28results about How to "Reduce bandwidth requirements" patented technology

The invention discloses a centralized phased array beam control method and system based on an FPGA, and relates to the technical field of phased array beam control, and the method comprises the steps: carrying out the real-time iterative operation through an incremental adaptive correction kernel in a centralized control FPGA, and obtaining an amplitude-phase correction increment and a corresponding target effective frame number; performing increment differential coding on the amplitude-phase correction increment and the corresponding target effective frame number in a centralized control FPGA (Field Programmable Gate Array) to generate an increment differential beam control message; sending the increment difference beam control message to an array element FPGA (Field Programmable Gate Array) at the front end of an array, executing frame-level atom switching according to a target effective frame number, and fusing the amplitude-phase correction increment and a locally stored old beam control weight in the switching process to obtain a final array element beam control weight; generating a real-time beam control directional diagram based on the final array element beam control weight; the stability and convergence precision of beam control are improved, and the bandwidth requirement of a control link is reduced.

The invention provides a memristor neural network cloud edge collaboration method and a memristor neural network cloud edge collaboration system based on multi-mode sensing. The method belongs to the field of artificial intelligence multi-modal data processing. The method mainly comprises the following steps: distributing multi-modal data subjected to synchronous acquisition and time-space alignment to an FPGA (Field Programmable Gate Array) and a memristor array for parallel processing; splicing the processed multi-modal data in a channel dimension to generate a multi-channel fusion feature tensor; a memristor array is used for carrying out storage and calculation integrated calculation on the multi-channel fusion feature tensor, and an advanced feature map is output; receiving a differential update packet issued by the cloud, and selectively updating the weight in the memristor array according to the update packet; and carrying out in-situ fine tuning on partial weights in the memristor array based on locally acquired data. According to the method and the constructed system, the memristor array can be effectively compensated, the calculation precision is improved, and rapid self-adaption of a local scene and continuous and efficient iteration of global knowledge are achieved.

The invention discloses a multi-energy complementary power distribution control method, belongs to the technical field of electric power system control, and aims to solve the problems that an existing multi-energy system control method based on periodic instruction issuing is heavy in communication burden, response lags when sudden disturbance is dealt with in two scheduling intervals, and the power distribution efficiency is poor. And the operation economy and the dynamic stability are difficult to consider at the same time. The method comprises the steps that an upper-layer optimization controller generates virtual impedance potential field function parameters and key topological characteristics and issues the virtual impedance potential field function parameters and the key topological characteristics to a local controller; the local controller executes power control based on the potential field gradient and monitors the topological position of the operation point; when a topology crossing event is detected, an asynchronous event triggering signal is sent upwards, and an upper-layer controller is triggered to carry out aperiodic re-planning. According to the method, decoupling of economic optimization and dynamic control is realized, the robustness and the adaptive capacity of the system under disturbance are improved, meanwhile, the communication burden is reduced, and the method is suitable for a system containing a large amount of distributed energy.

A data quantization method and device, a computer readable storage medium and a chip, the data quantization method comprising: obtaining a data block to be quantized, dividing the data block to be quantized into one or more data groups to be quantized according to a preset grouping method; performing quantization calculation on each data group to be quantized according to a target quantization format, to obtain quantization data corresponding to data in each data group to be quantized and quantization metadata corresponding to each data group to be quantized, wherein the quantization metadata is used for dequantization of the quantization data; and storing the quantization metadata corresponding to the data block to be quantized and the quantization data as a continuous data structure.

The application provides a lightweight variable bit rate multi-view image compression method and system, and relates to the technical field of image compression. The method comprises: downsampling, feature extraction and feature scaling of a single-view image to obtain a latent representation corresponding to a target bit rate; quantization and lossless entropy coding of the latent representation to obtain a final compressed bit stream; subsequent lossless entropy decoding and inverse scaling to restore the latent representation; feature fusion and upsampling of the restored latent representations of different views to generate a reconstructed compressed image. The model comprises a main encoder, a feature scaling module, a quantization module, an autoregressive entropy model, an arithmetic encoder, an arithmetic decoder, a feature inverse scaling module and a decoder. The application can efficiently compress image data, reduce computational complexity and storage space occupation while preserving image details and quality, thereby providing faster speed and lower bandwidth requirement for image transmission and storage.

