67 results about "Signal mapping" patented technology

Disclosed are methods, systems, and computer-readable medium to perform operations including: generating a mapping pattern that comprises a length-4 frequency division orthogonal cover code (FD-OCC4), the mapping pattern for mapping demodulation reference signals (DMRS) in frequency to a plurality of resource elements in at least one orthogonal frequency-division multiplexing (OFDM) symbol, wherein the DMRS are associated with a plurality of DMRS ports; mapping, using the FD-OCC4, the DMRS to the plurality of resource elements in the at least one OFDM symbol; and transmitting a transmission comprising the at least one OFDM symbol.

The embodiment of the present application relates to the technical field of vehicle intelligent diagnosis, and discloses a CAN signal intelligent analysis method and system, comprising the following steps: reading CAN messages and CAN protocols, and analyzing the CAN messages according to the CAN protocols, wherein the CAN protocols are used to define signal mapping and analysis basis; checking the analyzed CAN signals, including verifying whether the CAN signals meet the requirements of the CAN protocols and evaluating health degree indexes, recording various data in the signal checking process, and obtaining signal test results; reading a preset test report template, automatically matching, filling and abnormity marking the signal test results according to the test report template, and generating a test report; and generating a checking result report based on the health degree indexes and the test report and displaying the checking result report. The present application can realize automatic CAN signal analysis and multi-dimensional checking.

This invention discloses a sleep stage identification method, comprising: a multimodal data acquisition step; a preprocessing step, which normalizes the acquired physiological signals and segments them according to a set duration to obtain several original signal segments; a Williams RGB compression step, which maps the original signals to an RGB image to obtain a Williams RGB energy map; a feature extraction step, which inputs the Williams RGB energy map into a neural network model for feature extraction; and a comparison and classification step, which compares the feature values ​​with RGB standard thresholds to determine the corresponding sleep stage. This sleep stage identification method avoids directly processing the complex frequency domain features of physiological signals, thus reducing computational complexity. Three physiological signals within a certain time period only need to be represented by a single pixel in the image, achieving physiological signal compression and dimensionality reduction, further reducing computational load. This invention also effectively utilizes medical knowledge graphs to provide interpretable evidence for the sleep stage identification decision-making process.

The application discloses a kind of real-time detection method and system of food pollutant based on intelligent sensor, comprising: through the multimodal sensor array of deployment in food processing production line key station, sensor response signal is collected;Baseline response under the condition of no pollution is predicted by establishing dynamic baseline prediction model;Signal separation network based on variational decoupling autoencoder is constructed, residual signal is mapped to low-dimensional latent space by sharing encoder and is divided into baseline error subspace and pollutant signal subspace, respectively by two independent decoders reconstructing baseline prediction error signal and pollutant candidate signal;Multi-scale time-frequency transform is carried out to pollutant candidate signal to identify pollutant type and estimate concentration;Through distributed intelligent agent cooperation, pollution traceability and hierarchical early warning are carried out;Cross-scene adaptive calibration is realized using meta-learning framework.The application realizes the real-time decoupling of pollutant signal and matrix change signal in food processing process.

Techniques are described for configuring and indicating a mapping between one or more phase tracking reference signal (PTRS) ports and one or more demodulation reference signal (DMRS) ports. An example wireless communication method includes receiving, by a wireless device from a network node, an indication for a single-carrier physical uplink shared channel (PUSCH) transmission comprising at least one phase tracking reference signal (PTRS) port and at least two demodulation reference signal (DMRS) ports, and performing, based on the indication, the single-carrier PUSCH transmission.

A method, apparatus, device, and storage medium for compressing distributed acoustic wave sensing data are disclosed. The method includes: inputting the original beat frequency signal into a pre-trained encoder module, which directly outputs a low-dimensional compressed feature vector, thus achieving efficient compression of distributed acoustic wave sensing data. The encoder module, through end-to-end training, learns how to map the high-dimensional original signal into a low-dimensional feature vector, preserving the key physical features of the signal in the process. Compared to traditional fixed downsampling or threshold compression, this application can adapt to the dynamic characteristics of the signal, effectively maintaining signal fidelity while compressing the data volume, thereby reducing the burden of subsequent storage, transmission, and computational processing.

