49 results about "Signal optimization" patented technology

A method is provided that includes receiving a configuration associated with monitoring of a physical control channel for a paging downlink control information (DCI). The configuration indicates at least one first monitoring occasion for each paging occasion of a number of paging occasions for a paging frame. And the at least one first monitoring occasion for at least one of the number of paging occasions is indicated by a time location relative to a first monitoring occasion for a reference paging occasion. The method also includes monitoring the at least one first monitoring occasion for one of the number of paging occasions associated with a user equipment (UE) based on the configuration, where the at least one first monitoring occasion is monitored for the paging DCI.

The application relates to the technical field of electromagnetic measurement, and discloses a signal optimization processing method and system for electromagnetic frequency sensitive material, the method comprising the following steps: performing scanning measurement on an original response signal of the electromagnetic frequency sensitive material under frequency domain excitation to obtain amplitude-frequency characteristic parameters and phase-frequency characteristic parameters; performing frequency domain conversion analysis on the amplitude-frequency characteristic parameters and the phase-frequency characteristic parameters to obtain a complex spectrum change gradient; identifying the sensitivity response of dynamic frequency of the electromagnetic frequency sensitive material, and merging the identified frequency point groups into characteristic frequency subbands; mapping the characteristic frequency subbands into a frequency optimization strategy library to obtain an optimization strategy; performing compensation correction on the original response signal to obtain an optimized signal; performing signal-to-noise ratio evaluation on the optimized signal, and iteratively optimizing the frequency optimization strategy library according to the evaluation result, so that the signal optimization processing effect of the electromagnetic frequency sensitive material is realized; and the application can improve the signal optimization processing efficiency of the electromagnetic frequency sensitive material.

The application discloses a network signal optimization method and device, electronic equipment and a storage medium, and belongs to the technical field of communication. The method comprises the following steps: in the case that it is detected that the electronic equipment enters a preset scene, collecting scene sensing data of the electronic equipment in the preset scene; determining a corresponding first learning model according to the scene sensing data; in the case that the network signal quality of the electronic equipment meets a preset condition, outputting a network optimization strategy corresponding to the scene sensing data through the first learning model; and controlling the electronic equipment to execute the network optimization strategy.

Methods and apparatuses for automatic analysis and optimization of an audio signal are described herein. An example method may comprise receiving, by an audio signal optimizer, a first indication to perform an audio signal optimization, receiving an audio signal from an input device, recording a sample of the audio signal, analyzing the sample of the audio signal for at least one audio parameter, and performing, based on an analysis of the sample of the audio signal, the audio signal optimization of the audio signal, wherein the audio signal optimization comprises a configuration of a gain level of the audio signal.

The present application relates to the technical field of probe card signal optimization, in particular to a high-frequency probe card signal optimization method based on dynamic impedance matching and related devices. The method steps include: obtaining real-time high-frequency signal reflection parameters of the probe card test channel to provide real-time detection basis for dynamic impedance matching. The present application relies on the real-time acquisition of the high-frequency signal reflection parameters of the probe card test channel to complete the quantitative tracing of the dynamic impedance deviation, and through the closed-loop feedback adjustment, the integrated adjustable impedance network of the driving probe is used to complete the real-time correction of the output impedance. From the root level of transmission line impedance matching, the present application breaks through the inherent limitation of the traditional static matching scheme which can only adapt to the nominal working condition, and can effectively offset the dynamic impedance mismatch introduced by the contact state difference, the probe structure micro-deformation, the device individual parasitic parameter dispersion and the nonlinear evolution of the parasitic parameters under high frequency in the actual test process, and solves the reflection residual problem that cannot be eliminated by static matching.