The application discloses a kind of adaptive optics real-time controller hardware architecture based on multi-core CPU and GPU.Shack-Hartmann wavefront sensor sub-aperture slope calculation, wavefront recovery and wavefront control are completed in parallel by multi-core CPU and GPU using the real-time controller hardware architecture.The application uses general multi-core CPU and GPU as computing platform, after receiving image data in multi-core CPU, part of sub-aperture image data is transmitted to GPU by PCIE bus using a CPU core, and wavefront calculation task of the part of sub-aperture is completed by GPU;At the same time, the remaining CPU core is used to complete the remaining sub-aperture wavefront calculation task in parallel, to reduce the purpose of real-time controller calculation delay.The application uses multi-core CPU and GPU in parallel to complete wavefront calculation task, to reduce the effect of adaptive optics real-time controller calculation delay, to meet the real-time requirement of adaptive optics system to real-time controller, especially suitable for next-generation large-aperture ground-based telescope adaptive optics system real-time control.

This invention discloses a distributed intelligent decision-making and collaborative control system for unmanned aerial vehicle (UAV) swarms, relating to the field of UAV technology. The invention includes a data acquisition module, a situational awareness construction module, a distributed strategy negotiation module, a motion planning module, and a consistency control module. UAVs interact with neighboring nodes only to exchange decision parameters, reducing communication load and bandwidth requirements, avoiding the risk of single-node failure, and improving the robustness and operational reliability of the swarm system in complex maritime communication environments. It filters environmental information strongly correlated with its own motion, suppresses noise interference, and provides complete and reliable situational awareness data for swarm decision-making, improving the accuracy and anti-interference capability of maritime environmental situational awareness. Control parameters are adapted in real-time based on flight speed, attitude changes, and remaining battery power, balancing high-speed response accuracy and low-speed control stability, reducing low-power energy consumption, and enhancing the stability, endurance, and adaptability of swarm collaborative control to maritime operations.

The utility model relates to the technical field of brain imaging, in particular to a frequency-domain near-infrared spectrum measurement module and frequency-domain near-infrared spectroscopy device.The frequency-domain near-infrared spectrum measurement module comprises a detection unit and a processing unit, the detection unit is used for making direct contact with the head of a user, emitting detection light to detected tissue and receiving detection signals formed after being reflected by the detected tissue, and the processing unit is used for processing the detection signals; amplitude data and phase data of the detection signal are extracted, and the amplitude data and the phase data are sent to the processing unit after analog-to-digital conversion; and the processing unit is used for calculating optical parameters of the detected tissue based on the converted amplitude data and phase data, and wirelessly transmitting the optical parameters to the target main control unit. Amplitude and phase detection functions are completed by the front-end measurement module in advance, the use of a high-speed ADC and a mixer is avoided, the system complexity is reduced, signal transmission between the measurement module and the main control unit depends on wireless communication, excessive cable connection is not needed, and the brain activity monitoring system is suitable for brain activity monitoring requirements in a dynamic scene.

The application provides a low-orbit constellation satellite network traffic offloading method based on an auction theory, and steps are as follows: judging whether a subsidence satellite is a light-load subsidence satellite, a heavy-load subsidence satellite or a common subsidence satellite; all light-load subsidence satellites and heavy-load subsidence satellites send request packets containing detection information to each other, and transmission time delays between the subsidence satellites are obtained; the heavy-load subsidence satellite informs a ground station of the satellite state through a feeder link with a demand bandwidth, and the light-load subsidence satellite informs the ground station of the satellite state through the feeder link with a competitive bandwidth; the ground station puts the subsidence satellites into a buyer queue or a seller queue according to the collected satellite states, and obtains a matching result between the light-load subsidence satellites and the heavy-load subsidence satellites through a bidirectional auction; and the ground station informs all the subsidence satellites of the matching result through the feeder link, and the traffic offloading is transferred. The application maximizes the bandwidth of the satellite-ground link, and improves the overall throughput of the air-ground network.

