764 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.

Systems and methods for resource conservation based on query complexity are disclosed. An input query is received (e.g., via a chat interface) and provided to a response classifier, which is a machine-learning classifier that is trained to classify input queries with complexity scores that indicate how difficult it is likely to be for an artificial intelligence (AI) model to generate a response to the input query. If the complexity score exceeds a threshold score, the input query is provided to a first AI model (e.g., a relatively high-complexity AI model having a large number of parameters, relatively long response latencies, and / or other performance characteristics). If the complexity score does not exceed the threshold score, the input query is provided to a second AI model (e.g., a lower-complexity AI model having fewer parameters, shorter response latencies, and / or other differences in performance characteristics relative to the first AI model).

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 discloses a hybrid heterogeneous cloud workflow scheduling method based on reinforcement learning, and belongs to the technical field of cloud computing. The method comprises the following steps: aiming at a cloud workflow scheduling problem, by taking minimization of completion time as a target and taking cost and resources as constraints, a three-dimensional collaborative constraint model is constructed, and the cost constraints comprise server-free function budget and virtual machine budget; integrating the hyper-heuristic framework into a reinforcement learning algorithm; an improved reinforcement learning algorithm is adopted to solve the cloud workflow scheduling problem, optimal execution resources are selected, and an optimal scheduling scheme is obtained; and performing real-time scheduling according to the optimal scheduling scheme, and introducing a deviation feedback mechanism to monitor an execution error in real time. According to the method, the workflow scheduling problem is decomposed into a closed-loop optimization process of state perception and action decision, dynamic environment perception, multi-target tradeoff and online strategy optimization are deeply fused, the global search function is achieved, local optimization can be achieved, the algorithm complexity is low, and robustness is high.

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.

In an aspect, digital communication coding methods (or simply coding methods) are provided, said methods comprising providing families of quasi-cyclic low-density parity check, LDPC, codes each represented by a single equation. Said single equation is derived from a geometry whose nature implies good error correcting properties for each of the LDPC codes and allows quasi-cyclic parity check matrices to be constructed for geometric LDPC codes of exceedingly long length, up to and exceeding four hundred thousand bits. The construction of such check matrices is not possible by any other known method. The LDPC codes have different lengths and different rates and the families of LDPC codes are provided with a guarantee of minimum distance. The geometric and quasi-cyclic properties of the LDPC codes allow low complexity decoding with very low frame error rates. Systems, computing systems and computer programs suitable to perform such coding methods are also provided.

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.

The invention discloses a low-complexity MSK coded modulation system phase synchronization receiving system and method, and relates to the technical field of continuous phase modulation. On one hand, an original message is coded and modulated by constructing a pre-coding mode, a receiving end realizes optimal sampling point extraction at the minimum intersymbol crosstalk moment after phase decoupling frequency conversion processing, MSK is converted into BPSK-like modulation, oversampling processing is not needed, modulation phase components of a receiving synchronization section can be offset, and the modulation efficiency of the receiving synchronization section is improved; therefore, accurate estimation of Doppler phase and frequency is realized, and the anti-Doppler capability is improved. On the other hand, coherent demodulation soft information is directly output after the real part of the signal subjected to Doppler frequency offset and phase offset compensation is obtained, the complexity of the demodulation algorithm is low, the performance of the demodulation algorithm is equivalent to that of BPSK, the demodulation algorithm is remarkably superior to that of an MSK optimal demodulation receiver in a low signal-to-noise ratio region, and the demodulation algorithm is particularly suitable for a bit interleaving coding modulation system combined with channel coding and has a wide application prospect. And reliable transmission under a low signal-to-noise ratio can be realized.

The invention provides a signaling transmission method and device and a storage medium, relates to the technical field of communication, and is used for realizing efficient transmission of signaling in a low-complexity system. The method comprises the following steps: receiving a preamble sequence, wherein the preamble sequence comprises a first part and a second part; signaling is received based on the preamble sequence.

The invention relates to the technical field of point cloud compression coding, and discloses a point cloud projection video low-complexity coding optimization method based on depth structure prediction, which comprises the following steps of: 1, extracting an occupied video, a geometric video and an attribute video of a dynamic point cloud sequence under different code rates; step 2, extracting feature information of a near-layer frame to perform feature enhancement to obtain near-layer enhancement features # imgabs0 # corresponding to the occupancy graph, the attribute graph and the geometric graph; step 3, extracting feature information of a far-layer frame to perform feature enhancement to obtain near-layer enhancement features # imgabs0 # corresponding to the occupancy graph, the attribute graph and the geometric graph; 4, performing feature enhancement on a projection image block according to feature information of different types of frames, and realizing more accurate depth division structure prediction; and step 5, realizing low-complexity point cloud projection video coding acceleration by combining a depth division structure prediction result with an optimized coding algorithm.

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 discloses a random pre-coding multiple-input multiple-output orthogonal frequency division multiplexing wireless communication method and system, a transmitting end enables each symbol to fully utilize all sub-channels through random unitary transformation and random compression transformation, and at a receiving end, by means of a block diagonal channel matrix of MIMO-OFDM on a frequency domain, all sub-channels of the MIMO-OFDM are fully utilized, so that the random pre-coding multiple-input multiple-output orthogonal frequency division multiplexing wireless communication is realized. A cross-domain orthogonal approximate information transfer (CD-OAMP) detector is designed, which can perform signal detection with extremely low complexity, and can be optimal for replica maximum posteriori (MAP). The RP-MIMO-OFDM performance of the CD-OAMP detector exceeds the performance of MIMO-OFDM, the performance of MIMO-OTFS and the performance of MIMO-AFDM, the performance of RP-MIMO-OFDM is close to the performance of MIMO-IFDM, and the complexity is lower.