This invention discloses a method and system for predicting the trajectory of electric vehicles at signalized intersections, relating to the field of intelligent transportation technology. The method and system provided by this invention improve the accuracy and efficiency of electric vehicle trajectory prediction in complex intersection scenarios by utilizing Mamba to capture long-term temporal dependencies in signalized intersection videos and incorporating kinematic physical constraints using PINN. By constructing counterfactual scenarios of trajectory feature parameters for counterfactual inference prediction, the causal quantification of key factors affecting trajectory prediction results is achieved, enhancing model interpretability. Furthermore, Bayesian methods are used to perform uncertainty analysis on the Mamba-PINN fusion model, quantifying the uncertainty of trajectory prediction and improving model reliability. The optimized model exhibits strong adaptability and can provide decision-making basis and technical support for traffic signal optimization and intelligent transportation systems.

A device includes digital signal processors (DSPs) and analog crossbars in communication with the DSPs. The analog crossbars are operable to dynamically adjust equalization settings based on real-time feedback from DSPs, physical media-dependent (PMD) devices, or environmental sensors. Equalization adjustments optimize signal quality by compensating for traffic conditions, environmental changes, or signal degradation. The crossbars support predictive equalization using machine learning algorithms to preemptively adjust signal properties, ensuring performance across dynamic network environments. Diagnostics and logging capabilities monitor and refine equalization performance, while auxiliary in-band channels provide low-power pathways to reduce energy consumption. These features enable efficient, high-speed data transmission with enhanced reliability and adaptability in modern networking systems.

The application relates to a transformer oil dissolved gas fault tracing method based on photoacoustic spectroscopy. Photoacoustic signals generated by dissolved gases in transformer oil are acquired, and multi-stage signal optimization processing is performed on interference spectra corresponding to the photoacoustic signals to obtain gas concentration data. The gas concentration data is input into an intelligent fault diagnosis model for processing, and a current fault diagnosis result is output. The intelligent fault diagnosis model is based on a mutual information method to screen an optimal feature subset, and based on the optimal feature subset, an improved grey wolf optimization algorithm is used to globally optimize hyperparameters of a support vector machine and then trained to obtain the intelligent fault diagnosis model. Time sequence change data of the gas concentration data is acquired, and in combination with the time sequence change data and the fault diagnosis result, a fault evolution trend is analyzed, and dynamic tracing and early warning are performed, so that the accuracy of transformer oil fault analysis and tracing is improved.

A method is provided that includes receiving a configuration associated with monitoring of a physical control channel for a paging downlink control information (DCI) within a paging frame. The configuration includes at least one parameter that indicates one or more applicable time locations as a subset of all time locations within the paging frame. The method also includes monitoring a first monitoring occasion for a paging occasion associated with a user equipment (UE) based on the configuration, where the first monitoring occasion is monitored for the paging DCI.

The application discloses an implementation method and system for self-evolution learning of an intelligent agent, and belongs to the technical field of intelligent agent reinforcement learning, large language models, memory and cognitive intelligence, and transfer learning; the method comprises the following steps: acquiring an environment state; inputting the environment state into a pre-trained strategy to output an optimal action and executing the action; after executing the action, a feedback signal is acquired; the feedback signal comprises an environment response and a task completion degree; and a new strategy is obtained by optimizing the strategy according to the feedback signal. The task performance of the application is continuously upgraded: the intelligent agent can be continuously optimized when facing long-range or repetitive tasks, and the intelligent agent will become more and more skilled in processing cross-platform complex tasks. The application reduces the research and application cost: the intelligent agent can reduce the dependence on manual work, can autonomously discover reinforcement learning rules, does not need to continuously manually annotate data, and relies on environment feedback for iterative optimization.

A method performed is provided that includes receiving a configuration associated with monitoring of a physical control channel for a paging downlink control information (DCI). The configuration indicates at least one first monitoring occasion for each paging occasion of a number of paging occasions for a paging frame. And the at least one first monitoring occasion for each paging occasion is indicated by a time location from a beginning of the paging frame, and for at least one of the number of paging occasions, based on applicable time locations as a subset of all time locations within the paging frame. The method also includes monitoring a first monitoring occasion for a paging occasion associated with a user equipment (UE) based on the configuration, where the first monitoring occasion is monitored for the paging DCI.

