oscillation mode that satisfies a preset maximum condition; integrating the window lengths in the frequency test set that satisfy the preset shortest condition to obtain a window length set that satisfies the preset shortest condition; integrating the window lengths in the frequency test set that satisfy the preset maximum condition to obtain a window length set that satisfies the preset maximum condition; integrating the frequency test set, the window length set that satisfies the preset shortest condition, and the window length set that satisfies the preset maximum condition to perform frequency band division and window length selection on the target frequency band. Thus, the problem that the related technology is difficult to balance the detection response speed and calculation accuracy requirements in a multi-modal oscillation scenario is solved.

The present invention discloses a method for predicting the SOC of a lithium-ion battery based on a variable window adaptive unscented Kalman filter. First, the parameters of the second-order RC lithium-ion battery equivalent circuit model are estimated by adaptive forgetting factor least squares (AFFRLS); then, the optimal noise covariance matching window size of the adaptive unscented Kalman filter (AUKF) is determined by adaptive genetic algorithm (AGA) training; the obtained window size is used as the window cardinality to predict the battery SOC by AUKF; then, the change in the distribution of the error information sequence is identified by Allan variance analysis, and the window size is updated according to the update rule. The present invention determines the time window size of the AUKF by AGA, which is more intelligent; in addition, the Allan variance analysis method is introduced to improve the estimation accuracy of the noise covariance, thereby improving the algorithm's tracking ability for nonlinear time-varying systems.

The invention discloses a self-adaptive overlapped framing and variable window phase measurement method, device and system based on signal state perception, and belongs to the technical field of digital signal processing and phase measurement. Aiming at the technical problems that a fixed overlapping ratio and a single window function are adopted in an existing phase measurement method, resolution ratios of a time domain and a frequency domain cannot be considered under a time-varying signal, and frequency spectrum leakage and phase jump are easily introduced, the invention provides a joint self-adaptive preprocessing method. The method comprises the following steps: firstly, framing collected signals, and judging whether the signal state is a steady state or an unsteady state according to smoothness detection of absolute value sums of adjacent sampling points; according to the determined signal state, adaptively configuring an overlapping rate between adjacent data frames and window function type parameters, and then, before fast Fourier transform is carried out, introducing a window function coherent gain compensation mechanism to eliminate an amplitude reference error caused by window type switching; and finally calculating the phase difference based on the corrected spectrum result. According to the method, the overlapping framing and window function parameters are adaptively adjusted according to the signal state, the phase measurement continuity is ensured, the phase measurement precision and stability under the multi-frequency signal are improved, and the method has good real-time performance and engineering application value.

The application relates to the technical field of gene sequencing, in particular to a CNV detection method based on an isolated forest algorithm, a medium and equipment. The method comprises the following steps: obtaining genomic sequencing data of a CNV event introduced in a reference genome from a Bam file of single-cell DNA sequencing; adopting a variable window strategy to divide the reference genome into windows, and adjusting the windows through a consistent read quantity to obtain a segmentation site information file; calculating RD signal values in each window according to the segmentation site information file and the genomic sequencing data, and extracting PEM signals to obtain PEM signal values; performing multi-feature calculation and analysis on the RD signal values and the PEM signal values based on the isolated forest algorithm; and identifying CNV events in each window according to an analysis result. The application can effectively identify CNV events in single-cell DNA sequencing data, not only overcomes the limitations of traditional methods in single-cell DNA sequencing data, but also improves the accuracy and reliability of CNV event detection.

The invention relates to the technical field of phasor measurement, in particular to a broadband phasor self-adaptive variable window length measurement method and device for a power system, and the method comprises the steps: collecting a sampling signal of a target power system, responding to a non-power-frequency oscillation component in the sampling signal, determining the time window length of interpolation calculation, and calculating the time window length of the target power system according to the time window length. And calculating a phasor estimation value of each frequency component according to the signal data of the time window length, generating candidate oscillation modes, taking the frequency of at least one candidate oscillation mode as an index, querying a certain frequency-window length corresponding relation, determining the corresponding shortest time window length, and outputting a broadband phasor measurement result. Therefore, the problem that effective balance of measurement precision, calculation complexity and response speed is difficult to realize in practical engineering application due to the fact that the frequency band application range is narrow or the calculation complexity is high in the prior art is solved.

