39 results about "Time transformation" patented technology

According to the video stream image optimization method and device provided by the embodiment of the invention, a dynamic fuzzy kernel generation mechanism is innovatively designed, and the data processing security is ensured through space-time decoupling and physical constraint. A content-motion double-branch network is constructed, and a reliable feature reconstruction system is established in combination with residual connection and space-time transformation. A physical constraint corrector is introduced, and high-quality video output is provided while user privacy is protected through adaptive fusion and rule correction. According to the method, the defects of the traditional technology in the aspects of fuzzy processing, feature decoupling, image optimization and the like are effectively overcome.

The invention discloses a multi-type agent trajectory prediction method and system fused with a multi-graph convolutional network, and the method comprises the following steps: S1, obtaining scene information and trajectory information of multiple types of traffic participants, and generating a data set; s2, generating scene feature maps according to scene information in the data set, and weighting and fusing the scene feature maps through the attention score to generate global scene information; s3, respectively extracting position information, speed information and direction information of various types of traffic participants in the data set, and constructing a multi-influence graph; s4, jointly embedding the processed multi-influence graph and global scene information into a space-time graph convolutional neural network, and performing coding processing through the space-time graph convolutional neural network to generate dynamic space-time features; and S5, decoding the dynamic spatio-temporal characteristics through the spatio-temporal transformation trajectory generation network to obtain future moment trajectory points of the traffic participants. According to the method, the dynamic interaction relationship among the multiple types of traffic participants can be more accurately captured in trajectory prediction of the multiple types of traffic participants, and the prediction precision and the real-time response capability in a complex traffic environment are improved.

The invention provides a self-adaptive preset time control method and system for a flexible mechanical arm, and relates to the field of control science and engineering.The self-adaptive preset time control method comprises the steps that a dynamic model of the flexible mechanical arm is built, and a nonlinear system state equation is deduced; constructing a time transformation function and a coordinate transformation function based on the system state equation; a time transformation function and a coordinate transformation function are utilized to construct an adaptive preset time controller, a dead zone compensator is connected to the output end of the controller in series, the ideal input control signal is compensated, and actual control input is obtained and acts on the flexible mechanical arm; a time transformation function is introduced into flexible mechanical arm control, a Lyapunov function and a self-adaptive estimation method are combined, an asymptotic tracking given tracking curve is finally output, global specified transient performance is guaranteed, performance indexes in the aspects of stable time and tracking precision can be pre-distributed offline according to task requirements, and the stability of the flexible mechanical arm is improved. And the method does not depend on an initial state and any design parameters.

In one embodiment, a system includes a peripheral device, which includes an interface to receive from a virtual machine (VM) running on a host device, over a communication data bus, a request for timing data derived from a time measurement dialogue, the host device maintaining a master clock time, a hardware clock to maintain a peripheral device clock time, and processing circuitry to transform the master clock time to a frame of reference of the VM, and provide to the VM, over the communication data bus, the timing data based on the peripheral device clock time, and the master clock time transformed to the frame of reference of the VM.

The invention provides a kinematics equation linearization method of normalized time, which converts a time variable under an absolute scale into a relative scale, thereby facilitating derivation and numerical calculation of an optimal control problem. Converting free time into time with boundary conditions by using normalized time, and converting time serving as a differential term in the motion equation into a multiplication term, so as to realize transformation of the motion equation; and according to the motion equation after time normalization, the time after normalization is optimized, and equivalent solution of an optimal control problem is realized. Equivalent solution of an original optimal control problem is realized, and derivation and numerical calculation of the optimal control problem are facilitated.

The invention relates to the technical field of industrial process soft measurement and quality control, and discloses a paper quality prediction method based on multivariate statistical latent variable fusion and space-time transformation, which comprises the following steps: acquiring space-time sequence data of a multi-source sensor in a papermaking process, constructing a space-time diagram structure reflecting a topological relation of equipment, and preprocessing. Then, multi-view latent variables are extracted through non-negative matrix factorization, independent component analysis and robust principal component analysis, attention fusion is conducted on the latent variables through an LV fusion module, and fusion latent variables are obtained; and inputting the fusion latent variable and original node data into a multi-scale convolution auto-encoder to obtain spatial feature embedding, and inputting the spatial feature embedding and the fusion latent variable into a space-time Transform module together to realize joint modeling of space correlation and time dependence. And finally, outputting a paper quality predicted value through a linear regression module. The method can achieve the accurate prediction of the paper quality under a high-dimensional and multi-noise working condition, and is suitable for online monitoring and modeling updating.

