59 results about "Binary search algorithm" patented technology

The invention relates to the technical field of graphics card power consumption adjustment, and discloses a method, a device and equipment for dynamically adjusting the power consumption of a graphics card component. The method comprises the following steps: carrying out multi-channel data acquisition and working load characteristic analysis on operation parameters of a graphics card GPU core, a video memory and a power management unit to obtain a component temperature state evaluation matrix; executing component-level power consumption distribution based on multi-objective optimization to obtain a power consumption distribution scheme of each component; inputting the power consumption distribution scheme of each component into a power consumption-frequency-voltage mapping model, and calculating an optimal frequency voltage configuration parameter through a binary search algorithm to obtain a frequency voltage control instruction; performing multi-step prediction to obtain a module power consumption demand prediction value; according to the method, the frequency voltage combination with the highest performance efficiency can be found under the condition that the power consumption constraint is met, and accurate power consumption control is achieved.

The invention discloses an intelligent literature screening method and system based on zero sample voters. The method comprises the following steps: expanding a literature set based on seed literatures, constructing a classification system comprising a plurality of zero sample voters, screening literatures related to a target topic through a majority voting mechanism, and iteratively expanding the literatures to obtain more literatures related to the target topic. The zero sample voting device integrates subject term matching, language model pre-training, multi-large language model voting and a semantic embedding vector technology, adaptively determines a threshold value in combination with an improved binary search algorithm, and realizes high-precision classification without training data. The system supports parallel processing and intelligent API management, and the processing efficiency of a large-scale literature set is remarkably improved. The method is suitable for the fields of academic research, literature retrieval and the like, can quickly construct a large-scale high-correlation literature information base, and particularly meets the retrieval requirements of emerging technologies or interdisciplinary themes.

This invention belongs to the field of facial expression recognition and provides a micro-expression recognition method based on convolutional neural networks and optical flow features, which is used to improve the adaptability and accuracy of micro-expression recognition. The method first constructs a face detection module to perform face detection on each image frame in a video segment, outputs facial key point information, and extracts facial regions of interest (ROIs) based on the facial key point information: nose, mouth, left eye and eyebrow, right eye and eyebrow. Then, optical flow information and optical strain information are introduced to characterize the spatiotemporal information of facial movement and the intensity information of facial deformation. The optical flow eigenvalue of each image frame is calculated, and a binary search algorithm is used to search for the image frame with the maximum optical flow eigenvalue, which is used as the vertex frame for micro-expression recognition. Finally, a micro-expression recognition model based on a convolutional neural network is constructed, which uses the horizontal and vertical components of the optical flow and optical strain of the vertex frame as input. The micro-expression recognition model outputs a micro-expression category prediction result.

The invention provides a cellular-free mMIMO (multiple input multiple output) system computing power resource allocation and beam forming optimization method and a cellular-free mMIMO system computing power resource allocation and beam forming optimization system, and belongs to the technical field of wireless communication. The method specifically comprises the following steps of: respectively establishing a double-queue model based on a first-in first-out criterion at a central processing unit (CPU) and an access point (APs), taking a dequeue rate at the CPU as an enqueue rate at the AP, constructing a data volume relationship in a queue of a current frame and a previous frame, and analyzing system downlink end-to-end time delay based on an M / D / 1 queuing model. In a first layer queue, a binary search algorithm is provided to design computing power resource allocation at a CPU, and in a second layer queue, a path tracking algorithm is provided to optimize a beam forming vector at an AP. According to the method, the instantaneous channel state information is utilized, the worst user time delay is minimized under an alternating iteration algorithm framework, the calculation complexity is reduced, and meanwhile an effective solution is provided for ultra-low time delay communication.

The invention discloses an adaptive visual mark pruning method and device based on a multi-modal large model. The method comprises the following steps: calculating two initial distributions of visual marks; initializing an error threshold according to a binary search algorithm; using a greedy algorithm to delete the visual marks which have the minimum influence on the two initial distributions until the error of the two initial distributions reaches an error threshold value, obtaining two groups of candidate deletion marks, taking an intersection, and deleting the visual marks based on the intersection; updating an error threshold boundary according to the model calculation amount after the visual mark is deleted and the target calculation amount; repeating the deleting and updating steps until a stopping condition is met, and calculating the average deleting number of the visual marks in each layer of a batch of data as a deleting strategy; and sorting the visual marks to be deleted and then deleting the visual marks according to a deletion strategy. According to the method, the use of computing resources is optimized by automatically identifying and removing redundant visual marks, the operation cost is reduced on the premise of not sacrificing the performance of the model, and the reasoning speed of the model is increased.