The invention discloses a front-end page generation method and device, electronic equipment, a storage medium and a program product. The method comprises the following steps: acquiring components configured by a user, and adding the components configured by the user as editable variables to an editable variable window; in response to a formula configuration operation of a user on the editable variable, obtaining each formula function and the editable variable associated with each formula function, and generating an association relationship between each component and each formula function; and generating a front-end page according to the association relationship between each component and each formula function. According to the scheme, the problems that an existing front-end page generation mode is poor in flexibility and complex configuration logic is difficult to achieve are solved, the components serve as variables for formulation configuration, the complex dependency relation between the components can be established, dynamic configuration of the components is achieved, and the flexibility of front-end page generation is improved.

This invention provides a fine-grained code encryption method based on a variable window and a method for executing the code thereon. The fine-grained code encryption method includes: setting a window size based on the machine code length of the instruction statements in the target program; and targeting window P... i The machine code of each instruction statement is used with key K. i Encryption is performed, and based on window P i The machine code length and type of the instruction statement in the window P are used to determine the window P. i Slide to a new window; after processing the target program, an initial encryption program is obtained; after injecting the interpreter into the initial encryption program and adaptively modifying the metadata of the initial encryption program, the encryption program of the target program is obtained. This invention utilizes a variable window mechanism to ensure data confidentiality and effectively increases the analysis cost for attackers.

The embodiment of the invention provides an intelligent gateway and a variable window upgrading method. According to the method, upgrading data sent by an optical line terminal based on an upgrading window can be received. And recording a first count value of the number of received sub-messages and a second count value of the number of processed sub-messages. And in response to a receipt signal of upgrade data transmission failure, calculating a reference value according to the first count value and the second count value, the reference value being equal to the second count value when the first count value is greater than the second count value or the first count value is smaller than the window size. And recording the reference value according to the optical line terminal, so that the optical line terminal sends the sub-message according to the reference value. According to the method, the window size is calculated and updated through receiving and processing information of sub-messages in the upgrade data, and rapid and accurate transmission of the upgrade data can be ensured.

The invention discloses a data registration method based on a parallel variable window convolutional neural network, and the method comprises the steps: S1, constructing a model of the convolutional neural network, constructing a multi-head similarity module as output, setting an overall loss function, and carrying out the training; s2, traversing the measurement data by using a plurality of windows with different sizes of data to be registered, and inputting results into the model in parallel; s3, calculating the similarity of the feature vectors of the windows through the convolutional neural network, and determining an alternative region; and S4, traversing by taking the alternative region as a center, calculating cosine similarity, and taking the region with the highest cosine similarity as a registration region. According to the method, the structure of the convolutional neural network is improved and is combined with similarity calculation, so that a structure with a strong data matching effect is constructed; window change is combined, rough adjustment of similarity is calculated for the first time, secondary fine adjustment of cosine similarity is calculated again, and calculation accuracy is improved; and parallel data processing is supported, and the processing efficiency is improved.

The application discloses a kind of underdetermined time-varying operating modal parameter identification method and device based on statistical characteristic variable window length, comprising: obtaining the response signal sequence of structure vibration under the set environment excitation and processing, obtain the processed response signal subsequence in current sliding window, extract time-frequency feature matrix to the processed response signal subsequence in current sliding window, and extract principal component matrix from time-frequency feature matrix using principal component analysis, determine lag period using autocorrelation function analysis;Modal parameters of current sliding window are estimated according to the time-frequency feature matrix of current sliding window, lag period and principal component matrix;Statistical characteristics of current sliding window are calculated and adaptive window length adjustment strategy is designed, to obtain the window length of next sliding window;The next sliding window is used as the current sliding window, and the above steps are repeated, and the underdetermined time-varying operating modal parameter can be accurately identified.