The invention discloses a physical training load regulation and control method and system based on self-adaptive physiological coupling, and the method comprises the steps: collecting an electrocardiosignal, a light volume pulse signal, a respiration signal, a surface electromyographic signal and a body surface temperature signal, and generating a multimode sequence with a time mark; self-adaptive time alignment is executed, a timestamp graph is constructed, clock drift estimation is carried out, segmented monotonic reversible time transformation is established, and a multimode sequence is mapped to a unified time axis; reconstructing the missing section and the artifact section, establishing a mask auto-encoder with physiological priori constraints, combining time domain consistency constraints and frequency domain consistency constraints, and outputting a continuous differentiable reconstructed sequence. According to the method, by introducing adaptive time alignment, cross-modal signal reconstruction and dual-time scale state modeling, coordinated recognition and dynamic load regulation and control of multi-source physiological signals are achieved, coupling analysis in the training process is more stable, and an individual model can be continuously and adaptively updated.

The invention provides an intelligent electric energy meter load recording method and device based on a Fibonacci algorithm. The method comprises the following steps: constructing a Fibonacci sequence; designing a record data storage structure; the compression time algorithm is used for converting the storage time of each record into relative seconds when the records are stored; according to the Fibonacci algorithm, the position of the record corresponding to the target time is found. By reasonably designing a record data storage structure, orderly storage of the load records of the intelligent electric energy meter can be realized, and meanwhile, the load records can be quickly searched according to the Fibonacci algorithm, so that the record searching efficiency is greatly improved.

The present invention provides a preset time control method and device for a flexible linkage manipulator, relating to the field of robotics. The method comprises: constructing a dynamic model of the flexible manipulator; performing a dual-time-scale model decomposition of the flexible manipulator dynamic model based on singular perturbation theory to obtain a slow-varying subsystem and a fast-varying subsystem; designing a preset time trajectory tracking controller based on the slow-varying subsystem using a composite learning algorithm based on a neural network and a disturbance observer, using a time transformation function and a state transformation function; designing a vibration suppression controller based on the fast-varying subsystem by constructing sliding mode variables; and obtaining control inputs for the flexible linkage manipulator based on the preset time trajectory tracking controller and the vibration suppression controller. This method can effectively suppress flexible vibrations and improve the robustness and adaptability of the system.

A method for calibrating phase nonlinearity of a digital-to-time converter is provided. The method includes generating a reference signal using a phase-locked loop (PLL) based on a control word. The reference signal has a frequency equal to the frequency of an output signal of the digital-to-time converter. Furthermore, the method includes measuring a temporal sequence of transitions of the output signal from a first signal level to a second signal level and a temporal sequence of transitions of the reference signal from the first signal level to the second signal level. The method also includes adjusting a first entry of a lookup table based on the measured temporal sequence.

To provide a method and device for signal-adaptive transform kernel switching in audio encoding.SOLUTION: A decoder 2 includes an adaptive spectral-time transformer 6 and an overlap-add processor 8. The adaptive spectral-time transformer 6 converts blocks of consecutive spectral values 4' into consecutive blocks 10 of time values via a frequency-time transformation, furthermore, depending on control information 12, switches between a first group of transformation kernels, comprising one or more transformation kernels having different symmetries on both sides of the kernel, and a second group of transformation kernels, comprising one or more transformation kernels having the same symmetry on both sides of the kernel. The overlap-add processor 8 generates decoded audio values 14 by overlapping and adding consecutive blocks of time values 10.SELECTED DRAWING: Figure 1

The invention relates to the technical field of intelligent control of a fully mechanized coal mining face of a coal mine, and discloses a large coal tracking processing method and device based on an image and a radar, and the method comprises the following steps: building a data package containing time synchronization information; resolving a real-time transformation matrix of a camera coordinate system relative to a mechanical arm base coordinate system based on the characteristics of a fixed calibration reference object in the data packet to realize dynamic external parameter calibration; a large coal target is recognized, point cloud depth information is combined, a real-time transformation matrix is called, and the real-time transformation matrix is mapped into static position coordinates under a mechanical arm base coordinate system; combining the speed of the scraper chain with a system response time window, and calculating predicted position coordinates of the large coal at the interception moment; and the motion track of the mechanical arm is planned, and the tail end executor is driven to execute processing operation on the target through closed-loop dynamic error correction. According to the method, the problems of coordinate system drifting and dynamic target tracking lag in a strong vibration environment are effectively solved, and accurate interception and efficient treatment of large coal are realized.