This invention discloses an atomic fluorescence spectrometer and an automated sample measurement system, belonging to the field of atomic fluorescence spectrometer technology. This invention effectively ensures stable instrument operation and efficient atomization reactions through a comprehensive self-checking mechanism combined with adaptive matching of different analyte types and detection modes. Simultaneously, through precise cup positioning, automatic sample sequence configuration, and orderly scheduling of the detection process, coupled with reference light baseline correction, multi-level blank measurement, and standard curve fitting to establish quantitative correlations, it fully covers the entire detection chain from automatic sample introduction, signal acquisition, signal optimization processing to concentration calculation and correction, effectively improving the accuracy and repeatability of sample measurement results. It achieves fully automated operation of the entire process—including power-on self-check, parameter matching, automatic measurement, data calibration, result calculation, and standardized report generation—without extensive manual intervention, adapting to the needs of multi-element, multi-wavelength simultaneous detection and improving the intelligence, standardization, and automation level of atomic fluorescence detection.

The application provides a signal testing and optimizing device and method, the signal testing and optimizing device comprises a signal distribution module, a signal optimizing module and a signal testing module, the signal distribution module is used for obtaining a first signal, cloning the first signal to obtain a second signal, transmitting the first signal to the signal testing module, and transmitting the second signal to the signal optimizing module, the signal optimizing module is used for optimizing the second signal, obtaining optimization data of the second signal, and transmitting the second signal after optimization to the signal testing module, and the signal testing module is used for testing the first signal and the second signal to obtain a test result, so that the first signal can be optimized according to the optimization data of the second signal in the case that the test result of the second signal meets the requirements but the test result of the first signal does not meet the requirements, and then the optimization data can be obtained at the same time of obtaining the test result, and the optimization efficiency of the signal can be improved.

A live-line verification device and method for high-voltage instrument transformers are disclosed. The device includes a signal acquisition module, a signal processing module, a data transmission module, a control module, and a display module, all electrically connected in sequence. The signal acquisition module employs a voltage divider voltage sensor and a Rogowski coil current sensor to accurately acquire secondary-side voltage and current signals. The signal processing module uses second-order RC low-pass filtering, adjustable-gain instrument amplification, and high-sampling-rate analog-to-digital conversion to achieve interference filtering and signal optimization. The control module incorporates an error calculation algorithm and a Fourier harmonic analysis algorithm to accurately calculate the ratio difference and angle difference. The method, based on the aforementioned device, achieves live-line verification of high-voltage instrument transformers through standardized connection, acquisition, processing, calculation, and display steps.

This invention relates to the field of telemetry technology, proposing a telemetry system and method suitable for close-range testing of high-speed rotating components. The telemetry system includes a rotating transmitter and a fixed receiver. The rotating transmitter includes a target rotating component, a signal acquisition and processing module, and a transmitting antenna. The signal acquisition and processing module acquires and processes test parameters of the target rotating component and radiates the processed test data outward through the transmitting antenna. The fixed receiver includes a receiving antenna, a signal optimization module, and a data processing module. The receiving antenna receives the test data, the signal optimization module performs adaptive diversity synthesis and blind equalization processing on the test data to obtain processed data, and the data processing module outputs corresponding telemetry data based on the processed data. This invention enables high bit rate and low bit error rate transmission, meeting the high-precision, high-speed rotation testing requirements of aerospace, industrial equipment, and other fields.

The application provides a black box confrontation evaluation method based on strategy driving and frequency-space residual remodeling, belongs to the technical field of confrontation attack, selects neural networks with multiple different network architectures to construct a heterogeneous agent model matrix, obtains a source detection tensor and a calibrated true value and extracts a benchmark response gradient; the current evolution state tensor, the benchmark response gradient, the frequency domain amplitude spectrum feature and the iteration progress scalar are spliced to form a multi-dimensional joint state vector; a frequency domain attenuation barrier and a space domain remodeling tensor are generated through a strategy decision network, the frequency domain filtering denoising and the space domain nonlinear residual remodeling are sequentially performed on the benchmark response gradient, and the evolution state tensor is updated in the residual fusion remodeling direction. After the multi-round iteration and the composite feedback signal optimization strategy network parameter, the tensor with the optimal comprehensive threat effectiveness is selected as the confrontation evaluation carrier output. The application can effectively strip high-frequency overfitting noise, solve the cross-model response offset problem, and improve the cross-model migration and evaluation stability of the black box confrontation evaluation carrier.