The application provides a pilot pattern design method and device for a wireless ad hoc network, a terminal and a medium. The method comprises the following steps: S100, a second communication node generates a pilot pattern switching request signal according to channel quality information of a communication link, and sends the pilot pattern switching request signal to a first communication node; S200, after receiving the pilot pattern switching request signal, the first communication node sends a request acknowledgement response signal to the second communication node, and maps a new pilot pattern based on the request acknowledgement response signal, wherein a time domain position of the new pilot pattern remains unchanged, and a frequency domain starting offset is calculated through a control word in the request acknowledgement response signal. The application provides a plurality of variable pilot patterns for different channel environments of the wireless ad hoc network, and realizes dynamic switching through a two-way negotiation mechanism between a sending end and a receiving end, thereby significantly improving the adaptability of the wireless ad hoc network system.

The application provides a CPU post-silicon verification system and method, and relates to the technical field of post-silicon verification. The CPU post-silicon verification system comprises an editable CPU simulation component, an interposer, a socket and a verification platform, and the editable CPU simulation component, the interposer, the socket and the verification platform are electrically connected in sequence; wherein the interposer is used for mapping the signals of the editable CPU simulation component into preset CPU pin definitions; the editable CPU simulation component is used for performing read-write operations on the verification platform, and when the read-write operations are successful, it is determined that the verification platform is in a non-fault state. The CPU post-silicon verification system and method provided by the application have the advantage that the principle of the verification platform can be verified.

This invention relates to the field of biodiversity monitoring technology and discloses a monitoring and alarm device for rare and endangered aquatic organisms based on environmental DNA. The device includes a sampling and enrichment unit, a nucleic acid in-situ extraction and purification unit, a isothermal fluorescence detection unit, an environmental factor monitoring unit, a main control and data transmission unit, a power supply and protection unit, and a remote alarm and control platform. The main control and data transmission unit obtains the pressure change rate based on the digital pressure signal output by the microcomputer-controlled pressure sensor, extracts the high-precision peristaltic pump operating time parameter to calculate the actual filtration volume, and performs a division operation to obtain the environmental DNA calibration concentration. It then calculates the dynamic transmission power value by combining the network signal strength indicator value and transmits the complete communication data packet. The remote alarm and control platform obtains a risk index based on the environmental DNA calibration concentration, maps the spatial coordinate signal to an electronic map module to generate coordinate nodes, and displays the risk index and digital environmental parameters in association.

This application relates to a high-fidelity real-time rendering method, apparatus, device, and storage medium for dynamic digital humans. It includes receiving multimodal driving signals, mapping them to expression and pose parameters, inputting a parameterized human model to generate standard spatial geometry and skinning weights, and constructing a three-dimensional Gaussian sputtering field to deform to the target pose to obtain dynamic geometric data; arranging sparse virtual cameras in the target pose space, and simultaneously rendering and generating a sparse reference view set containing color and depth within a single rendering call; determining dense virtual viewpoints based on the display device's viewpoint parameters, and generating depth range textures for each dense viewpoint through downsampling depth reprojection and point sputtering techniques; determining ray step intervals using the depth range textures, sampling along the rays and fusing signed distance values ​​truncated from multiple viewpoints to generate surface position textures; projecting the surface positions onto sparse view sampled colors, fusing to generate a dense view color image, and adapting it for output to different display devices.

The application relates to the field of communication, in particular to a communication method and a communication device. Multi-user multiplexing can improve system capacity. In some cases, a plurality of OCC scrambling signals used by multi-user multiplexing correspond to different error-resistant scrambling sequences, which can cause the phases of the plurality of OCC scrambling signals to be discontinuous. In the application, a third time unit is located at adjacent time domain positions, which ensures that the plurality of OCC scrambling signals are mapped at adjacent time domain positions. In this way, the plurality of OCC scrambling signals are scrambled by using the same error-resistant scrambling value, and the phase continuity is maintained. The number of the plurality of OCC scrambling signals is greater than or equal to the number of users in a multi-user multiplexing scenario when the third time unit is greater than or equal to the length of the OCC scrambling sequence. Therefore, the application can improve the signal decoding performance in a multi-user multiplexing scenario.

The application discloses a kind of asynchronous brain-computer interface switch control methods based on periodic motor imagery task, it is related to automatic control field, method includes the following steps: user operation, when needing to trigger brain-computer interface switch, user executes periodic motor imagery task, and periodic variation brain electric signal is generated;Non-invasive scalp EEG data acquisition and pretreatment;Extracting EEG signal online feature;Characteristic signal is mapped as virtual force;Virtual force is applied to virtual dynamics system to drive virtual dynamics system state change and oscillation;According to virtual dynamics system state, brain-computer interface switch trigger control;The state of virtual dynamics system is fed back to user, and user completes periodic motor imagery task according to the rhythm and period of virtual dynamics system.The application constructs a new switch trigger mode, improves the reliability of switch control, realizes the switch reliable control to external equipment etc., improves the practicability of brain-computer interface system.