The invention provides a rotation perception enhanced variable window attention super-resolution method, and belongs to the technical field of image processing. Comprising the steps of collecting and obtaining an original remote sensing image of a target object for preprocessing, segmenting the original remote sensing image into a plurality of basic windows, extracting feature vectors, predicting basic parameters of a projective transformation matrix by using quadrangles according to the extracted feature vectors, obtaining a reconstructed projective transformation matrix, extracting a rotation angle difference of any two quadrangles as a rotation sensing item, and obtaining a rotation sensing result. The method comprises the following steps: establishing a variable window attention mechanism, embedding the variable window attention mechanism into a SwinIR network to establish a framework of a high-precision super-resolution model, training to obtain the high-precision super-resolution model, inputting a real-time remote sensing image into the high-precision super-resolution model, and outputting to obtain a high-resolution image containing a target sampling area. Through the combination of the attention mechanism of the variable window and the rotation perception mechanism, the super-resolution reconstruction precision and geometric consistency of the rotating ground feature are significantly improved while the calculation efficiency is maintained.

The present invention relates to the field of image processing, and more particularly to a digital image correlation method based on variable window matching technology. The method utilizes a variable search window to implement a fast search method that can be used for integer pixel searches, achieving fast and accurate integer pixel measurement, significantly improving pixel point matching efficiency, and shortening calculation time. The method, based on variable window matching technology, eliminates the need for a full-field integer pixel search and instead performs an integer pixel search only on the first point and points where a sub-pixel search failed, thereby improving calculation speed and enabling correction of search errors.

The present invention discloses a SAR water depth inversion method driven by variable window sliding segmentation, which belongs to the field of synthetic aperture radar technology and is used for water depth inversion, including image segmentation and water depth inversion. Image segmentation includes regular adjustment of the original image, information storage, coastline identification and noise processing, pixel extreme value judgment, determination of pixel change function, and window sliding. After extracting the coastline and determining the starting point, the pixels are expanded to both sides of the starting point on the coastline and the pixels invaded by the coastline are eliminated, thereby improving the utilization of nearshore images. By dynamically adjusting the pixel size, a more accurate surge wavelength is obtained. Compared with the existing technology, the present invention accurately extracts wavelength information of different regions, avoids complex manual judgment, and improves segmentation efficiency and inversion accuracy. For irregular coastlines, the utilization rate of water depth inversion of images in areas near the coastline is increased by changing the starting point along the coastline and expanding outward.

This invention relates to the field of electronic digital data processing technology and discloses a data processing system for message management, comprising: a look-ahead buffer unit that maintains a sliding window with variable window size parameters and pre-reads message sequences; a mapping logic circuit that converts resource identifiers into resource request masks; a status register that stores a global occupancy bitmap representing resource occupancy; and a scheduling controller that distributes messages based on bit operation results and generates a resource saturation index by counting the number of bitmap bits set based on population counting instructions, thereby negatively feeding back to adjust the window size parameters. This invention utilizes hardware instructions to directly perceive resource contention entropy values, achieving nanosecond-level adaptive breathing control of the scheduling window and solving the problem of physical computing power collapse caused by bitmap scanning jitter in high-concurrency scenarios.

The present invention discloses a data registration method based on a parallel variable window convolutional neural network, comprising the following steps: S1, constructing a convolutional neural network model and constructing a multi-head similarity module as output, setting an overall loss function and training; S2, using multiple windows of different sizes of the data to be registered to traverse the measured data, and inputting the results into the model in parallel; S3, using the convolutional neural network to calculate the similarity of the feature vectors of each window and determine the candidate area; S4, taking the candidate area as the center and traversing again, calculating the cosine similarity, and using the area with the highest cosine similarity as the registration area. The present invention improves the convolutional neural network structure and combines it with similarity calculation to construct a structure with a strong data matching effect; furthermore, it combines window variation, rough adjustment of the initial similarity calculation, and secondary fine adjustment of the recalculation of the cosine similarity to improve the calculation accuracy; furthermore, it supports parallel data processing and improves processing efficiency.