The present invention belongs to the field of industrial robot collision detection, and discloses a conservative collision detection method for industrial robot path planning, including 1: using a binary search algorithm based on Morton code to construct a linear hierarchical bounding volume; 2: proposing a GPU-accelerated SDF construction algorithm; 3: proposing an envelope sphere generation algorithm based on particle swarm; 4: using SDF and envelope sphere to achieve conservative collision detection. The present invention marks and subdivides the voxel grid of the model surface area, and only calculates the distance field function value in the area, thereby reducing the number of voxels that need to be calculated, thereby improving the calculation efficiency, and using sparse grids for storage to reduce memory overhead; all threads can independently access LBVH and calculate the shortest distance, thereby improving the parallelism of the calculation; using a particle swarm optimization algorithm to calculate a tight envelope sphere instead of robot joints to perform collision detection, thereby improving the efficiency of collision detection.

The invention discloses a stepped three-band grating coupler and a reverse optimization method thereof, and belongs to the technical field of photonic devices and integration, and the reverse optimization method comprises the steps: determining a design target of the grating coupler, and defining an initial structure; defining optimization parameters including grating height and grating width according to the grating number; defining an optimization quality factor according to a design target of the grating coupler, and dynamically updating a weight coefficient of the quality factor; optimizing the width and height distribution of all gratings by using an improved direct binary search algorithm; and iterative optimization is continuously carried out until a design target is achieved, and width distribution corresponding to gratings with different heights in the optimized stepped grating structure is obtained. The problem that traditional grating diffraction has inherent wavelength dependence is effectively solved, and efficient coupling of three optical communication wavebands is achieved.

This invention relates to the field of multi-processor multi-task joint scheduling technology, specifically disclosing a typed task joint scheduling system and method based on a heterogeneous multi-core architecture. It introduces a joint scheduling mechanism to divide and sort tasks according to task size and priority. Based on this, for the time-limited characteristics of real-time tasks, an inertial weight coefficient particle swarm optimization method is used to iteratively update the load balancing strategy, minimizing the maximum response time of real-time tasks while meeting their schedulability requirements. Simultaneously, for the low-priority characteristics of non-real-time tasks, the problem-solving is simplified using a Lagrange-based convex optimization approach, and an energy-constrained binary search algorithm is employed to effectively reduce the average response time of non-real-time tasks, achieving optimal load distribution for the system.

The invention provides an industrial edge network micro-service optimization method based on dynamic arrangement and migration expansion, which comprises the following steps: abstracting an industrial edge network into an intelligent industrial network model formed by heterogeneous edge nodes and links, modeling an industrial application request into a request chain formed by combining a plurality of micro-services with a data dependency relationship in sequence, calculating a micro-service instance deployment scheme and a request routing scheme; counting a time-varying request stream, analyzing the minimum core number meeting the time delay constraint in a statistical result by using a multivariate performance analysis model based on an m / m / c queue network and a binary search algorithm, and carrying out dynamic expansion and contraction adjustment on core resources of deployed micro-service instances; and solving a mixed integer nonlinear programming migration decision problem according to the initial dynamic scaling adjustment result and the migration cost so as to optimize the optimal collaborative deployment and request routing of the micro-service instance between the edge nodes. According to the invention, the service continuity and the overall energy efficiency of the industrial edge network system are improved.

The invention belongs to the technical field of battery cluster thermal runaway detection, and particularly relates to a detection positioning method, system and device suitable for thermal runaway of a battery pack in a battery cluster and a medium. The method comprises the following steps: grouping channels such as battery packs, battery cabins and electrical cabins in a battery cluster in a manner of combining grouping detection and dichotomy positioning, and sequentially carrying out thermal runaway detection; and when a thermal runaway early warning or alarm occurs in a certain channel group, a thermal runaway channel is quickly positioned by adopting a bisection method. According to the method, an air suction type thermal runaway detection technology is utilized, gas in the battery pack is extracted for analysis, and thermal runaway detection of the battery pack is achieved. The application of the dichotomy search algorithm further improves the accuracy of thermal runaway channel positioning. Compared with a traditional detection method, the method has the advantages of being short in detection period, accurate in positioning, low in cost and the like, is suitable for battery pack thermal runaway detection scenes such as electrochemical energy storage and the like, and has high application value.