The application provides a direction of arrival (DOA) estimation method for a distributed sensor array based on a graph neural network, comprising the following steps: step 1, constructing a signal model of a distributed sensor array containing more than two sub-arrays; step 2, mapping array receiving signals into graph signals, and respectively constructing local and global graph structures and adjacency matrices; and step 3, after data preprocessing and label setting, building a network containing local and global GCN and determining a loss function. The method can effectively extract the correlation between array elements, has better robustness in a complex environment, and can more accurately perform DOA estimation.

This invention provides a dynamically reconfigurable plug-in capacitor array (PUF) and electronic device resistant to machine learning attacks, belonging to the field of integrated circuit hardware security. It includes: a reconfigurable sub-capacitor array and an amplifier connected to the reconfigurable sub-capacitor array; the reconfigurable sub-capacitor array includes multiple sub-capacitor units cascaded along the signal transmission direction, with the multiple sub-capacitor units connected in parallel to the same pair of differential busbars; the multiple sub-capacitor units are used to select a target capacitor from the multiple capacitors based on the input signal and connect it to the target node of two differential nodes on the same pair of differential busbars, so as to map the challenge signal into an equivalent capacitance difference signal between the two differential nodes; the amplifier is used to amplify and judge the equivalent capacitance difference signal and output a digital response signal. This invention can solve the problem of disrupting the fixed mapping relationship between challenge and response in a strong PUF without significantly increasing hardware overhead, thereby effectively improving its resistance to machine learning modeling attacks.

This invention relates to the field of flow measurement and industrial process control technology, specifically to a gas ultrasonic flow meter and its measurement method; it includes a measurement pipe section, signal acquisition, phase space reconstruction, symplectic geometric analysis, and adaptive solution modules; the system acquires the original acoustic time-series signal and maps it into a high-dimensional state trajectory matrix; its core is to use symplectic geometric transformation to extract dynamic invariants such as the maximum Lyapunov exponent, determine the flow field distribution correction coefficient, and compensate the basic flow velocity to generate a standard flow rate; this invention transforms a complex inverse fluid mechanics problem into a geometric topology feature extraction problem, eliminating the need for massive model training, significantly reducing computational power consumption, and solving the computational deadlock problem.

The present application relates to the field of communications, and specifically to a communication method and a communication apparatus. Multi-user multiplexing can increase system capacity, and in some cases, different error-resilient scrambling sequences corresponding to a plurality of OCC scrambled signals used in multi-user multiplexing will cause phase discontinuity of the plurality of OCC scrambled signals. In the application, (I) [equation 1] third time units are located at adjacent time domain positions to ensure that the plurality of OCC scrambled signals are mapped to adjacent time domain positions, such that the plurality of OCC scrambled signals will be scrambled by the same error-resilient scrambling value, thereby keeping phase continuity; and (II) [equation 1] is greater than or equal to the length of an OCC scrambling sequence, thereby ensuring that the number of the plurality of OCC scrambled signals is greater than or equal to the number of users in a multi-user multiplexing scenario. Therefore, the present application can improve signal decoding performance in multi-user multiplexing scenarios.

This application relates to an EEG signal transmission device and method based on event-driven backscattering. The device includes a neural signal input unit, an event triggering unit, an impedance modulation unit, and an antenna unit. The neural signal input unit acquires and outputs continuous analog EEG signals. The event triggering unit performs time integration on the continuous analog EEG signals and executes threshold decision to generate event pulses characterizing EEG events. The impedance modulation unit switches the load impedance state under the control of the event pulses. The antenna unit generates backscattered signals that change with the load impedance state switching under the action of an external radio frequency excitation signal. This application maps continuous neural electrical signals to event pulses and controls the load impedance switching in an event-driven manner, so that the antenna only participates in modulation when an event occurs. This achieves wireless transmission of neural information without analog-to-digital conversion and complex digital processing, significantly reducing the average power consumption of the system.