This invention discloses a reconfigurable metasurface beamforming method based on the branch-and-bound method. The method includes: constructing a fundamental beamforming problem and calculating its initial solution; progressively optimizing the phase distribution of the metasurface based on the search and branching steps of the branch-and-bound method; discarding non-optimal branches using a pruning strategy to reduce computational complexity; and obtaining the beamforming result based on the final discrete phase of each element. This invention is the first to introduce the branch-and-bound method into metasurface beamforming, enabling rapid and accurate generation of the digitally encoded sequence corresponding to the target beam. Compared with traditional analytical methods, this invention has advantages such as high computational efficiency and ease of operation, and is suitable for high-precision beam control and signal optimization systems in 6G wireless communication scenarios.

This application discloses a method and apparatus for dynamic optimization of intersection signals based on vehicle-road cooperation, relating to the field of traffic signal optimization. The method includes: collecting road condition data, analyzing the congestion index of each phase, determining a basic congestion index by combining historical road risk status data and phase demand data, and judging whether optimization is necessary; secondly, when optimization is required, filtering effective historical traffic flow data with a loss time target, statistically analyzing the signal cycle duration according to the total traffic flow ratio interval, and then allocating the signal duration according to the proportion of each phase's congestion index to generate a basic signal control scheme; finally, analyzing the optimized road data, comparing the current optimization improvement rate, and optimizing the control scheme if it does not meet the target. This invention integrates historical and real-time data, relying on vehicle-road cooperation to achieve dynamic and precise signal control, improving intersection traffic efficiency and reducing vehicle delays.

This invention discloses a closed-loop control system based on electroencephalogram (EEG) signals, comprising a sound processing module, an external closed-loop control module, and an internal implanted stimulation module. The sound processing module is connected to both the internal implanted stimulation module and the external closed-loop control module. The sound processing module acquires sound signals and processes them according to preset processing and encoding strategies to output stimulation encoding parameters. The internal implanted stimulation module parses the stimulation encoding parameters and generates corresponding electrical stimulation pulses to apply to the patient. The external closed-loop control module acquires and processes the EEG signals generated after the patient receives the applied electrical stimulation pulses, and optimizes at least one of the processing and encoding strategies based on the processed EEG signals. The system of this invention can optimize the processing and encoding strategies based on EEG signals to achieve more precise closed-loop control and provide patients with more accurate sound processing solutions.

This invention discloses a multi-machine signal transmission system and method for power distribution inspection. The system includes a multi-machine signal acquisition and preprocessing module, a dynamic spectrum allocation and multi-link transmission module, an edge relay node cluster, a secure encrypted transmission module, a collaborative scheduling and signal optimization module, and an emergency communication support module. The method achieves signal transmission through steps such as task initialization, signal acquisition and preprocessing, spectrum allocation and multi-link establishment, signal relay and secure transmission, dynamic optimization of transmission quality, emergency communication activation, and data sharing and processing. The technology is implemented by combining dynamic spectrum allocation, hierarchical relay, national cryptographic algorithm encryption, Ad Hoc self-organizing emergency network, and transmission and scheduling linkage optimization. This invention reduces signal interference during multi-machine operation, achieves wide-area signal coverage without dead zones, improves data transmission security and emergency transmission reliability, optimizes transmission efficiency, and meets the high-reliability and high-security multi-machine collaborative inspection requirements of power distribution networks.