The invention relates to the technical field of audio processing, in particular to an audio transmission system and method, a related device and a vehicle, and the system comprises a first device, a second device and a power amplifier device; wherein the first equipment and the power amplifier equipment are connected to form a first transmission link, and the first transmission link is used for at least transmitting multimedia information; the second equipment and the power amplifier equipment are connected to form a second transmission link for at least transmitting the multimedia information; and the first equipment and the second equipment are connected to form a third transmission link for at least transmitting the instruction information. According to the audio transmission system, through the annular audio link, the operational capability and reliability of the system can be improved.

This invention discloses a second-stage sampling time control circuit for a PIPELINE SAR ADC, relating to the field of integrated circuit technology. It includes a second-stage sampling circuit and a second-stage sampling clock generation circuit. The second-stage sampling circuit includes a margin amplifier, a second-stage sampling switch, an input capacitor, a feedback capacitor, and a load capacitor. The input terminal of the margin amplifier is connected to a reference voltage terminal through the second-stage sampling switch and the input capacitor, and the output terminal is grounded through the second-stage sampling switch and the load capacitor. The second-stage sampling clock generation circuit includes an inverter, a delay circuit, and an AND gate. The first input terminal of the AND gate is connected to the input signal, and the second input terminal is connected to the input signal through the delay circuit and the inverter. The output terminal outputs a level signal used to control the on / off state of the second-stage sampling switch. This invention designs the sampling time of the second-stage SAR ADC to vary with the PVT, reducing the bandwidth requirement of the margin amplifier at the SS corner and decreasing the power consumption of the margin amplifier.

An event filtering method for operating an event-based image sensor comprising a plurality of pixel circuits, a pixel circuit comprising: - a photoreceptor circuit configured for delivering a photoreceptor signal, - a change detector configured for detecting a change in the photoreceptor signal and emitting an event upon each detection of a change, the event being characterized at least by a polarity reflecting a direction of the change, wherein an event filter (20) receives a series of events and, for each received event, the event filter accepts or rejects the received event, the event filter (20) accepting a received event only when a first condition a) and a second condition b) are fulfilled: a) the received event has a same polarity as a polarity of at least a last received event, and, b) the received event and the last received event are separated by a time interval shorter than a time threshold.

The invention relates to the field of expressway safety, in particular to an expressway alarm event rechecking method and device, electronic equipment and a computer readable storage medium. The method comprises the steps that a plurality of alarm images corresponding to an alarm event are acquired, and the alarm images comprise target objects; obtaining motion feature description of the target object according to the plurality of alarm images, and constructing a re-checking prompt word according to the motion feature description; and inputting the re-checking prompt word and any alarm image into a multi-mode large model, and obtaining an alarm event re-checking result output by the multi-mode large model. According to the expressway alarm event rechecking method and device, the electronic equipment and the computer readable storage medium provided by the invention, the technical effects of improving the accuracy of an expressway alarm event rechecking result and reducing the expressway alarm event rechecking cost can be realized.

A smart image recognition integrated circuit chipset is a single chipset disposed in an image acquisition device, serving as a replacement for an image acquisition chip, an image front-end processing chip, and a back-end device image recognition chip. The smart image recognition integrated circuit chipset includes: a dynamic random access memory (DRAM) wafer layer; and a logic wafer layer disposed on the DRAM wafer layer. The logic wafer layer includes a redistribution layer at the bottom and a logic circuit layer above the redistribution layer. The logic circuit layer has a multiply-accumulate operation structure and a static random access memory (SRAM) structure. The DRAM wafer layer and the redistribution layer of the logic wafer layer are interconnected by hybrid bonding.

