542 results about "Low complexity" patented technology

The invention discloses a water quality time sequence prediction method of an SSA-VMD-LSTM-XGBoost hybrid model, and belongs to the technical field of water quality monitoring and prediction. Comprising the following steps: (1) data preparation and preprocessing; (2) optimizing the water quality time sequence decomposition of the VMD based on SSA: optimizing a penalty factor and a modal number of the VMD by adopting a sparrow search algorithm (SSA), and decomposing the water quality time sequence into a plurality of sub-components with high stability and low complexity by utilizing the optimized VMD; (3) construction and training of an LSTM-XGBoost hybrid prediction model: constructing a hybrid prediction model fusing long-short term memory (LSTM) and extreme gradient boost (XGBoost), inputting a high-frequency component into the LSTM model, inputting a low-frequency component into the XGBoost model, and finally performing superposition and integration on prediction results of the models; and (4) multi-component prediction result integration and performance verification. According to the method, adaptive optimization of VMD parameters is realized through SSA, the feature extraction and time sequence modeling capability is improved by combining the advantages of LSTM and XGBoost, and the prediction precision and stability of the water quality time sequence are effectively improved.

The invention discloses an efficient optical flow estimation method and device based on Mama, and the method comprises the steps: carrying out the normalization and size alignment of two adjacent frames of images, and extracting the dense features of a fixed down-sampling rate through a shared weight convolution encoder; the two-frame features are sent to a multi-level feature enhancement module, an intra-frame modeling unit and a cross-frame interaction unit are cascaded and matched with channel reforming and residual error correction, and enhanced features are obtained; constructing a four-dimensional cost body on a low resolution, performing probability normalization along a target coordinate dimension, weighting a target coordinate grid according to a probability to obtain a corresponding coordinate, and subtracting the corresponding coordinate from a source coordinate to obtain an initial optical flow; and carrying out attention-guided space fusion on the initial optical flow and context and local correlation, sending the fused optical flow to a differential Mama-based autoregressive refinement module, carrying out iterative updating according to a small number of fixed steps, recovering to a target resolution through convex combination up-sampling, and outputting a final optical flow. According to the method, the optical flow field can be accurately estimated under the conditions of low complexity and low time delay.

The invention discloses a configurable number-theory transformation parallel computing acceleration method and device for a post quantum cryptographic algorithm, and relates to the technical field of cryptographic algorithms. The number theory transformation is a calculation bottleneck in lattice-based post-quantum cryptography and PQC; a hardware accelerator specially designed for number theory transformation (NTT) is an effective solution for improving the execution speed. At present, a mainstream design neglects the influence of the scale of a calculation array, so that the design of an NTT calculation circuit is poor in flexibility and low in memory utilization rate, and a two-dimensional reconfigurable number theory transformation acceleration circuit is provided; the method is applied to a key generation stage, an encryption stage and a decryption stage of the post-quantum cryptographic algorithm. The NTT reconfigurable computing circuit provided by the invention can keep the utilization rate of hardware resources, and is suitable for mobile terminal equipment with limited resources; the NTT circuit adopts a low-complexity memory mapping scheme, so that the address control logic is greatly simplified, and the hardware overhead is reduced.

The invention discloses a power adaptive digital pre-distortion method, system and device based on sparse GRU and a medium. The method comprises the steps that input and output signals under different powers are collected, a composite feature vector is constructed through amplitude normalization and phase alignment, and a pre-distortion training target is generated in combination with indirect learning; constructing a sparse GRU neural network, introducing L1 regularization constraint, and obtaining a sparse pre-distortion model through joint optimization of mean square error and sparse constraint; partial weight updating is realized based on power grading, and weight fusion output is carried out during power interval switching so as to complete power adaptive optimization; pruning and compressing the sparse GRU model and then deploying the sparse GRU model in a pre-distortion module to compensate the nonlinearity of the power amplifier; according to the method, the model complexity is reduced through rarefaction, the dynamic working condition stability is improved through a power adaptive mechanism, pruning compression adapts to low-power-consumption hardware, high precision, low complexity and adaptive capacity are considered, and the method is suitable for the low-power-consumption and high-performance requirements of a broadband wireless communication system.

