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10528results about How to "Reduce computational complexity" patented technology

Density evolution based polarization code constructing method and polarization code coding and decoding system

The invention discloses a density evolution based polarization code constructing method and polarization code coding and decoding system. According to the invention, the code length N and the information bit length K of an information code to be processed are obtained, an expectation value set of a log-likelihood ratio probability density function of N bit channels, K bit channels are selected as the information bit channels according to the expectation value set and information bit information index vector quantity is generated; an information bit sequence and a fixed bit sequence are mixed and the mixed bit vector quantity is multiplied by a polarization code for generating a matrix so as to output an encoding sequence; the encoding sequence is modulated and input into a transmission channel and the sequence output by the transmission channel is subjected to decoding operation by adopting a polarization code decoding algorithm, bit error probability and frame error rate of the decoded code are calculated and a design signal to noise ratio is changed, the above operation is repeated until the bit error probability and frame error rate become the minimum. The method and system provided by the invention are suitable for general binary system memoryless channels, the bit error probability and frame error rate are low, the calculation complexity is low and the communication performance of a communication system is improved.
Owner:SHENZHEN UNIV

Moving object detecting and tracing method in complex scene

The present invention discloses method for moving target detection and tracking in a complex scene. The method comprises two steps of multiple moving target detection and multiple moving target tracking: in the multiple moving target detection, a background model based on self adapting nonparametric kernel density estimation is established with the aim at the monitoring of the complex scene, therefore the disturbance of the movement of tiny objects can be effectively suppressed, the target shadow is eliminated, and the multiple moving target is detected; in the multiple moving target tracking, the target model is established, the moving state of the target is confirmed through ''matching matrix'', and corresponding tracking strategy is adopted according to the different movement condition of the target. Target information is ''recovered'' through the probabilistic reasoning method, and the target screening degree of the target is analyzed with the aim at the problem that multiple targets screen mutually. The algorithm of the present invention can well realize the moving target tracking, obtains the trace of the moving target, and has good real time and ability of adapting to the environmental variation. The present invention has wide application range and high accuracy, therefore being a core method for intelligent vision monitoring with versatility.
Owner:HUNAN UNIV

Data-driven lithium ion battery cycle life prediction method based on AR (Autoregressive) model and RPF (Regularized Particle Filtering) algorithm

A data-driven lithium ion battery cycle life prediction method based on an AR (Autoregressive) model and an RPF (Regularized Particle Filtering) algorithm relates to a lithium ion battery cycle life prediction method and belongs to the technical field of data prediction. The invention solves the problems in the existing lithium ion battery cycle life prediction method that the model-based prediction method is complicated in modeling, and parameters are difficult to identify. The data-driven lithium ion battery cycle life prediction method combines time sequence analysis with particle filter method and comprises the following steps: the AR model is firstly utilized to realize the multi-step prediction on battery performance degradation process time sequence data; and then, aiming at the problem of uncertainty expression of the cycle life prediction result, the regularized particle filtering method is introduced, and a lithium ion battery cycle life prediction method framework is proposed. The method proposed by the invention can be used for effectively predicating the cycle life of a lithium ion battery and realizes the output of probability density distribution of the predication result, has good computational efficiency and uncertainty expression ability.
Owner:HARBIN INST OF TECH

Gesture recognition method based on 3D-CNN and convolutional LSTM

The invention discloses a gesture recognition method based on 3D-CNN and convolution LSTM. The method comprises the steps that the length of a video input into 3D-CNN is normalized through a time jitter policy; the normalized video is used as input to be fed to 3D-CNN to study the short-term temporal-spatial features of a gesture; based on the short-term temporal-spatial features extracted by 3D-CNN, the long-term temporal-spatial features of the gesture are studied through a two-layer convolutional LSTM network to eliminate the influence of complex backgrounds on gesture recognition; the dimension of the extracted long-term temporal-spatial features are reduced through a spatial pyramid pooling layer (SPP layer), and at the same time the extracted multi-scale features are fed into the full-connection layer of the network; and finally, after a latter multi-modal fusion method, forecast results without the network are averaged and fused to acquire a final forecast score. According to the invention, by learning the temporal-spatial features of the gesture simultaneously, the short-term temporal-spatial features and the long-term temporal-spatial features are combined through different networks; the network is trained through a batch normalization method; and the efficiency and accuracy of gesture recognition are improved.
Owner:BEIJING UNION UNIVERSITY

Color image three-dimensional reconstruction method based on three-dimensional matching

The invention relates to a color image three-dimensional reconstruction method based on three-dimensional matching, comprising the following steps of: (1) simultaneously and respectively taking an image from proper angles by using two color cameras; (2) respectively calibrating the internal parameter matrixes and the external parameter matrixes of the two cameras; (3) carrying out polar line correction and image transformation according to calibrated data; (4) working out matching cost for each pixel point in the two corrected images by applying a self-adaption weight window algorithm and acquiring an initial parallax image; (5) marking the reliability coefficient of the pixel initial matching result by adopting matching cost reliability detection and left and right consistency verification; (6) carrying out color segmentation on the images through a Mean-Shift algorithm; (7) carrying out global optimization by a selective confidence propagation algorithm on the basis of color segmentation and pixel reliability classification results to obtain a final parallax image; and (8) working out the three-dimensional coordinates of actual object points on the images according to the calibrated data and the matching relation, thereby reconstructing the three-dimensional point cloud of an object.
Owner:南通洁万家纺织有限公司 +1

Method for detecting code similarity based on semantic analysis of program source code

The invention discloses a method for detecting code similarity based on semantic analysis of a program source code, which relates to computer program analyzing technology and a method for detecting complex codes of computer software. The method solves the prior problems of low similarity detection accuracy and high computing complexity on the codes of different syntactic representations and similar semantemes, and also solves the problem of incapability of realizing large-scale program code similarity detection. The method comprises the following steps: resolving two segments of source codes to be detected into two control dependence trees of a system dependence graph respectively and executing basic code standardization respectively; utilizing a measure method to extract candidate similar code control dependence trees of the control dependence trees which are subjected to the basic code standardization; executing an advanced code standardization operation on extracted candidate similar codes; and computing semantic similarity to obtain a similarity result so as to finish the code similarity detection. The method is applied to source code piracy detection, software component library query, software defect detection, program comprehension and the like.
Owner:HARBIN INST OF TECH
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