The application provides a training method and processing method of a seismic sensor signal optimization model, and relates to the technical field of seismic signal optimization. The training method comprises: obtaining a first feature alignment loss and a first detail modulation loss by forward conversion of a low-quality reference signal; obtaining a second feature alignment loss and a second detail modulation loss by reverse conversion of a high-quality reference signal; obtaining a first cycle consistency loss by reconstruction of the forward conversion result; obtaining a second cycle consistency loss by reconstruction of the reverse conversion result; obtaining a first adversarial loss by discriminating the forward conversion result, and obtaining a second adversarial loss by discriminating the reverse conversion result; weighting and combining all the losses obtained into a total loss function, and alternately optimizing and training the model based on the total loss function until convergence, to obtain a trained optimization model. Finally, a seismic sensor signal optimization model capable of effectively suppressing noise and maintaining effective wave components is obtained.

The application provides a kind of intersection traffic adaptive control optimization decision method and system based on electric police data, it is related to intersection traffic signal optimization field.First, based on electric police data, the influencing factors such as cycle flow, vehicle type, signal cycle and driving behavior are obtained by data integration.Second, the adaptive control effect expressed by traffic capacity is the dependent variable, and the above four traffic influencing factors are the independent variables to construct a multiple linear regression model for key factor analysis.Finally, according to the decision criteria and analysis results, the decision suggestions are given.The application introduces the evaluation method based on data analysis to evaluate the adaptive control effect to support the corresponding decision, and this data analysis and optimization method based on electric police data can help optimization personnel make different decisions for intersections with different characteristics, find out the key influencing factors of intersection congestion, and make targeted optimization, so as to improve the adaptive control effect of intersection.

This invention belongs to the field of stroke rehabilitation engineering technology, specifically relating to a cross-subject gesture recognition method for stroke patients based on a prototype network and high-density surface electromyography (HD-sEMG). The method includes subject screening and preparation, HD-sEMG signal acquisition, signal preprocessing, macro- and micro-feature extraction, feature dimensionality reduction and standardization, prototype network model construction, data augmentation and signal optimization, and model training and validation. This invention improves feature discriminativeness through macro- and micro-feature fusion; simplifies the Transformer encoder to achieve high-quality feature embedding; utilizes a multi-loss collaborative framework to achieve a dynamic balance between cross-domain generalization and classification discriminativeness; enhances the model's anti-interference ability under small sample conditions through physiological data augmentation and signal optimization; and requires only a very small number of patient calibration samples to achieve accurate gesture recognition, significantly reducing calibration costs in clinical applications. This provides a feasible solution for the clinical translation of intelligent rehabilitation robots and closed-loop rehabilitation systems, promoting the intelligent development of stroke rehabilitation.

The application relates to the technical field of wireless communication, and discloses a 5G wireless repeater signal expansion combination system, which comprises the following modules: a distributed repeater module for receiving and amplifying 5G signals from a base station; an intelligent signal processing module for monitoring signal quality in real time and optimizing signal processing; a dynamic resource management module for dynamically allocating frequency spectrum and power according to signal quality and user demand; a self-organizing network mechanism module for monitoring environmental changes and analyzing signal optimization processing strategies; and a user interface and feedback module for displaying real-time signal states. Through the technical scheme of combining the self-organizing network mechanism module and the dynamic resource management module, the application achieves the effect of real-time adaptation to network environment changes. This makes the system capable of quickly responding to user demand and environmental fluctuations, and solves the problem of unstable signal quality caused by network load changes.

The present application relates to new energy control technology field, specifically for a kind of far sea wind farm consistency frequency control method and device based on restraint signal optimization, method steps include: obtaining the power system parameter containing wind farm;The wind farm restraint consistency control topology is constructed, and wind farm restraint consistency frequency controller is set for each wind turbine generator, according to the state of wind turbine generator itself, adjacent unit state and restraint signal, the active power reference value of corresponding wind turbine generator is calculated to control the rotor kinetic energy release of wind turbine generator;Frequency security is considered, and the restraint control signal frequency modulation stage length optimization problem is constructed, and the optimization problem is solved, and the optimal restraint signal is obtained compared with prior art, the present application considers the wind speed distribution difference of offshore wind farm, realizes the frequency modulation state consistency of wind farm internal unit, effectively reduces frequency secondary drop, improves frequency support effect, and has important significance to the power system frequency security containing offshore wind farm.

