179results about How to "Reduce overhead" patented technology

Systems and methods for managing divergence of best effort transactional support mechanisms in various transactional memory implementations using a portable transaction interface are described. This interface may be implemented by various combinations of best effort hardware features, including none at all. Because the features offered by this interface may be best effort, a default (e.g., software) implementation may always be possible without the need for special hardware support. Software may be written to the interface, and may be executable on a variety of platforms, taking advantage of best effort hardware features included on each one, while not depending on any particular mechanism. Multiple implementations of each operation defined by the interface may be included in one or more portable transaction interface libraries. Systems and / or application software may be written as platform-independent and / or portable, and may call functions of these libraries to implement the operations for a targeted execution environment.

This invention discloses a video tag dynamic overlay anti-shake method and system based on AR, comprising: acquiring real-time video stream and device pose parameters at corresponding timestamps; constructing a dynamic perspective projection model based on the device pose parameters and calculating the initial pixel coordinates of the target AR tag in the current video frame; planning a local feature search window based on the initial pixel coordinates; calculating the average pixel displacement vector of image feature points in the local feature search window of the current and adjacent historical video frames; performing reverse displacement compensation on the average pixel displacement vector to obtain the target rendering coordinates, and rendering the target AR tag to the current video frame based on the target rendering coordinates. Compared with the prior art, this invention can overcome the shortcomings of large drift errors caused by simply relying on mechanical pose, high computational power consumption caused by global matching, and high-frequency jitter of tags caused by slight device vibrations, thereby improving tag mapping accuracy, reducing system computational power consumption, and improving the visual stability of video overlay.

This invention relates to the field of data processing and discloses a database log archiving method, apparatus, device, and medium, comprising: identifying a target redo log file to be archived from the database; creating a preliminary redo log file with the same attributes as the target redo log file and empty content within the same logical disk as the target redo log file; moving the target redo log file to a preset archiving directory located within the same logical disk via MV operations; changing the filename and storage path of the preliminary redo log file to the original filename and storage path of the target redo log file via MV operations; and mounting the revised preliminary redo log file to the database. This invention solves the problems of high I / O consumption and low archiving efficiency in existing database log archiving technologies.

The application discloses a method for establishing end-to-end secure communication of unmanned aerial vehicle under cloud network architecture, and takes cloud server as a security service center to provide full-process authentication service for unmanned aerial vehicle end system; the cloud server only issues public authentication materials to unmanned aerial vehicles, and session key negotiation and establishment of end-to-end secure communication are realized between unmanned aerial vehicles; the unmanned aerial vehicle end system does not need to store authentication materials of other unmanned aerial vehicles in advance, the cloud server is driven by specific tasks, and specific authentication materials required for key negotiation are issued to unmanned aerial vehicles which need to be securely cooperated according to task requirements. The application only requires that the cloud server and any one of the unmanned aerial vehicles for key negotiation establish a communication connection, and the authentication materials issued by the cloud server can make the unmanned aerial vehicles realize key negotiation and establish an end-to-end secure channel in a specific range; different temporary public keys are used for each request message, which can effectively prevent the harm caused by long-term and short-term secret leakage.

This invention discloses a power distribution IoT communication and equipment management system based on dynamic optimization algorithms. It adopts a four-layer architecture: a perception layer, an edge layer, a platform layer, and an application layer. The end devices in the perception layer are used to collect power distribution data and execute control commands. The edge devices in the edge layer, and their managed sub-devices, are used for protocol conversion, data preprocessing, and executing dynamic optimization algorithms. The platform layer is used for message parsing, algorithm optimization, device management, and data storage. The application layer provides a visual user interface. Through dynamic optimization algorithms and a full lifecycle device management scheme, the system significantly improves the reliability of power distribution IoT data transmission, optimizes network resource utilization, enhances equipment operating efficiency, ensures the real-time performance of critical services, and features strong compatibility, security, and concurrent processing capabilities.