The application relates to a method for measuring delay difference between optical fiber channels based on nonlinear fitting, belonging to the technical field of optical fiber communication and measurement. The method comprises the following steps: dividing a modulated optical signal into a reference path signal and at least one measuring path signal, inputting the signals into different cores of a multi-core optical fiber or different optical fibers for transmission, respectively, carrying out photoelectric conversion and resampling to obtain the sampled reference path signal and the at least one measuring path signal; then carrying out Fourier transformation and squaring on the sampled reference path signal and the at least one measuring path signal to obtain power spectrum of the corresponding signals; then carrying out waveform nonlinear fitting on the power spectrum to obtain a frequency domain correlation peak expression and carrying out inverse Fourier transformation to obtain a time domain correlation peak expression; and carrying out correlation and fitting on the sampled reference path signal and the at least one measuring path signal by using the time domain correlation peak expression to obtain the coordinates of the fitted correlation peak, and calculating the delay difference between the optical fiber channels. The application has high measurement precision, low bandwidth requirement and low calculation complexity.

A method and system for encoding salient regions in real-time rendering scenarios includes: configuring the importance of various objects on the application screen; generating a video stream in real time based on user-input control information; acquiring and rendering the current frame from the video stream; then, based on the configured object importance, re-rendering the corresponding importance texture map of the current frame in the GPU buffer through the rendering context; finally, sending the current frame and its importance texture map into the CPU; calculating the QP increment that needs to be adjusted for each macroblock in the current frame based on the importance weight of macroblocks in the importance texture map; then adjusting the QP value of each macroblock based on the QP increment; and encoding the current frame based on the QP value. This invention relates to the field of information and communication networks, and can acquire and encode accurate object-level salient regions from the rendering pipeline in real time, enhancing the video quality of user-interested regions while ensuring real-time performance. It is suitable for real-time rendering scenarios such as video games.

The application discloses a kind of based on blockchain's internet of things equipment authentication method and system, belong to internet of things technical field, this internet of things equipment authentication method includes following steps: step 1, equipment registration, specifically including following steps: step 1.1, generates the dynamic identity code of internet of things equipment;Step 1.2, server verifies dynamic identity code;Step 1.3, block chain receives and stores the data uploaded by server;Step 2: mutual authentication between internet of things equipment and server, specifically including following steps: step 2.1, the authentication initialization of internet of things equipment;Step 2.2, the authentication of internet of things equipment in server and the session key generation of server;Step 2.3, the authentication of server in internet of things equipment and the state reconstruction of internet of things equipment.The application avoids the risk of large-scale information leakage caused by the CA being broken;Significantly reduce the burden of internet of things equipment, further optimize overall communication efficiency.

The invention relates to a neural network model training method and device, a neural network model calculation method and device, electronic equipment and a computer program product. According to the training method of the neural network model, the neural network model comprises a neural network layer, and the method comprises the following steps: dividing a target tensor in the neural network layer into at least two data blocks; for each data block, determining a corresponding public index according to the amplitude information of the elements in the data block; normalizing all elements in the data block relative to the common index to obtain a corresponding mantissa; for each element, only corresponding mantissa and sign bit are stored; the public indexes are stored according to data blocks, layers or channels; when the neural network model is trained, the public index, the bit width of the mantissa and the weight parameter of the neural network layer are updated through back propagation. According to the technical scheme, the requirements for the storage space and the memory bandwidth of the neural network model can be remarkably reduced on the premise that the precision is controllable.

The application discloses a convolution operation method and device. The specific implementation scheme is as follows: the method comprises the following steps: configuring a split parameter; inputting the split parameter, the parameter of the convolution operation and the parameter of the convolution acceleration device into a cost function to obtain the optimal value of the split parameter under the condition of meeting the constraint condition; adopting the optimal value of the split parameter to split input image data and weight data used for inputting the convolution acceleration device into a plurality of input data blocks and a plurality of weight data blocks; and controlling the plurality of input data blocks and the plurality of weight data blocks to be input into an internal local buffer, so that an operation device obtains the input data blocks and the weight data blocks required by the convolution operation from the internal local buffer, and performs the convolution operation on the input data blocks and the weight data blocks to obtain a plurality of output data blocks. The average utilization rate of the convolution acceleration device is improved, the time of the convolution operation is effectively reduced, and the balance between the utilization rate and the bandwidth demand of the convolution acceleration device is realized.