Provided in the present application are an ultrasonic radar echo envelope optimization circuit and optimization method. The optimization circuit comprises an analog-to-digital conversion module, a signal demodulation module, an envelope signal optimization module and a controller. The analog-to-digital conversion module is used for converting an echo signal of a transducer from an analog signal into a digital signal. The signal demodulation module is used for generating an initial envelope signal on the basis of the echo signal that has been subjected to analog-to-digital conversion. The envelope signal optimization module is used for performing interference suppression on the initial envelope signal, so as to generate a target envelope signal. The controller is used for controlling an anti-interference coefficient of the envelope signal optimization module. The anti-interference coefficient is negatively correlated with the operating frequency of the transducer, positively correlated with the sampling frequency of the analog-to-digital conversion module, and positively correlated with a quality factor of a band-pass filter. The anti-interference coefficient can be dynamically adjusted on the basis of different combinations of the operating frequency of the transducer, the sampling frequency of the analog-to-digital conversion module and the quality factor of the band-pass filter, thereby improving the anti-interference capability of the target envelope signal.

A method for optimizing electric field strength measurement signals based on SSA-AKF includes the following steps: Step 1: Construct and obtain a target field mill electric field meter model; Step 2: Convert and amplify the output induced current of the field mill electric field meter through a signal conditioning circuit to obtain a stable and collectable voltage signal; Step 3: Suppress low-frequency disturbances and random noise in the voltage signal obtained in Step 2; Specifically, the Sparrow Search Algorithm (SSA) is used to optimize the key noise covariance parameters in the adaptive Kalman filter. SSA searches and iteratively updates the process noise covariance and measurement noise covariance parameters within a preset parameter range, using the filter estimation error as a fitness evaluation index to obtain the parameter combination that optimizes the filtering performance; The optimization results of SSA are used as the parameter initialization values ​​or periodically updated parameters for the adaptive Kalman filter, and are used in the subsequent filter recursion process, thereby providing a reasonable parameter configuration basis for the adaptive Kalman filter; Step 4: Based on the optimal parameters output by SSA, a state-space model with the electric field modulation signal as the state variable is constructed, and the adaptive Kalman filter (AKF) is used to recursively estimate the measurement signal.

The application provides a variable lane reorganization and main-pre-signal cooperative optimization method and system under an entrance construction scene, predicts the flow of each entrance and each turning direction in the future 1-3 signal periods based on a Transformer flow prediction model, forms a feedforward control input, can predict the flow change trend in advance, reserves sufficient adjustment time for upper optimization and emergency control, improves the foresight and predictability of the control strategy, calculates the total delay of the intersection under the conditions of no construction, construction lane occupation, variable lane and main-pre-signal optimization, sets the lane affected by the construction as a dynamic variable lane, constructs a double-layer cooperative optimization model, adopts a double-layer cooperative architecture of upper genetic algorithm optimization signal timing and lower particle swarm algorithm optimization variable lane and pre-signal timing, realizes dynamic matching of signal timing and lane function, and the intersection passing efficiency is obviously improved and the flow delay is greatly reduced.

The application discloses a radar communication integrated signal optimization method and belongs to the technical field of radar communication integration. The application constructs a multi-pulse OFDM integrated signal model, designs an ICI self-cancellation precoding matrix based on frequency offset and Doppler effect, and suppresses inter-subcarrier interference; meanwhile, an inter-pulse coherent communication sequence is designed by combining Gold sequences and coherent accumulation constraints, so that the multi-pulse phase coherence is ensured. The transmitting end loads the precoded communication information to OFDM subcarriers to generate an integrated signal; the receiving end first performs ICI compensation and coherent accumulation, and then completes detection and demodulation. The application can significantly reduce waveform sidelobes, improve ranging and speed measurement accuracy and weak target detection performance, is compatible with a traditional OFDM structure, and is suitable for high-speed motion scenes such as vehicle-mounted radars and airborne detection.