The invention belongs to the technical field of communication, and particularly relates to a multiplication active code decoding method based on an SO-ORBGRAND decoder. The SO-ORBGRAND decoder outputs soft information by calculating a correct posterior probability of a conjecture code word sequence, and high-performance decoding is realized through soft information exchange and optimization processing between the row decoder and the column decoder. In the iteration process, a method for judging the validity of the code word through the check matrix is designed by utilizing the polarization characteristic of the multiplication active code, so that the iteration is supported to jump out in advance to reduce the complexity. The invention provides a multiplication active code decoding algorithm based on an SO-ORBGRAND decoder, and compared with various non-system multiplication active code decoding algorithms and the performance of traditional long-code polarization codes, the method has remarkable advantages in error correction performance; a method for judging the validity of the code word through the check matrix by utilizing the polarization characteristic design of the multiplication positive code is provided, the complexity is reduced while the judgment success rate is improved, and the implementation overhead is reduced.

The invention provides a parallel policy determination method, electronic equipment, a storage medium and a program product. The method comprises the following steps: determining cluster communication information, model calculation information and model resource occupation information according to information of a cluster used when a large model is trained and a structure of the large model; according to the cluster communication information and the model calculation information, modeling training time required by large model training to obtain a training time model; according to the model resource occupation information, carrying out modeling on resources occupied by large model training to obtain a resource occupation model; and according to the training time model and the resource occupation model, determining a target parallel strategy from multiple groups of parallel strategies as a parallel strategy used during large model training. Thus, by constructing the training time model and the resource occupancy model, the optimal parallel strategy can be automatically screened out from the multiple groups of parallel strategies, manual intervention is not needed, and therefore efficiency can be improved, and complexity can be reduced.

This invention discloses a low-complexity decoding method for LDPC-Hadamard codes based on a prototype diagram, belonging to the field of digital signal processing. The implementation method is as follows: information bits are LDPC encoded, and then the constraint relationship of the check nodes of the LDPC code is encoded into Hadamard code to obtain the prototype diagram of the LDPC-Hadamard code; the encoded codewords are transmitted and received through a channel, and the PVN and HCN nodes are initialized with the received information; Hadamard decoding is performed using a symbol-by-symbol maximum a posteriori probability decoding algorithm, and DFHT approximation is used to reduce decoding complexity; the decoded information is transmitted to the PVN nodes; the updated HCN node information is summed with the information from the previous iteration, and the summation result is used to determine the decoding; a decoding decision is made on the PVN information, and decoding is performed. This invention combines LDPC encoding, Hadamard encoding, and Max-Log approximation calculation methods to reduce decoding complexity and enhance the stability and reliability of the communication system.

The invention provides a business process model instance construction method and device based on a data structure, and the method comprises the steps: carrying out the assembly according to a JSON structure and a business process drawn by a user, and generating a business process JSON data structure; performing data serialization on the business process JSON data structure to generate a database process draft basic information extension table; in response to a release process instruction input by a user, performing data deserialization according to the database process draft basic information extension table, generating business process series information and updating a business process series table; in response to a process starting instruction input by a user, determining a business process series information instance from the business process series table; according to the business process model architecture, the business process series information instances are spliced, and the business process model instance is generated, so that expansibility, maintainability and flexibility can be improved, front-end load work is reduced, complexity and error risks are reduced, and response speed is increased.

The invention provides a programmable frequency control array radar waveform generation system and method based on an FPGA, and belongs to the technical field of radar systems and digital signal processing. In order to solve the technical problems of complex hardware system, inflexible parameter adjustment and poor multi-channel synchronism of the traditional frequency control array radar, the invention provides an integrated high-performance solution. The system adopts an FPGA (Field Programmable Gate Array) architecture of an integrated processing system (PS) and programmable logic (PL). The method comprises the following steps: a PS end receives waveform control parameters of an upper computer through a communication interface and transmits the waveform control parameters to a PL end; and a plurality of parallel direct digital frequency synthesizer (DDS) modules in the PL end synchronously generate multi-channel digital baseband signals with programmable frequency offset at high precision according to the parameters under the unified driving of the FPGA global clock network. And the digital signal is subjected to digital-to-analog conversion and radio frequency front-end processing to finally form a transmitting wave beam. According to the invention, flexible programmability of parameters is realized by utilizing a PS-PL collaborative architecture, the synchronization precision of multi-channel signals is remarkably improved through a global clock network and a parallel DDS module generated in the FPGA, and meanwhile, the system has the advantages of high integration level and low complexity.

A switched-element digital-to-analog converter (DAC) circuit for use, for example, in a successive-approximation register, SAR, analog-to-digital converter, ADC. The DAC circuit comprises a pool of unary circuit elements (410), each having a common nominal weighting value, and switching (420) and multiplexer (430) arrangements configured so that each unary circuit element (410) in the pool can be independently associated with any one of two or more bits of the switched-element DAC.