The application provides a provincial meteorological and administrative collaborative wind speed prediction method based on dynamic federal learning, relates to the cross technical field of artificial intelligence and energy meteorology, S1, basic data of N meteorological monitoring stations in a province is acquired, is divided into M initial subgraphs according to the administrative boundary of a prefecture-level city and is allocated an edge server, each collaborative subgraph pair is determined according to the Pearson correlation coefficient of the wind speed sequence of the station, the time sequence data deviation of the synchronized subgraph is synchronized through a dynamic time warping algorithm after every 3 rounds of federal iteration, and the subgraph data after synchronization is output. Through an endogenous decision and optimization framework, three links of dynamic coordination of cross-domain collaboration, local learning and gradient transmission are coordinated, and finally a global optimal provincial meteorological and administrative collaborative wind speed prediction method based on dynamic federal learning is achieved among multiple targets such as prediction accuracy, convergence speed and communication cost.

The application discloses an OTFS system channel estimation method, device, storage medium and equipment, belongs to the wireless communication technical field, and the method comprises the following steps: acquiring a sending pilot signal, a receiving pilot signal and a noise variance; preprocessing the sending pilot signal and the receiving pilot signal to obtain sending pilot data and receiving pilot data; inputting the sending pilot data, the receiving pilot data and the noise variance into a trained channel sparsity estimation model to obtain a channel sparsity estimation value, wherein the channel sparsity estimation model is a deep neural network; and reconstructing the channel based on the channel sparsity estimation value by using an OMP algorithm to obtain a channel estimation value; the application estimates the channel sparsity through the deep neural network, overcomes the selective bias problem in the traditional OMP algorithm, improves the accuracy of channel estimation by combining offline training and data driving, and can also reduce the overhead of the pilot signal.

The application provides an activation module for data calculation, an AI processor and a data calculation method. When it is determined that a result calculated by a preceding matrix acceleration module meets an output condition, the output calculation data is stored in a cache unit. A read-write control unit reads the output calculation data from the cache unit and distributes the output calculation data to each calculation unit. Each calculation unit performs a softmax calculation and outputs a target calculation result. In this way, the output calculation data output by the preceding matrix acceleration module can be stored in the cache unit of the activation module. After processing by the read-write control unit and data distribution, the softmax calculation is performed in parallel by at least one calculation unit. The calculation and access of all data are performed in the activation module, reducing the overhead of accessing memory and improving overall calculation performance. The parallel calculation processing scheme can also improve calculation efficiency.

This invention discloses a hardware acceleration method and accelerator for Transformer based on mixed-precision quantization and Huffman coding. The acceleration method includes: using a genetic algorithm to obtain several configuration schemes for mixed-precision quantization of Transformer network layers; performing mixed-precision quantization on each Transformer network layer based on each quantization configuration scheme to obtain a corresponding KL divergence; training a multilayer perceptron to obtain a quantization configuration prediction network using the quantization configuration scheme and the corresponding KL divergence as the output label and input feature, respectively; receiving a user-set target KL divergence value, using the quantization configuration prediction network to obtain the corresponding quantization configuration scheme, and performing mixed-precision quantization on each network layer based on the quantization scheme; and using Huffman coding to encode and compress all quantization weights before on-chip storage. This invention can reduce storage and computational overhead while maintaining model accuracy.

This application provides a communication method, network-side device, terminal, communication system, storage medium, and product, relating to the field of communication technology. The method includes: broadcasting first indication information, wherein the first indication information indicates the value range of a first parameter and a combination of first parameter values, the first parameter being the time slot offset between the time slot where the Downlink Control Information (DCI) is located and the time slot for the Physical Uplink Shared Channel (PUSCH) transmission, and the combination of first parameter values ​​indicating the start symbol and number of symbols for optional PUSCH transmission and the mapping type of optional PUSCH. Therefore, when broadcasting the first indication information, indicating both the value range of the first parameter and the combination of first parameter values ​​respectively, compared to indicating only the combination of the value range of the first parameter and the first parameter value, results in lower network overhead, thereby optimizing the network overhead when broadcasting a time-domain resource list.

A video encoding and decoding method, apparatus, and medium are provided. An example method of video decoding includes receiving a video bitstream including a plurality of frames, the plurality of frames including a current frame; and identifying a primary reference frame for context initialization of the current frame. The method further includes identifying a reference frame of the current frame based on the primary reference frame, and reconstructing the current frame by applying a cross component sample offset (CCSO) mode using the reference frame.