The invention discloses a viewpoint data transmission method, device and system, a medium and a program product. Comprising the following steps: a terminal device receives target viewpoint data transmitted by a base station device; wherein the base station equipment is used for determining and transmitting the target viewpoint data to the terminal equipment based on a viewpoint transmission strategy associated with the data processing state of the naked eye 3D service of the terminal equipment at the current moment; the number of viewpoint data in the target viewpoint data is smaller than the number of viewpoint data in the viewpoint data set; the viewpoint data set is associated with the naked eye 3D service; and loading the target viewpoint data. According to the scheme, the naked-eye 3D data display requirement of the terminal equipment can be met, transmission of redundant viewpoint data is reduced, and consumption of data transmission resources is reduced.

Provided are an uplink feedback method, apparatus and device, the method comprising: a station receiving a first frame sent by an access point, the first frame comprising first information, the first information being used for instructing the station to feed back compressed channel state information; the station receives a second frame sent by the access point, wherein the second frame is used for the station to perform channel estimation; and the station sends a third frame to the access point, the third frame comprising the compressed channel state information, the compressed channel state information being obtained by performing m times of polynomial fitting processing on the channel state information, the channel state information being obtained by performing channel estimation based on the second frame, m being a positive integer.

The invention is suitable for the technical field of laser communication, and provides a turbulence disturbance-oriented optical communication emission gain intelligent adjustment method, which comprises the following steps of: acquiring atmospheric turbulence channel state information in real time, constructing a turbulence disturbance intensity evaluation model, and outputting a current turbulence disturbance level; matching the turbulence disturbance level with a preset multi-level transmitting gain strategy table, and determining a target transmitting power gain value; the driving current of the laser transmitting end is dynamically adjusted through a self-adaptive feedback mechanism, continuous circulation execution is performed, and a closed feedback loop is formed. The turbulence channel state information is collected in real time, the turbulence disturbance intensity evaluation model is constructed, the multi-stage transmission gain strategy table is matched, the difference value between the actual transmission gain and the target value is controlled within the preset error range through the self-adaptive feedback mechanism, and the feedback correction step length is dynamically adjusted in combination with the turbulence intensity grade. The system can quickly respond to turbulence changes, and the bit error rate and the stability of a communication link are improved.

The invention discloses a portable miniature magnetic electrocardiosignal detection probe system, and relates to the technical field of biomedical engineering and weak magnetic signal detection. Comprising a miniature magnetic environment control subsystem, a weak signal acquisition subsystem and a real-time data processing subsystem, and the miniature magnetic environment control subsystem comprises a cylindrical miniature shielding cavity, a three-axis double-plane coil assembly and a measuring probe composed of a main measurement TMR sensor. The reference probe is composed of a cylindrical miniature shielding cavity, a three-axis double-plane coil assembly and a reference TMR sensor; the weak signal acquisition subsystem is used for acquiring measurement data of the main measurement TMR sensor and background reference data of the reference TMR sensor; and the real-time data processing subsystem is used for processing the acquired measurement data and background reference data to obtain a magnetocardiogram signal. According to the invention, a local low-magnetic-noise measurement space is constructed in the probe, the dependence on a large-scale building-level magnetic shielding room is reduced, and the availability in bedside and mobile scenes is improved.