The invention discloses an answer generation method based on a thinking chain, a product, equipment and a medium, and relates to the technical field of calculation data processing, and the method comprises the steps: constructing a self-adaptive thinking chain generation mechanism based on reward driving based on the matching degree between the complexity score of question data and the quantized value of the length of the thinking chain, therefore, the strategy model can autonomously learn a strategy that a high-complexity problem generates a long thinking chain and a low-complexity problem generates a short thinking chain in a training stage, so that the technical problems of waste of model computing resources and aggravation of system response delay caused by adoption of an undifferentiated thinking chain generation strategy in related technologies are solved; the beneficial effects of reducing the redundancy calculation overhead, improving the system response efficiency and realizing on-demand allocation of the calculation resources according to the problem difficulty are achieved.

The invention discloses a frequency offset estimation method and device, electronic equipment and a storage medium, and relates to the technical field of communication. The method comprises the following steps: receiving a baseband spread spectrum signal from a low earth orbit satellite to obtain a received signal; performing segmented sweep frequency compensation on the received signal to obtain a compensated measured signal; despreading and descrambling the compensated measured signal by using prior information determined from the received signal, and completing coarse frequency offset estimation on the measured signal despread and descrambled for the first time; and de-spreading and descrambling the signal data after the coarse frequency offset estimation again, and finishing fine frequency offset estimation on the signal data after the second time of de-spreading and descrambling. According to the invention, prior information is introduced to directly lock and track a specified target beam signal, so that the directionality and efficiency of measurement are remarkably improved; by designing a low-complexity signal processing flow, the algorithm burden can be remarkably reduced, it is ensured that adjacent satellite beam frequency offset estimation is rapidly completed in service proceeding, and the real-time requirement of seamless switching is met.

The present invention provides a method for low-complex estimation of Direction of Arrival (DoA) and Time of Arrival (ToA) in multi-antenna-based communication comprising detecting overlapped paths between a Mobile Station (MS) and a Base Station (BS) operating under said multi-antenna-based communication with scatters present therein involving channel paths represented as Channel Impulse Response (CIR) defined with channel signatures including delay and angle steering vectors, decoupling the channel paths in delay and angle-domain and separately estimate the DoA and ToA of each path with a low computational complexity which is based on one-dimensional low-index based rotation methodology and finally pairing the DoA and the ToA.

An apparatus comprising an interface and a processor. The interface may be configured to receive pixel data of an environment. The processor may be configured to process the pixel data arranged as video frames, generate a luminance distribution map of the video frames in response to a low-pass filter operation, determine a plurality of defogging intensity weights for the luminance distribution map, perform adaptive smoothing to each of the plurality of defogging intensity weights, and generate defogged video frames in response to the video frames and the plurality of defogging intensity weights with the adaptive smoothing. The plurality of defogging intensity weights may each correspond to one of a plurality of luminance intervals of the luminance distribution map. The adaptive smoothing may be configured to prevent brightness differences in the defogged video frames.

The present invention discloses a low-complex, reliable multidimensional orthogonal time-frequency space (ND-OTFS) modulation-based communication system for uplink and downlink wireless communication between resource-constrained Internet of Things (IoT) and machine-to-machine (M2M) devices comprising at least one transmitter configured to transmit bit stream involving N-Dimensional signal mapper and OTFS frame and at least one receiver configured to be integrated into said IoT or M2M devices, featuring a low-complexity detector for receiving the transmitted bit stream.

The invention provides a live broadcast long video editing method and device based on memory perception collaboration, and relates to the technical field of image processing and video editing. Voice, subtitles and picture actions are analyzed in a linkage mode on a unified time grid, low-complexity characterization of a long video is achieved through an efficient perception module, and the effect of editing the long video is achieved. Cross-fragment core characters, events and semantic clues are precipitated through long-term memory of an entity center, and current perception is fed back through memory retrieval so as to enhance consistency and robustness; on the basis, a three-mode fusion wonderness score is generated, interval optimization and boundary refinement with duration budget constraint are executed, and finally, an editing decision list is output and quickly spliced into a high-quality finely-cut video. According to the invention, the problems of large quantity of long-time live broadcast materials, low efficiency of manual reviewing and editing and easy leakage of wonderful fragments are solved, and the later production efficiency and the quality of the live broadcast content are remarkably improved.