This application discloses a data processing method, generation method, apparatus, device, medium, and product, comprising: first acquiring sample data, which is determined based on at least one image; then performing stepwise denoising processing on the sample data according to a time step sequence to obtain the denoising processing result of each time step in the time step sequence; then calculating the similarity between the denoising processing results of any two time steps in the time step sequence, so that the similarity can indicate whether the denoising processing results of different time steps in the time step sequence are similar; then determining the skip step analysis result of the time step sequence based on the similarity, so that the skip step analysis result can indicate that in the generation processing based on the time step sequence, the denoising processing of certain time steps can be skipped by reusing existing denoising processing results, thereby making the computational resource overhead and time overhead of the generation process based on the skip step analysis result relatively low.

This invention relates to the fields of computer data processing and database technology, specifically to an intelligent search system for business objects based on metadata. The system includes: a context request parsing module: receiving abstract search requests and extracting environment parameters and permission features to generate a dynamic context snapshot; a logical structure construction module: combining snapshot execution rule injection operations to generate a logical abstract syntax tree containing implicit filtering conditions; a multi-dialect compilation and execution module: translating the syntax tree into physical execution statements matching the target storage engine dialect according to physical mapping rules; and an adaptive optimization feedback module: monitoring execution latency data and dynamically correcting the index strategy definition. This invention solves the maintenance bottleneck caused by the tight coupling between business logic and physical storage in heterogeneous data source environments, achieving zero-code modification and hot deployment of business logic.

This application discloses a high-speed serializer with selectable bit width and a high-speed interface, belonging to the field of high-speed interface technology. The high-speed serializer includes: multiple shift registers and a tree-structured serializer for converting the data output from the multiple shift registers into serial data; the selection signals corresponding to the two-to-one selection modules in each shift register are independent; wherein each signal input terminal of the tree-structured serializer is connected to the signal output terminals of the multiple shift registers. When supporting parallel-to-serial conversion output with different bit widths, only the selection signals of the two-to-one selection modules of the shift registers need to be selected for output, eliminating the need for multiple sets of serializers, thus significantly reducing the hardware overhead required by the serializer. Furthermore, when implementing parallel-to-serial conversion with the same bit width, the number of D flip-flops in the phase-shift register can be reduced, thereby greatly reducing the power consumption required by the serializer.

The application relates to an expandable multi-agent hierarchical navigation method and device based on a graph network, wherein the method comprises the following steps: receiving state information of all agents and position information of target points, and respectively generating an agent relationship graph of all agents and a target point relationship graph of all target points according to the state information and the position information, so as to calculate an agent-target point relationship matrix, and match a corresponding optimal target point for a current agent through the relationship matrix; fusing the state information and the position information through a subgraph fusion strategy to obtain a fusion result, and encoding the fusion result according to a multilayer perception strategy, extracting an encoding relationship between the current agent and the optimal target point, and generating an optimal path between the current agent and the optimal target point. Therefore, the problems that the existing multi-agent navigation method has large calculation amount and poor performance, the action space and the state space of multiple agents are too complex, overfitting is prone to occur, the migration ability is poor, and large-scale application is difficult are solved.

The application belongs to the technical field of artificial intelligence security and model intellectual property protection, and discloses an active defense and access control method for a deep learning model, which comprises the following steps: S1, generating a scalar license sequence based on a private key parameter, and dividing a training round into multiple stages, so that the stage indexes are consistent and the license values corresponding to the indexes in the license sequence are read; S2, constructing an authorized channel set in combination with channel static importance evaluation and channel chaos score, generating an authorized mask and an unauthorized mask; S3, respectively calculating authorized task loss and unauthorized confusion loss and jointly optimizing, and simultaneously implementing reset and gradient freezing on the parameters corresponding to the authorized channel set at the beginning of the training stage; S4, during model deployment and reasoning, the authorized end reconstructs the license sequence according to the shared key and generates the authorized mask for reasoning, and the unauthorized end outputs performance degradation. The application improves the robustness to adaptive attacks and maintains the performance gap between authorized and unauthorized.

The present application relates to the technical field of artificial intelligence and federated machine learning, and particularly relates to an asynchronous federated learning aggregation method and system based on clustering cache. The present application clusters clients by intermediate features of the clients. In global aggregation, intra-cluster aggregation is firstly performed, and then global aggregation is performed based on client clusters. The client clusters are dynamically updated. In intra-cluster aggregation, an active set and a slow set are introduced to realize an asynchronous participation mechanism of intra-cluster aggregation. Weighted aggregation of the active set and the slow set solves the problem of system heterogeneity. The present application solves the defect of insufficient timeliness of existing federated learning methods in a data heterogeneous scene, and guarantees the timeliness and model training accuracy of federated learning in the data heterogeneous scene.