The application relates to the technical field of automobile software upgrading, in particular to a software upgrading method and device, an electronic device and a storage medium, wherein the method comprises the following steps: obtaining the identification of a target ECU to be upgraded and a software upgrading package; if it is determined according to the identification that the target ECU is deployed with a reverse differential function, performing differential processing on the software upgrading package to obtain a differential package, and packing the differential package into a target format in which the target ECU can trigger the reverse differential function; and sending the differential package in the target format to the target ECU, wherein the target ECU analyzes the differential package in the target format, performs reverse differential processing on the differential package by using the reverse differential function to obtain the software upgrading package, and performs software upgrading by using the software upgrading package. Therefore, the problems in the prior art that the differential upgrading communication mode has a low rate, the vehicle-mounted network architecture is not adapted to the size of the software upgrading package, the ECU upgrading efficiency is low, and the upgrading experience is poor are solved.

This invention provides an artificial intelligence algorithm acceleration system and method for real-time junction temperature prediction of IGBTs, including a parameter acquisition module, an artificial intelligence algorithm acceleration module, and a host computer. The parameter acquisition module is used to acquire the saturated on-state collector-emitter voltage VCE(Sat), collector current IC, and substrate temperature TC during IGBT operation. The artificial intelligence algorithm acceleration module is based on a Zynq7000 series FPGA to build a SoC architecture, integrating a dual-core ARM Cortex-A9 processor and a dedicated neural network processor (NPU). The host computer is used to receive the junction temperature prediction results and raw acquired parameters transmitted by the artificial intelligence algorithm acceleration module, enabling real-time data display, historical data storage, junction temperature anomaly alarms, and model parameter calibration. This invention aims to solve the high latency, high communication cost, and data privacy issues of cloud computing solutions through collaborative optimization design of algorithms and hardware, while simultaneously overcoming the bottlenecks in computing power, energy efficiency, and accuracy of existing edge computing platforms.

This application discloses a method, apparatus, electronic device, and readable storage medium for determining k target values. First, the input dataset is divided into multiple data blocks. Based on the local extrema of each data block obtained through parallel computation, k candidate data blocks are selected. According to the block indices of the k candidate data blocks, their internal data rows are obtained, and based on the local extrema of each data row obtained through parallel computation, k candidate data rows are selected. Finally, the data is obtained according to the row indices of the k candidate data rows, and k target values ​​are determined. This scheme transforms traditional serial heap operations into fully parallelizable extremum comparison operations through block division and a two-level selection mechanism, reducing computational complexity. This design enables efficient parallel execution of computational tasks on multiple processors, improving processing throughput. Simultaneously, the index supports batch data retrieval mechanisms, optimizing memory access efficiency and reducing bandwidth requirements, thereby achieving excellent performance in scenarios with data volumes much larger than k.

This invention discloses a multispectral sensor-based precision monitoring device for farmland mounted on a drone, comprising: a crop growth cycle knowledge base, which is a structured database used to store full life cycle data of various crops, and pre-set multiple growth stages for each crop, wherein each growth stage defines a unique set of monitoring parameters; and a task input module, which is equipped with a communication interface for connecting to external devices and receiving task instructions transmitted in the form of structured data. This invention standardizes the raw multispectral data through the preprocessing unit and feature extraction unit of the onboard data processing module, transforming the massive and complex raw data into unified orthophoto data and lightweight vegetation index distribution maps, significantly reducing the data volume, lowering the requirements for drone computing power and network bandwidth, and achieving efficient data processing.

The invention discloses a multifunctional calculation circuit which comprises a parameter configuration unit used for performing parameter configuration, and configured parameters comprise an addressing base address and an interpolation mode; the read addressing unit is used for generating a read request to a read bus, reading data from an external memory according to the addressing base address, and caching the read data; the data comprises input feature map data and / or input grid data; the first-round addressing address is an addressing base address; the mapping unit is used for performing coordinate transformation according to the cached grid data, and determining adjacent point pixel values and coefficients thereof for interpolation calculation according to the obtained original image coordinates; the multiply-accumulate calculation unit is used for carrying out multiply-accumulate calculation on the adjacent point pixel value and the coefficient thereof determined by the mapping unit to obtain an interpolation; and the write addressing unit is used for writing the interpolation back to the external memory. According to the scheme, the affine transformation function and the grid sampling function can be flexibly achieved, resources are saved, and the interpolation calculation speed in the affine transformation is increased.