The application relates to the field of automatic control of intelligent agricultural equipment, and particularly discloses a constraint control method for an intelligent mower based on fixed-time convergence. First, a kinematic model and a heading subsystem of a differential steering intelligent mower are established; a fractional time conversion function is constructed to complete time dimension conversion scheduling of the heading subsystem; a nonlinear mapping function is used to convert the constrained heading system into an unconstrained system; and finally, a nonlinear heading constraint controller based on the backstepping method is designed to realize fixed-time convergence. The application can guarantee that the heading angle converges to the expected value within a fixed time, and the constraint boundary is not exceeded throughout the whole process, thereby improving the response speed, control accuracy and operation safety of the heading control of the intelligent mower.

The embodiment of the invention discloses a dialogue interaction method and terminal equipment, and the method comprises the steps: inputting request information inputted by a user into a slot size model, and outputting slot position information of the current round; under the condition that the slot position information of the round comprises time information, if the time information is fuzzy semantic information, converting the time for receiving the request information into preset format time; if the time information is not the fuzzy semantic information, converting the time information into preset format time; updating the time information in the slot position information of the current round; and inputting the request information and the updated slot position information to a reply generation model to generate reply information. According to the embodiment of the invention, the time information in the request text is extracted only by using the slot extraction model, the fuzzy semantic judgment is independently carried out on the time information, and different judgment results are converted into different preset format time, so that the accuracy of time slot extraction can be improved, and the time slot extraction efficiency is improved. Therefore, the reply information generated based on the accurate time meets user requirements.

The application discloses an asymmetric S-curve transformation method and device, a terminal and a medium. The method comprises the following steps: acquiring current motion state data corresponding to a current S-curve, and determining an initial target speed based on system limit parameters corresponding to the current S-curve; calculating a key motion distance corresponding to the initial target speed based on the current motion state data and the initial target speed; processing the initial target speed based on the initial target speed and the key motion distance to obtain a target speed, and determining a target S-curve corresponding to the target speed based on the target speed. The application aims to realize real-time transformation of an asymmetric S-curve, and then realize real-time speed transformation at any moment of a motion process.

The invention relates to the technical field of clock generation, in particular to a high-performance clock generation method and device based on a flexible H tree. The method comprises the following steps: generating a reference clock signal by adopting a multi-channel phase-locked loop array, and carrying out dynamic phase calibration through a digital time converter to obtain a final reference clock signal; constructing a flexible configurable H-tree clock network structure, and forming a trunk and branch topological structure by adopting a high-drive buffer; the useful deviation of a clock path is adjusted in combination with a clock concurrency optimization strategy; environment parameters are collected, clock adjustment is carried out through the environment parameters, and clock signals meeting performance requirements are generated. Therefore, the problems of insufficient adaptive capacity to the environment, delay imbalance of part of paths, incapability of realizing sensing and real-time compensation, reduction of time sequence precision and the like due to the fact that the H-tree structure design is solidified and a dynamic adjustment mechanism is lacked in the prior art are solved, and the phase consistency of clock signals, the system time sequence margin and the energy efficiency ratio are remarkably improved.

The application discloses a vector multiplication circuit for prediction optimization, which comprises a digital time converter (DTC), a 1T1R memory array, a weighting circuit and an analog-digital converter; the digital time converter (DTC) is used for converting input data into a fully coded time signal, the 1T1R memory array is used for receiving time information obtained after conversion by the DTC and accumulating current; the weighting circuit is used for weighting the current; and the analog-digital converter is used for analog-digital conversion of the current signal to generate a digital output. This structure can effectively reduce the calculation delay of vector multiplication; hierarchical weighting can greatly reduce the area consumption of the weighting circuit; and the prediction output can reduce the response time between the output and the input, so that the output can be applied to subsequent calculation more quickly.