This disclosure provides a text data processing method, apparatus, device, storage medium, and program product, relating to the field of big data processing. The method includes: acquiring incremental text data and historical clustering data; the incremental text data includes at least one text data item; performing incremental clustering processing on the text data items based on historical clusters in the historical clustering data, matching historical clusters or creating new clusters for each text data item, and generating corresponding cluster topics for clusters that meet preset conditions, thereby obtaining incremental clustering results; and updating historical clustering data according to the incremental clustering results. This method can effectively integrate newly added text data, dynamically adjust the clustering results as data is updated, avoid the high overhead of full re-clustering, and enhance the interpretability of clustering results by automatically generating cluster topics. It achieves efficient dynamic clustering of incremental text data, improving the automation and intelligence level of data management.

The application provides a multi-layer satellite network distributed routing method and system, the method comprising: dividing a low-orbit satellite set into multiple low-orbit satellite regions, each low-orbit satellite region corresponding to at least one medium-high-orbit satellite as a regional control node; multiple medium-high-orbit satellites cooperatively generating an exit selection strategy for each low-orbit satellite region and issuing the exit selection strategy to the corresponding low-orbit satellite region; low-orbit satellites in a low-orbit satellite region taking the corresponding exit selection strategy as an inter-regional forwarding constraint and performing hop-by-hop autonomous forwarding in the low-orbit satellite region; and multiple medium-high-orbit satellites updating the exit selection strategy for each low-orbit satellite region based on updated regional network state. The multi-layer satellite network distributed routing method and system of the application can reduce the frequency of cross-region path reconfiguration while retaining the real-time response capability of hop-by-hop routing, thereby enhancing the overall stability and scalability of the system.

The utility model relates to a charger power module sampling compensation circuit, including resistance -capacity partial pressure network, voltage follower, differential current sampling amplifier and first low pass filter, resistance -capacity partial pressure network is used for gathering voltage signal from power module output end, and the voltage signal is scaled down with the existing bias voltage each other superimposes and generates input signal and then is delivered to voltage follower, voltage follower is used for generating first signal based on input signal, differential current sampling amplifier is used for gathering current signal from the current sampling resistance of power module output end and converts current signal into second signal, and second signal can generate third signal with first signal superposition, first low pass filter converts third signal into final sampling signal and exports final sampling signal to DSP controller, the utility model discloses under the condition that guaranteeing LLC resonant converter output voltage wide range, has reduced the overhead of DSP controller.

The present disclosure provides systems, apparatus, devices, and methods, including computer programs encoded on storage media, for CSI feedback based on a Type 1 codebook and multiple CSI-RSs. A UE (102) receives (710), from a network entity (104), a configuration for a CSI report, the configuration indicating multiple CSI-RS resources for channel measurement and a Type 1 codebook. The UE (102) receives (730), from the network entity (104), the multiple CSI-RSs indicated by the configuration. The UE (102) transmits (740), to the network entity (104), a CSI report, the CSI report including CSI based on the multiple CSI-RSs and the Type 1 codebook.

This invention discloses a machine learning-based method, identification method, and apparatus for detecting and identifying UAV telemetry and control link signals, relating to the field of signal detection, and aimed at improving applicability to complex electromagnetic backgrounds such as non-Gaussian noise environments. The invention includes: acquiring radio frequency (RF) signals; preprocessing the RF signals using wavelet transform; extracting and fusing the dimensional transformation state statistical features and signal envelope features of the preprocessed RF signals to obtain fused features, and performing UAV presence identification based on the dimensional transformation state statistical features; calculating the classification results of the fused features using a basis vector learning model and a spatial metric search model, respectively; and performing weighted fusion of the calculated classification results, using the category corresponding to the maximum fused classification probability as the identification result. This invention improves the accuracy of UAV telemetry and control link signal detection in complex non-Gaussian channel environments, exhibits better universality in non-Gaussian noise environments, and demonstrates strong robustness.