The invention discloses a pseudo-ginseng flower maturity detection method based on an improved RT-DETR model, and belongs to the field of agricultural intelligent detection and deep learning application, the pseudo-ginseng flower maturity detection method is an improvement of a deep learning algorithm taking RT-DETR as a baseline model, and mainly performs optimization and enhancement on three aspects of backbone network replacement, neck network optimization and AIFI module partial replacement. On the premise of ensuring the detection speed, the lightweight detection model with lower complexity and higher detection precision is successfully realized. The model provides a core detection method for intelligent picking of panax notoginseng flowers, fills the blank of small-target and easily-confused growth stage detection technologies in a complex field environment, has important engineering application value, and promotes automatic upgrading of the panax notoginseng industry.

The invention discloses a multi-sensor fusion data processing method and system, and the method comprises the steps: receiving the signal information of a plurality of sensors, extracting original data and manual features, carrying out the combined learning of a sensor specific auto-encoder through output label knowledge, fusing the weight of the auto-encoder and the weight of a classifier, so as to learn discriminative features, and further classifying the test data. The system comprises a memory, a communication interface and a hardware processor and is used for executing the operations. According to the method, discriminative features are learned through a joint optimization technology, compared with the prior art, the performance is better, the complexity is lower, good accuracy and robustness are shown in scenes such as bearing fault detection, and the method can be applied to multiple fields such as remote sensing and industrial automation.

A reduced number of interleaved encoded bits is obtained by encoding input bits by a polar code and interleaving a subset of the encoded bits obtained by the encoding. The polar code comprises a number of bit indices for placing bit values before encoding, including a first set of bit indices for placing values of the input bits and a second set of bit indices for placing a predetermined bit value. The first set of bit indices comprises a first subset of bit indices and a second subset of bit indices. The subset of the encoded bits corresponds to the second subset of the bit indices, and is for reducing the number of the encoded bits. An input bit value placed on both a first bit index in the first subset and a second bit index in the second subset, and the second bit index is based on the interleaving.

The invention discloses a dynamic beam hopping and resource allocation method for NGSO satellite security communication, and belongs to the field of sixth-generation mobile communication security communication and wireless resource allocation. According to the method, significant non-uniformity of distribution of ground flow requirements in a time domain and a space domain is considered, and a satellite-ground security communication network dynamic beam hopping and resource allocation problem model is constructed by considering ground user flow requirements and composition elements and channel characteristics of an NGSO multi-beam satellite network. Through joint optimization of satellite hopping beam scheduling, power resource allocation and auxiliary interference unmanned aerial vehicle deployment strategies, service requirements of different users and ground eavesdropping environments are dynamically adapted, and the safety throughput and queue delay fairness of the system are improved. According to the method, mixed integer linear programming modeling is adopted, and a low-complexity approximation algorithm is combined, so that the method not only has optimality guarantee, but also can be deployed and operated in an actual satellite communication system, and thus unification of secure communication and efficient resource scheduling is realized.

The invention provides a multi-channel data alignment method and device based on delay compensation. The method comprises the following steps: detecting an alignment mark in target data of a data channel by applying an alignment mark detection module; corresponding data reconstruction modules are arranged on the multiple data channels, and the data reconstruction modules are used for reconstructing the target data, so that the data of the data channels are aligned and marked at the same position in one beat of data after being reconstructed; the data calibration module receives the data output by the plurality of cache modules, detects the delay deviation among the data of the plurality of data channels, outputs the delay deviation to the delay matrix module, and detects the delay deviation among the target data of the plurality of data channels, and the delay matrix module controls the time for each cache module to transmit the data to the data calibration module. The invention further provides a device for implementing the method. According to the invention, multi-channel data alignment can be flexibly realized with low complexity.

A device for decoding encoded video data is configured to determine, from the encoded video data, a block of a picture; apply a neural network (NN)-based filter process to the block to generate a filtered block, wherein to apply the NN-based filter process, the processing circuitry is configured to process a first input channel comprising sample data in a transform domain and process a second input channel comprising context data in a non-transform domain; determine a decoded version of the block based on the filtered block; and output a decoded version of the picture comprising the decoded version of the block.

The invention belongs to the technical field of low earth orbit satellite communication, and particularly relates to a low earth orbit satellite large-scale hopping beam efficient scheduling method and system based on an interference approximation model. According to the method, downlink beam resources of a multi-beam low-orbit satellite are used as research objects, and the problems that in existing large-scale and long-period beam scheduling, the performance evaluation complexity of a beam scheduling strategy is high, and the complexity of a beam scheduling algorithm is rapidly increased along with the increase of variable dimensions are solved. The invention provides low-complexity design and application based on an inter-beam interference approximation model, the inter-beam interference approximation model is introduced from a probability perspective, a rapid performance evaluation method is designed, and a low-complexity scheduling method is designed for two typical low-orbit satellite beam scheduling problems by utilizing an introduced beam activation intensity concept.