The invention discloses a method and system for solving time zone delay in a cross-border fund collection set, and the method comprises the steps: generating the optimal collection instruction triggering time of a transnational branch company through a working time intersection algorithm and a daylight saving time adaptive UTC time difference dynamic calculation rule, and carrying out the fund collection operation based on the optimal collection instruction triggering time. Collection delay caused by time zone dislocation can be avoided; meanwhile, data synchronization after collection is carried out by means of a dual-mode data synchronization mechanism and a time synchronization mechanism based on a UTC time difference dynamic calculation rule, the problem of flow stagnation caused by inconsistency of cross-time zone data can be eliminated, the time difference calculation rule is dynamically adjusted based on daylight saving time and non-daylight saving time, time conversion errors can be avoided, and the time conversion efficiency is improved. In addition, the cross-time-zone manual guarding is not needed, the risk of manual errors is avoided, and the labor cost is remarkably reduced.

Various aspects of the disclosure relate to automated conversion of time and / or date information from a first format to a second format and initiating computing functionality based on a successful conversion event. Mainframe computer hardware and software are provided for automatically converting differing time formats used across an enterprise computing network, automatically presenting times in multiple formats and / or translations of times across time zones for different regional computing systems of the enterprise computing network, and translating time formats based on an input and automatically pulling data records based on time zones of one or more of the involved computing systems and / or a location associated with the input source.

The present invention relates to the field of signal processing technology, and solves the technical problems in the prior art of poor filtering effect on mixed signals and low signal correction accuracy. In particular, it relates to a method for adjusting base station signals based on user access, the method comprising the following steps: S1, obtaining a source signal received by a base station, and preprocessing the source signal to obtain a preprocessed signal x(t); S2, performing time transformation on the preprocessed signal x(t) to obtain a time-varying signal SP(t, f), and obtaining an instantaneous frequency pi(t) according to a peak value of the distribution of the time-varying signal SP(t, f); the present invention performs secondary processing on the mixed signal, first filtering out the clutter, and then performing detailed filtering on the 5G signal, thereby reducing the influence of noise on the signal time-frequency diagram, improving the signal-to-noise ratio of the signal to be measured, and improving the instantaneous frequency estimation accuracy, and greatly improving the signal-to-noise ratio of the reconstructed signal time-frequency distribution.

This invention provides a time conversion circuit and chip based on a differential delay chain. The differential delay chain-based time conversion circuit includes: a coarse delay chain, a first delay chain, a first trigger chain, a high-order encoder counter, a first low-order encoder, and a decoder. The differential delay chain-based time conversion circuit and time measurement method of this invention, employing a differential delay chain system architecture and corresponding internal testing and calibration methods, significantly improves time measurement accuracy.

The invention discloses a neural network computing system and device, and relates to the technical field of neural networks, the neural network computing system comprises a digital time conversion module, a digital frequency conversion module and a phase accumulator, and the output end of the digital time conversion module and the output end of the digital frequency conversion module are connected with the input end of the phase accumulator; the digital time conversion module is used for compressing and converting sparse data in the received input data to obtain a corresponding time pulse signal and outputting the time pulse signal to the phase accumulator; the digital frequency conversion module is used for converting the received weight data into corresponding frequency signals and outputting the frequency signals to the phase accumulator; and the phase accumulator is used for carrying out multiply-accumulate calculation on the time pulse signal and the frequency signal based on the phase and outputting a calculation result. According to the method, the technical problems of high resource overhead and high energy consumption of a neural network calculation strategy aiming at sparse data at present are solved.

The embodiment of the application provides a video stream image optimization method and device, a dynamic blur kernel generation mechanism is innovatively designed, space-time decoupling and physical constraints are used, and data processing safety is ensured. A content-motion double-branch network is constructed, residual connection and space-time transformation are combined, and a reliable feature reconstruction system is established. A physical constraint modifier is introduced, adaptive fusion and rule correction are used, user privacy is protected, and high-quality video output is provided. The method effectively solves the deficiencies of traditional technologies in blur processing, feature decoupling and image optimization.