The application discloses a probability shaping log likelihood ratio acquisition method, supports probability shaping log likelihood ratio calculation of non-MB distribution, can be used for non-linear channel performance optimization, can be compatible with LLR calculation of MB distribution probability shaping, uniform distribution and part of low-order modulation, has low circuit operation complexity, supports multi-functional merging design, can be realized by using the same circuit, reduces hardware cost compared with multiple independent realizations, when the probability distribution is known, probability value calculation is directly used, and there is no need to convert a shaping factor or to look up a shaping factor, and the method can work in a normal signal-to-noise ratio range and does not need to meet a higher signal-to-noise ratio condition. The application further provides a corresponding probability shaping log likelihood ratio acquisition device.

This invention provides a distributed time synchronization method suitable for UAV swarms, comprising: Step 1: Synchronization information exchange between adjacent nodes of the UAVs; Step 2: Propagation delay compensation, using the synchronization interaction information received from neighbors within the synchronization period of Step 1 to compensate for the time-varying propagation delay timestamps; Step 3: Logical clock adjustment parameter update, combining the previously obtained synchronization information to estimate and update the logical clock parameters, completing the final time synchronization; Step 4: Reinforcement learning-based adaptive selection of the synchronization period, using an adaptive period decision mechanism based on reinforcement learning to dynamically and adaptively output the optimal synchronization broadcast period in the current state. This method overcomes the synchronization error caused by time-varying propagation delay in high-mobility environments; it adaptively adjusts the synchronization interaction period according to the actual clock state of the swarm, effectively reducing the system's communication overhead and energy consumption while ensuring high-precision time synchronization.

The application discloses a positioning method, device and terminal, and belongs to the technical field of wireless communication. The positioning method of the application comprises the following steps: a first terminal broadcasts sidelink (SL) positioning related information; wherein the SL positioning related information is used for at least one second terminal to determine a target terminal, the target terminal is used for transmitting first information of at least one second terminal, and the first information comprises at least one of a positioning measurement result, a positioning result and positioning assistance information.

This invention discloses a model management and reliability enhancement method for AI-driven mobility prediction in wireless networks, belonging to the field of mobile communication network technology. The method includes: an offline phase, collecting historical data including UE measurement data; training and testing the AI ​​model using a subset of data based on UE mobility level, functional requirements, and OW / PW step size; identifying the model's predictive performance and overhead; establishing a mapping relationship between model identifiers and network / UE side parameters; and selecting the optimal unique sub-model based on uploaded mobility speed and functional requirements; and an online phase, performing instance-level predictability evaluation of the AI ​​model based on the local dataset before and after each model call, followed by model activation / deactivation determination. This invention improves the inference reliability and stability of the AI ​​model deployed in the access network, offering advantages such as convenient implementation, low additional signaling overhead, and low engineering deployment cost, making it more suitable for widespread application in practical mobile communication systems.

This application proposes a method and chip device for monitoring processor program execution information, relating to the field of processor technology. It includes: real-time acquisition of the processor's raw program counter value, raw return address value, and hardware timestamp; compression processing of the raw program counter value and raw return address value to obtain compressed program counter value and compressed return address value, wherein the compression processing discards low-order alignment bits and high-order address bits; address range judgment of the raw program counter value and raw return address value to generate a program counter position flag and a return address position flag; concatenating the hardware timestamp, compressed program counter value, compressed return address value, program counter position flag, and return address position flag in a preset order into a fixed-width monitoring data packet; and reporting the monitoring data packet in response to the fulfillment of a preset trigger condition. This scheme can achieve effective monitoring of processor program execution information with low hardware overhead.

The application discloses a data processing method and system in a remote procedure call, and the method comprises the following steps: one party of the remote procedure call acquires to-be-transmitted data, wherein the to-be-transmitted data comprises at least one field; the one party acquires serialized data and data in a predetermined field, wherein the serialized data is obtained by serializing data in other fields of the to-be-transmitted data, the other fields are fields of the to-be-transmitted data except the predetermined field, the predetermined field is a field satisfying a predetermined condition, and the data in the predetermined field has not been subjected to serialization processing; and the one party sends the serialized data and the data in the predetermined field to another party of the remote procedure call. The application solves the problem that the RPC cannot meet the requirements due to the large serialization processing overhead in the RPC process, thereby saving the memory copy overhead in the serialization processing and improving the processing efficiency of the RPC.