The invention relates to a time-delay phase-locked loop circuit, a time-delay phase-locking method and a memory, and the time-delay phase-locked loop circuit comprises a comparator, a fine adjustment control circuit and a fine adjustment circuit. The comparator is configured to receive a reference clock signal and a clock signal to be finely adjusted and generate a first feedback signal; the jump of the first feedback signal represents that the phase relationship between the reference clock signal and the clock signal to be finely adjusted is changed. The fine tuning control circuit is connected with the comparator and is configured to generate a fine tuning control code based on a binary search algorithm; and receiving a first feedback signal, and adjusting the fine tuning control code based on a binary search algorithm in response to the first feedback signal. And the fine tuning circuit is configured to respond to the numerical value change of each bit of code in the fine tuning control code, and adjust a fine tuning delay value until the phase difference between the reference clock signal and the clock signal to be finely tuned is smaller than the unit delay amount of the fine tuning circuit. Therefore, the adjustment interval can be rapidly reduced, and fine adjustment locking is accelerated.

The invention discloses an image segmentation method and device, equipment and a storage medium, and relates to the technical field of automatic segmentation, and the method comprises the steps: determining a target binary mask corresponding to a target image through employing a preset image segmentation model, and generating a target compression code corresponding to the target binary mask based on a preset data structure; generating a target one-dimensional array corresponding to the target compressed code based on a preset typed array condition, and determining a target two-dimensional array corresponding to the target one-dimensional array based on a preset segmentation method; determining a target one-dimensional position corresponding to the current mouse position, and determining a target matching index based on a preset binary search algorithm, the target compressed code and the target one-dimensional position, so as to determine a target segmentation region based on the target matching index and the target two-dimensional array, and segmenting the target image based on a preset dynamic rendering technology and the target segmentation region. In this way, the efficiency and accuracy of image segmentation can be improved.

The invention discloses an optical filter for realizing a medium-wave infrared focal splitting plane on a metasurface and a reverse design method. According to the light field regulation and control characteristics of the metasurface, spectrum routing and focusing functions of a specified medium-wave infrared wave band can be completed only by using the single-layer all-silicon medium metasurface, so that the filtering effect similar to that of a Bayer optical filter is achieved, the spectrum energy utilization rate is remarkably improved compared with that of the Bayer optical filter, an end-to-end reverse method is used in the design thought, and the design cost is reduced. Structural parameters are optimized in a staged mode through a genetic algorithm and a binary search algorithm (DBS), the advantages of all the algorithms are brought into full play, the design threshold is lowered, the optimization freedom degree is improved, and therefore the optimization performance can be improved. Therefore, key device support can be provided for low-illumination mid-infrared night vision color imaging application, and a new design thought is expanded for the technical field of integration and miniaturization.

The invention provides a tunnel monitoring emergency system and method based on an interpolation algorithm and a binary search algorithm, and the system comprises an Internet of Things data collection module, a data processing module, an alarm module, a plan strategy module and an event handling module which are connected in sequence, and all the modules work cooperatively. According to the method, abnormal or missing data is intelligently complemented through an interpolation algorithm, alarm parameters are dynamically configured for event monitoring equipment in advance based on a tunnel environment, an operation time period and the equipment type of the event monitoring equipment, and a nearest camera and upstream and downstream cameras thereof are rapidly positioned through pile number sorting and a binary search algorithm. In combination with an intelligent analysis and plan linkage mechanism, automatic screen projection of infield pictures and outfield traffic situation awareness are realized, and evacuation decision making is assisted; and finally, by generating and grading emergencies, related units are linked to perform timely processing, so that all-directional perception and intelligent management of the tunnel operation state are realized, and the tunnel safety management level and the emergency response capability are improved.