In various examples, a time conversion operation may be performed based at least on updating a first local clock of a component based at least on a reference clock of a system including the component. A difference between a current time of the first local clock and a current time of a second local clock of the component may be determined. A state of at least one of the reference clock, the first local clock, or the second local clock may be determined based at least on comparing the time difference to a previously determined difference between a time of the reference clock and a time of the second local clock.

The invention provides an electromechanical system reliability evaluation method based on symbolic entropy and random degradation modeling, which comprises the following steps: step 1, carrying out data normalization preprocessing on pressure data acquired by a sensor; step 2, performing symbolization processing on the normalized pressure signal, retaining the dynamic performance of periodicity and symmetry of a dynamic system, and reducing the independence of continuous samples; 3, selecting a vector length according to the pressure information data, and constructing a symbol matrix; 4, traversing the number of each symbol sequence in the symbol matrix, solving the probability of the symbol sequence, and solving the symbol entropy according to an information entropy formula; 5, based on the symbol entropy sequence data solved in the step 4, selecting a proper time transformation function according to a Wiener process method, and fitting a symbol entropy trend; and step 6, performing reliability evaluation according to the Wiener process reliability function and the probability density function. The method can provide solid theoretical basis and technical guarantee for long-term safe and stable operation of the electromechanical system.

The invention provides an eagle head section line and gradient measurement method based on space-time transformation. The method comprises the steps that the average wave velocity C of eagle between a first observation point and a second observation point in the eagle advancing direction is obtained; recording a tide level time sequence of the tidal bore from the first observation point to a midpoint M of the second observation point; based on the average wave velocity C and the M-point tide level time sequence, the time sequence is converted into spatial distribution, and tidal bore tide head section lines Z-X are generated; a tidal bore section line within the range from a tidal bore rising point to the highest point L of a tidal bore head is selected, a straight line is made with the rising point as the starting point, the slope of the straight line is adjusted to enable the upper area and the lower area defined by the straight line and the section line to be equal, and at the moment, the ratio of the intercept of the straight line on the longitudinal axis to L is the gradient. The scheme provided by the invention is not influenced by terrain, time and space, can obtain the section line and gradient of the tidal bore head with high precision only by using a small number of pointing equipment, and can be applied to the aspects of embankment consolidation, river maintenance, tidal bore protection and the like.

The application relates to the field of automatic control of intelligent agricultural equipment, and particularly discloses a constraint control method for an intelligent mower based on fixed-time convergence. First, a kinematic model and a heading subsystem of a differential steering intelligent mower are established; a fractional time conversion function is constructed to complete time dimension conversion scheduling of the heading subsystem; a nonlinear mapping function is used to convert the constrained heading system into an unconstrained system; and finally, a nonlinear heading constraint controller based on the backstepping method is designed to realize fixed-time convergence. The application can guarantee that the heading angle converges to the expected value within a fixed time, and the constraint boundary is not exceeded throughout the whole process, thereby improving the response speed, control accuracy and operation safety of the heading control of the intelligent mower.

Systems, devices, software, and methods of the present invention provide for homomorphically encrypted (HE) and other data represented as polynomials of degree K-1 to be transformed in 0(K*log (K)) time into ‘unique-spiral’ representations in which both linear-time (0(K)) addition and linear-time multiplication are supported without requiring an intervening transformation. This capability has never previously been available and enables very significant efficiency improvements, i.e., reduced runtimes, for applications such as Fully Homomorphic Encryption (FHE), Post-Quantum Cryptography (PQC) and Artificial Intelligence (AI). Other efficient operations, such as polynomial division, raising to a power, integration, differentiation and parameter-shifting are also possible using the unique-spiral representations. New methods are introduced based on the unique-spiral representation that have applications to efficient polynomial composition, inversion, and other important topics.

The invention provides a time conversion circuit based on a differential delay chain and a chip. The time conversion circuit based on the differential delay chain comprises a coarse delay chain, a first delay chain, a first trigger chain, a high-order encoding counter, a first low-order encoder and a decoder. According to the time conversion circuit and the chip based on the differential delay chain, a differential delay chain system architecture is adopted, and a corresponding internal test and calibration method is matched, so that the time measurement precision is greatly improved.