This invention relates to the field of power engineering cost control technology, specifically to an intelligent cost deviation control method for power plant renovation projects oriented towards a cloud platform. The method includes: establishing a cost monitoring process on an industrial cloud platform encompassing deviation detection, impact tracing, and control decision-making; identifying the initiation point and propagation path of cost deviations during the deviation detection stage; integrating the transmission relationship of project sub-items deviations with external market data flow disturbance signals during the impact tracing stage to map the multi-level impact chain of cost deviations; and analyzing the contribution weight and control sensitivity of deviations at each level during the control decision-making stage to generate a differentiated pre-control instruction set, collecting the cost flow response trajectory after instruction execution, iteratively correcting instructions based on their matching degree with the expected control trajectory, and updating the control strategy online. This method can fully present the deviation attribution logic, adapt control instructions to the characteristics of sub-items, achieve closed-loop intelligent control of cost deviations, and enhance the dynamic adaptive optimization capability of the control process.

This invention belongs to the field of rotating machinery fault diagnosis and discloses a fault diagnosis working condition domain generalization method and system based on working condition-independent feature representation. The method includes collecting vibration signals and corresponding working condition information of the target equipment under multiple working conditions in both normal and fault states; cutting the vibration signals into segments of preset length; mapping the working condition information into working condition vectors of the same length as the vibration signal segments; generating modulation parameters using a learnable multilayer perceptron through the working condition vectors; adjusting the vibration signals and their intermediate features step-by-step according to time steps; mapping the vibration signals to a working condition-independent feature representation space; classifying faults based on the mapped feature representations; and outputting fault diagnosis results. This invention, by embedding working condition information into a learnable model, guides the vibration signals to a normalized feature space independent of working condition changes, thereby achieving adaptation to unseen vibration signals under new working conditions and solving the cross-working-condition generalization problem.

This invention discloses a method and system for distribution network fault identification based on adaptive visual graphs and multi-source fusion. The method includes the following steps: S1: Acquire multi-source electrical analog data of the distribution network and preprocess it to obtain preprocessed multi-source signals; S2: Dynamically weight and fuse the preprocessed multi-source signals using a correlation variance contribution algorithm to obtain a fused signal; S3: Map the fused signal into a graph structure using an adaptive convergent visual graph algorithm; S4: Input the graph structure into a pre-constructed graph neural network model to obtain a global graph feature vector; S5: Input the global graph feature vector into a fully connected layer and output the fault probability distribution through a Softmax classifier. This invention constructs a feature space that can objectively characterize the essential differences between normal operating conditions and fault states in terms of physical correlation and topological structure, thereby achieving accurate identification of known faults and effective identification and elimination of unknown benign disturbances.

The present application relates to the technical field of power equipment, and more particularly to a high-voltage cable fault diagnosis method and system. The present application collects discharge data in the discharge process of the high-voltage cable to be detected, analyzes the fault trend data of the high-voltage cable in the target interval, and obtains a trend prediction waveform. Through the historical discharge data of the high-voltage cable to be detected, a reference fault-sample waveform signal mapping library is constructed, at least one reference fault is selected from the reference fault-sample waveform signal mapping library to form a fault combination, and the sample waveform signals corresponding to each reference fault in the fault combination are superimposed to obtain a sample comprehensive signal corresponding to the fault combination. Based on the sample comprehensive signal and the corresponding fault combination, the potential fault of the high-voltage cable and the time point when the fault is likely to occur are predicted. The present application can timely investigate the possible fault before the fault occurs and perform targeted advance processing.

The application discloses a kind of heart sound abnormality detection method and system based on earphone, belong to signal processing technical field.The method includes: obtaining the earphone microphone collected ear sound signal;Based on the physical information neural network constructed in advance, the ear sound signal is calculated inversely;Based on the constructed neural network, the mapping of inverse signal and real heart sound label is completed, and the reconstructed heart sound chart is obtained;Based on the reconstructed heart sound chart, abnormality detection identification is carried out;Physical information neural network includes source pulse wave inversion network HemoNet and source heart sound inversion network CardiNet;HemoNet is obtained in ear drum at arterial pulse pressure wave by ear sound signal inversion, and source pulse wave is obtained at heart;CardiNet is inverted into source heart sound signal at heart by heart sound collected in thoracic cavity;MappingNet generates heart sound signal by source pulse wave signal mapping, and obtains reconstructed heart sound chart.Improve the physical consistency and accuracy of reconstructed signal, realize accurate inversion source pulse wave signal and heart sound reconstruction, improve the convenience and accuracy of heart rate monitoring.

A method for detecting a static object using a radar sensor of a roadside unit includes scanning, using the radar sensor of the roadside unit, a surrounding environment to receive a radar reflection signal, and identifying a dynamic object in the surrounding environment based on the received radar reflection signal. The method further includes mapping the radar reflection signal to a preestablished grid map of the surrounding environment, and detecting, according to a change in a mapping state of the radar reflection signal in the preestablished grid map over time, the static object into which the dynamic object has changed.