The invention relates to the technical field of avionics networks, and discloses a TSN redundant frame filtering method and system based on an IEEE802.1 CB protocol, and the method comprises the steps: receiving a data frame through an MAC layer of an end system, and extracting a destination MAC address and a source MAC address of the data frame; constructing an address two-tuple by using the destination MAC address and the source MAC address, and performing matching query in a pre-configured flow table by adopting a binary search algorithm to obtain a flow identifier corresponding to the address two-tuple; searching data stream state information bound with the stream identifier, wherein the data stream state information comprises a currently received maximum frame sequence number and historical window information for recording a historical frame receiving state; comparing the serial number of the data frame with the maximum frame serial number; according to the comparison result and the historical window information, corresponding data frame receiving or filtering operation is executed, and the problems that the flow identification query efficiency is low, and the out-of-order redundant frame processing logic is not accurate are solved.

Disclosed are an offset calibration method and circuit applied to a comparator array. The offset calibration circuit includes a global calibration voltage generation module, integrators, comparators, a global logic control circuit, and local logic control circuits; an entire comparator array shares the single global calibration voltage generation module, and each of the comparators only needs to introduce an integrator circuit, such that a large calibration range and a small calibration step are achieved, a long calibration cycle and a large circuit area are required, and the requirements for a low area are satisfied. The offset calibration method provided by the present disclosure is similar to a binary search algorithm, which is adopted to search for the offset voltage, the calibration step of12N⁢Vrefcan be realized by only N cycles, and short calibration time is thus realized.

Pipelining a binary search algorithm of a sorted table is performed by breaking a single sorted table into multiple smaller tables, such that a binary search can produce a result every clock cycle. A process includes storing a plurality of tables that collectively form a single sorted table that includes addresses and entries corresponding to each address where the entries are sorted, each of the plurality of tables include a subset of the addresses and corresponding entries; and performing a binary search where each iteration of the binary search searches one of the plurality of tables such that a complete search traverses through all of the plurality of tables and such that a plurality of searches are performable concurrently pipelined through each of the plurality of tables.

The invention relates to the technical field of power system risk assessment, in particular to a power system cascading failure event sampling method, system and device and a storage medium. An initial fault event set is constructed by acquiring power system parameters, a dynamic probability correction model is constructed based on a current system state, and a load state influence factor, a new energy fluctuation influence factor and a topological correlation influence factor are introduced to correct a candidate event probability in real time. And converting the corrected dynamic probability into a roulette selection weight, optimizing the sampling efficiency by adopting a binary search algorithm, and outputting a complete fault sequence through iterative evolution until a termination condition is met. The technical problems of insufficient coverage of high-risk events, large deviation between static probability setting and an actual fault propagation path, low calculation efficiency and the like in a traditional sampling method are solved, the dynamic evolution law of cascading faults can be accurately reflected, the authenticity and reliability of a risk assessment result are improved, and important technical support is provided for safe operation of a power system.

Pipelining a binary search algorithm of a sorted table is performed by breaking a single sorted table into multiple smaller tables, such that a binary search can produce a result every clock cycle. A process includes storing a plurality of tables that collectively form a single sorted table that includes addresses and entries corresponding to each address where the entries are sorted, each of the plurality of tables include a subset of the addresses and corresponding entries; and performing a binary search where each iteration of the binary search searches one of the plurality of tables such that a complete search traverses through all of the plurality of tables and such that a plurality of searches are performable concurrently pipelined through each of the plurality of tables.

The invention provides a satellite-ground network OFDM (Orthogonal Frequency Division Multiplexing) anti-interception waveform design method based on security coding, and relates to the technical field of communication. The method comprises the following steps: determining a first signal to interference plus noise ratio at a legal receiver and a second signal to interference plus noise ratio at an eavesdropper according to a source symbol transmitted on each subcarrier, a security coding matrix in a time domain, a power allocation scheme, a frequency domain channel matrix and a frequency domain noise vector; according to the first signal to interference plus noise ratio and the second signal to interference plus noise ratio, a target optimization problem is established, and the target optimization problem takes the signal quality of the legal receiver end as an optimization target; and solving the target optimization problem by using a binary search algorithm and a neural network to obtain a final security coding matrix and a final power allocation scheme, and designing a satellite-ground network OFDM anti-interception waveform based on security coding by using the final security coding matrix and the final power allocation scheme. Therefore, the secrecy performance of the satellite-to-ground link is relatively high, and the computing power resource occupation of the satellite-to-ground fusion network is reduced.