The application provides a uniform plane array FDA-MIMO three-dimensional target positioning method and system based on complete decoupling atomic norm minimization. The method converts the problem into a semi-positive programming solution by constructing a low-dimensional observation matrix and using complete decoupling atomic norm, and realizes joint estimation of distance, pitch angle and azimuth angle through Vandermonde decomposition. Compared with high complexity algorithms (VANM, etc.), the application significantly reduces the calculation amount by decomposing the Toeplitz matrix, and improves the single snapshot precision by using the multi-slice constraint mechanism. Compared with low complexity algorithms (3D-DANM), the application introduces an auxiliary variable matrix to restore the distance-angle coupling structure, avoids the performance loss caused by excessive relaxation, and significantly improves the estimation accuracy and multi-target resolution capability while ensuring the calculation efficiency.

The invention belongs to the field of signal processing algorithms, and provides a phase loss sparse low-rank signal recovery method based on convex programming. According to the method, through convex relaxation and anchor regression, a convex optimization frame based on an original parameter space is provided for the first time aiming at the problem of simultaneous sparse low-rank phase loss matrix signal recovery, the frame is used for recovering a simultaneous sparse low-rank matrix signal from phase loss observation data, and the frame works in an original space domain of an unknown variable. And aiming at the convex frame, a low-complexity alternating direction multiplier minimum method is developed. The sparse low-rank phase loss signal recovery method is a first sparse low-rank phase loss matrix signal recovery method based on convex optimization and in an original parameter space, and the calculation complexity is very low.

The present disclosure provides a flow detection method, device, electronic device and storage medium, which relate to the fields of computer technology such as the Internet and big data. The specific implementation scheme is: obtaining the business flow data to be detected, the corresponding detection dimensions and statistical indicators; determining multiple dimension values ​​of the detection dimensions and determining multiple index values ​​of the statistical indicators; based on the multiple dimension values ​​and the multiple index values, aggregating the business flow data to obtain the flow distribution data of each dimension value under the multiple index values; determining the correlation between the flow distribution data of each dimension value under the multiple index values, and determining the target business flow data in the business flow data based on the correlation. In this way, it is achieved that the target business flow data with abnormalities can be detected from the business flow data to be detected, and it has strong versatility, low complexity and high detection efficiency.

The application provides a channel coding identification method of an LDPC code, comprising the following steps: remodeling a first path vector of a kth ant in an ith iteration into a first base matrix, and obtaining a first check matrix based on the first base matrix; determining whether the first check matrix satisfies a preset constraint condition; in response to the first check matrix satisfying the preset constraint condition, determining a second path vector corresponding to an elite ant in the ith iteration; and determining an identification result based on the second path vector. The method can avoid searching all vectors in a large space, reduce complexity, and has a high identification rate.

This application relates to the field of fintech and discloses a dynamic hybrid parsing and deterministic verification system and method for fuzzy bond instructions. The system constructs structured data through an instruction preprocessing module; a routing decision module calculates complexity scores based on structure, semantics, and business characteristics, and generates path selection instructions using a resource-aware dual-threshold strategy; a hybrid parsing module responds to instructions, employing a rule engine to handle low-complexity tasks and a large-scale model with enhanced retrieval to handle highly ambiguous tasks; a fallback verification module performs confidence-weighted integration and logical consistency checks, and repairs anomalies through issuer set operations and edit distance matching; a mapping generation module constructs standard query statements using an abstract syntax tree; and a closed-loop optimization module dynamically updates parameters based on user interaction feedback. This invention effectively balances computational efficiency and parsing accuracy, eliminates model illusion risks, and achieves adaptive evolution of the system.

The present embodiments disclose devices, methods, apparatuses and computer readable storage media of low complexity beamforming. The method comprises determining, at a network device, a channel covariance matrix and at least one signature vector, the at least one signature vector characterizing features of a signal associated with the terminal device; constructing one or more beam sets based on the channel covariance matrix and the at least one signature vector; selecting a predefined number of beams from the one or more beam sets; and performing a transmission to the terminal device based on a target beamforming matrix determined at least based on the predefined number of beams.