Systems and methods for enhanced phase tracking reference signal (PTRS) to demodulation reference signal (DMRS) mapping for three transmit (TX) user equipment (UE) are provided. In some embodiments, a method performed by a UE includes configuring two PTRSs for a three TX chain UE, and determining a PTRS to DMRS association for the UE. In this way, by introducing an overhead efficient and flexible "PTRS to UL layer" mapping, for UL transmissions that need to track phase noise, overhead signaling can be reduced, or PTRS to layer mapping flexibility can be increased, which will improve phase tracking performance.

The application discloses a minimum harmonic optimization overmodulation method of a permanent magnet synchronous motor, and comprises the following steps: S1, a mathematical model of a double three-phase permanent magnet synchronous motor is established, and a deadbeat prediction control model is designed; motor winding variable signals are mapped, and a discretization model of the double three-phase permanent magnet synchronous motor is established; a deadbeat prediction control model of the system is constructed, and a state expansion observer is introduced to estimate and compensate harmonic currents; S2, overmodulation optimization control based on a gradient projection algorithm; a cost function taking the error between a reference modulation signal and a feasible modulation signal as an objective is constructed, and is converted into a quadratic programming problem containing linear equation constraints and boundary constraints; an optimal duty cycle is solved by online iteration through the gradient projection algorithm, the collaborative optimization of fundamental wave voltage synthesis and harmonic voltage minimization is realized, and the utilization rate of a direct current bus voltage and the dynamic performance of the system are improved. The modulation strategy has excellent steady-state performance and dynamic response capability under different working conditions.

This application relates to the field of automation control technology, and in particular to a constant speed control method, device, system, and medium for an EEG feedback track vehicle. It involves receiving EEG focus signals and mapping these signals to a target motor speed; acquiring the real-time motor speed; employing PID control with feedforward compensation; generating PWM drive commands based on the real-time and target motor speeds; and controlling the motor to operate at a constant speed according to the target speed. This application solves the problem that changes in track resistance cause the vehicle speed to not accurately reflect EEG focus. Furthermore, this application incorporates a dual-power supply and automatic charging mechanism to freeze the control state and maintain communication during the moment of derailment and power loss; upon return to track, the frozen data is read to achieve smooth start-up and constant speed recovery, completely resolving the data loss and reconnection problems caused by derailment.

A base station system of the present disclosure applies a first resource mapping to a plurality of signals to map the plurality of signals to a first physical resource or a logical resource and generate a first mapped signal. The base station system performs a Fourier transform on the first mapped signal to generate a first transformed signal. The base station system applies a second resource mapping to the first transformed signal to map the first transformed signal to a second physical resource and generate a second mapped signal. The base station system performs an inverse Fourier transform on the second mapped signal to generate a second transformed signal. The base station system generates a downlink signal to which a single-carrier modulation scheme is applied from the second transformed signal.

This invention discloses a method and system for low-temperature control of acid rain samples based on active temperature control and semiconductor refrigeration, belonging to the field of acid rain sample low-temperature control technology. The method includes the following steps: sample pretreatment and temperature control triggering, dynamic adjustment of PID control quantity and mapping of PWM signal, semiconductor refrigeration mode driving and execution, and feedback parameter updating and closed-loop control cycle. This invention pretreatment and packaging of acid rain samples into standard samples, collecting temperature data to determine whether temperature control is needed; during temperature control, according to a preset cycle, the PID control quantity is adjusted based on the temperature deviation and mapped to a PWM signal to drive the semiconductor refrigeration module to execute the corresponding mode, collecting and updating the temperature and updating the feedback variables, forming a negative feedback temperature control loop through cyclic execution. This improves the reliability of low-temperature control of acid rain samples and solves the problem of low reliability in existing technologies.

This invention discloses a flexible electrode array, system, and manufacturing method for closed-loop neural modulation, relating to the fields of neural engineering, medical devices, and biosensor technologies. The flexible electrode array includes a flexible biocompatible substrate, a recording electrode array, and a stimulating electrode array. The recording sites are arranged in a matrix, and the stimulating sites are coplanar with the recording sites, located between or within rows of the recording electrode array, achieving a spatially co-located layout of recording and stimulation. The system also includes an external control unit for receiving neural signals acquired by the recording electrode array and dynamically adjusting the stimulation parameters applied to the stimulating electrode array based on the neural signals. This application improves biocompatibility, achieves high-resolution signal mapping, and enables efficient closed-loop neural modulation by shortening the spatiotemporal distance between stimulation and monitoring.