A system can include one or more processors and one or more non-transitory computer-readable media storing computing instructions that, when executed on the one or more processors, cause the one or more processors to perform operations: receiving a new notification; determining, using a binary search algorithm, a number of one or more notifications, wherein an interval of the binary search algorithm comprises a time period between a reclamation pointer and an ingestion pointer; when the number of the one or more notifications is greater than a maximum number of notifications, removing, from a central data store, at least one notification of the one or more notifications; and storing the new notification in the central data store. Other embodiments are described.

According to the anti-noise bi-clustering method and system for the gene expression data, the thought that a seed list is obtained through a longest common subsequence searching method is utilized, the longest approximate common subsequence is searched through an element exchange permitting strategy, interference of noise in a data set on sequence matching can be effectively reduced, and the anti-noise bi-clustering method and system for the gene expression data are provided. The algorithm can still accurately identify the similarity in the gene expression mode in a complex noise environment, so that the accuracy of a bi-clustering result is improved; the binary search algorithm is adopted to determine the insertion interval, the method can fully consider the characteristics of noise data, and compared with a traditional expansion mode, the method can more reasonably process the influence of noise and avoid error expansion caused by the noise, so that the bi-clustering structure is more accurately constructed.

The application relates to a high-speed SAR-ADC circuit with a redundancy algorithm, comprising: a DAC array unit, which samples an input signal and completes a binary search algorithm by utilizing inter-capacitor charge redistribution; a dynamic comparator, which is used for comparing the size of a differential analog input signal, outputting a binary digital signal and completing quantization; a clock logic unit, which is used for providing a sample-and-hold clock, a reset clock and a synchronization clock, and the clock output end of the clock logic unit is connected with the DAC array unit, the comparator, the bit latch and the combination logic unit; and a combination logic unit, which controls signal switching of a capacitor array according to the output result of the comparator, completes conversion of redundant bits and buffers and outputs a quantization code. The application uses an asynchronous SAR-ADC architecture with redundancy, and since the asynchronous SAR-ADC is adopted, the time of each cycle can be fully utilized, the speed is improved, the redundancy method is used, the fault tolerance of conversion is improved, and the precision is improved.

The invention provides an automatic phase error calibration method and system for a self-adaptive control MEMS gyroscope, and the automatic phase error calibration method comprises the following specific steps: estimating the search range of a phase error according to the composition of the phase error and the influence degree of the phase error on the performance of the self-adaptive control gyroscope; taking search parameters and the search range as data input of a phase error binary search algorithm, running the phase error binary search algorithm, and outputting an optimal estimated value of the phase error; according to the optimal estimation value, setting the stage number and the coefficient of a cascaded all-pass filter with an adjustable coefficient to obtain a cascaded filter module; automatic phase calibration of the self-adaptive control MEMS gyroscope is realized through the cascade filter module, so that the estimation precision of a phase error is improved, and the problem of control error divergence caused by unknown phase shift is effectively solved.

This invention provides a microservice optimization method for industrial edge networks based on dynamic orchestration and migration expansion, comprising: abstracting the industrial edge network into an intelligent industrial network model composed of heterogeneous edge nodes and links; modeling industrial application requests as request chains composed of multiple microservices with data dependencies; calculating microservice instance deployment schemes and request routing schemes; statistically analyzing time-varying request flows; and utilizing a method based on... m / m / c This invention utilizes a multivariate performance analysis model of queue networks and a binary search algorithm to analyze and statistically determine the minimum number of cores that satisfy latency constraints. It then dynamically scales and adjusts the core resources of deployed microservice instances. Based on the preliminary dynamic scaling and adjustment results and migration costs, it solves a mixed-integer nonlinear programming migration decision problem to optimize the optimal collaborative deployment and request routing of microservice instances among edge nodes. This invention improves the service continuity and overall energy efficiency of industrial edge network systems.