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 discloses an interpretable model training method based on sensitivity analysis, and belongs to the technical field of specific calculation models, and the method comprises the steps: carrying out model training according to training set sample data to obtain a baseline model, evaluating the baseline model according to test set sample data, and recording a reference prediction index, the sample data comprising a plurality of variables; according to the training set sample data and the test set sample data of which any variable is removed, carrying out model retraining and evaluation to obtain a prediction index corresponding to the removed variable; and according to the prediction index and the reference prediction index, obtaining sensitivity of removing variables, and according to the sensitivity, obtaining a plurality of key variables for training of an interpretable model. According to the method, key variables are screened through sensitivity analysis, an interpretable model is constructed, a black box model is replaced, the influence of the variables on prediction is quantified, and the model stability is improved; the complexity and the over-fitting risk are reduced by eliminating redundant variables, and the consumption of computing resources is reduced.

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 a low-complexity random access channel coding and decoding method based on a sparse regression code, which belongs to the technical field of random access channel coding and decoding, and comprises the following steps of: acquiring to-be-sent information of all active users through a sending end; wherein the information to be sent comprises identity identification information and message information; encoding and transmitting the to-be-sent information, and repeating a plurality of stages; receiving signals are obtained through a receiving end, and whether the whole transmission process is finished after the tth stage is completed or not is judged; wherein the obtained receiving signal transmitted in the first stage is the superposition of a plurality of identity identification sub-code words and noise; the received signals transmitted from the second stage to the t-th stage are all superposition of a plurality of message sub-code words and noise; if the transmission is finished, determining the number of active users according to the number of the transmission stages, and decoding the received signals of the first stage to obtain identity information of all the active users; and decoding the received signals transmitted from the second stage to the t-th stage to obtain message information of all active users.

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 invention discloses a method for designing a double-iteration Turbo equalizer of an OTFS-MIMO-ISAC system, and the method comprises the steps: carrying out the sparse processing of covariance matrix inversion, and reducing the matrix inversion cost of conventional MMSE equalization through linear complexity derivation; the sparse linear system is solved through the TFQMR algorithm to reduce the complexity of the first iteration, and a sparse approximate inverse matrix is generated in the subsequent iteration through the FSPAI algorithm to further realize the balance between the calculation efficiency and the performance; and dynamically optimizing channel information by adopting an iterative channel estimation method and utilizing MMSE (Minimum Mean Square Error) equilibrium feedback. Through outer iteration and inner iteration, the symbol estimation precision is gradually improved, meanwhile, the calculation complexity is reduced, and a low-complexity and high-precision equalization and channel estimation solution is provided for a high-mobility wireless communication system.

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.

The invention discloses a power amplifier digital pre-distortion optimization method based on a complex convolutional neural network, and the method comprises the following steps: S1, collecting a plurality of groups of digital signals before and after passing through a power amplifier PA, and forming a sample set; s2, preprocessing the data in the sample set; s3, constructing a complex number time delay convolutional neural network containing a linear auxiliary branch and a nonlinear model as a digital pre-distortion model of the power amplifier; s4, training the digital pre-distortion model of the power amplifier by using the preprocessed data in the sample set to obtain maturely trained digital pre-distortion model parameters; and S5, when the digital pre-distortion of the power amplifier is actually carried out, sending a to-be-sent digital signal to the maturely trained digital pre-distortion model for processing. According to the method, the linearization capability is remarkably improved by introducing complex field processing and auxiliary linear branches while the low complexity characteristic is kept.

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 invention discloses a channel estimation method of an active RIS-assisted millimeter wave MIMO system, which researches the channel estimation problem of the active RIS-assisted millimeter wave MIMO system in a multipath environment, realizes decoupling of a departure angle at UE and cascade channel parameters by designing a specific UE pilot frequency sequence and RIS phase configuration, and improves the channel estimation accuracy. Making it possible to estimate an angle of arrival at the BS, an angle of departure at the UE, and cascade channel parameters, respectively; in order to solve the challenge of estimating the cascade channel parameters, a low-complexity algorithm for decoupling the two-dimensional cascade channel parameters is developed, and the estimation process is converted into multiple times of one-dimensional search by utilizing a greedy algorithm principle, so that the calculation complexity is greatly reduced.

Example embodiments of the present disclosure relate to a terminal device, a network device, methods, apparatuses and a computer readable storage medium for updating information for uplink synchronization. The terminal device determines a first threshold duration for first information for uplink synchronization and a second threshold duration for second information for the uplink synchronization; and performs a first procedure for updating the first information and a second procedure for updating the second information based on: determining that a validity duration of one piece of information expires and a remaining validity duration of the other piece of information is shorter than corresponding threshold duration. As such, the two procedures updating the first information and the second information may be aligned with each other, thus the complexity can be reduced, the power consumption can be reduced, and the communication efficiency may be improved.

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 provides a control information transmission method of Internet of Things equipment and related equipment, and relates to the technical field of environment Internet of Things communication. The method comprises the steps that control information of the Internet of Things equipment is configured or indicated through a high layer and / or a physical layer, the control information comprises D2R control information or R2D control information, and the D2R control information or the R2D control information comprises at least one of high layer control information and physical layer control information. According to the invention, environmental Internet of Things communication can be realized, and the Internet of Things equipment can receive the control information and execute the corresponding operation, so that low cost, low power consumption and low complexity are realized.