The present invention discloses a digital signal processing method, which includes signal acquisition, signal preprocessing, matrix transformation, signal modulation and model parameter search. The present invention belongs to the field of digital signal processing technology, and specifically refers to a digital signal processing method. The scheme performs filtering processing on the original signal through equal-interval sampling, periodic denoising processing and designing a lattice wave digital filter. The signal is transformed and decomposed through matrix changes based on orthogonal components and transformations based on fading, thereby extracting signal feature information; signal modulation is realized based on a deep learning model, and the encoder and decoder layers use Conv1D and MaxPool1D blocks to realize spatiotemporal downsampling and dimensionality reduction. The transformer layer introduces an attention mechanism to effectively capture long-range dependencies and intra-sequence correlations; the loss function considers both the reconstruction accuracy of the signal and the classification accuracy; and the optimal model parameters are searched through an improved binary search algorithm.

The present invention discloses a furniture production order management method and system, which relates to the technical field of furniture production management, and includes: collecting relevant data of furniture orders to be processed, and constructing multiple sequential processing chains according to the sequential relationship of furniture processing steps; marking orders, furniture products and processing equipment, and establishing a processing waiting queue; screening out processing steps that need to enter the waiting queue according to the sequential processing chain and the preceding processing task judgment strategy; when a new step is added to the queue, calculating the priority of each step according to the processing sequence adjustment strategy, and performing preliminary sorting; if the priorities are the same, further considering the order category, the furniture category and the preceding step status to adjust the sequence; finally, calculating the processing task amount assigned to each processing equipment by calculating the processing rate of each processing equipment and using a binary search algorithm; ensuring efficient and orderly furniture production.

The invention relates to the technical field of mobile communication network optimization, in particular to a base station position intelligent prediction method and device based on an improved DBSCAN algorithm, and the method comprises the steps: carrying out the rasterization of collected original data and stock base station data, obtaining an effective Enodeb list, carrying out the classification according to an operator and a network type, and obtaining a plurality of effective Enodeb sub-lists; positioning a raster data index of each Enodeb by using a binary search algorithm, extracting latitude and longitude coordinates of all grids under the same Enodeb, and constructing a clustering data list; performing clustering analysis on the raster data in each Enodeb to generate a predicted base station position data table; wherein during clustering analysis, clustering parameters are dynamically adjusted based on the number of cell identifiers under each Enodeb; and quantitatively predicting the matching degree of the base station and the actual base station, screening out the optimal parameter of the improved DBSCAN algorithm, and predicting the position of the base station based on the optimal parameter. Therefore, different base station density scenes are adapted, and the base station position prediction precision and efficiency are improved.

The application provides a method and system for improving the diversity of bit-level autoregressive image generation, and relates to the technical fields of artificial intelligence and computer vision, and has the characteristics that in the sampling process of a bit-level autoregressive image generation model, for each generation scale k, the original prediction logits of all token bits at the scale are obtained; based on the original prediction logits, an adaptive temperature coefficient τk is dynamically solved by a binary search algorithm, so that after the logits are scaled by the τk and normalized by softmax, the difference between the actual average maximum bit probability of the current scale k and the preset target average maximum bit probability Sk is less than the preset tolerance; an adaptive temperature coefficient τk is dynamically determined by binary search, so that after the softmax normalization is applied to the τk. The application has the advantages that the generation diversity is improved by adaptively smoothing the early prediction distribution, and the visual quality is maintained by means of energy-based path search; the method mainly operates in the early stage with low computational overhead, and the inference delay is only slightly increased, and the core design can be extended to similar autoregressive generation models.

The present application provides a method, apparatus, device, storage medium and product for searching strings in memory. The method includes: obtaining a target memory-resident string to be searched; determining a currently satisfied string search condition; if it is determined that the currently satisfied string search condition is a linear search condition, then using a binary search algorithm to search whether the target memory-resident string exists in the stored resident strings in the memory; if it is determined that the currently satisfied string search condition is a combined search condition, then searching whether the target memory-resident string exists in the stored resident strings in the memory based on a hash table corresponding to the stored resident strings and a data structure corresponding to a hash value index in the hash table. Using a binary search algorithm or searching for a target memory-resident string based on a hash table and a data structure corresponding to a hash value index in the hash table can reduce the algorithm's time complexity, improve search efficiency, and control the memory occupied by the stored resident strings.