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970results about How to "Reduced characteristics" 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

Method for preparing super-hydrophobic antireflex micron and nano composite structure surface

The invention belongs to the technical field of preparing the surface of a composite structure, and in particular relates to a method for preparing super-hydrophobic antireflective silicon surface with a micron and nanometer composite structure. The method comprises the following steps: cleaning a silicon chip; preparing a micron-level silicon island and a gridding structure on the surface of the silicon chip; carrying out catalytic etching taking silver or aurum nanoparticles as blockage; obtaining the surface of the micron and nanometer composite structure; and carrying out chemical modification of the surface of the composite structure. A static contact angle between the super-hydrophobic antireflective material surface prepared by the method and water is more than 150 degrees, and a static rolling angle of water is less than 3 degrees. The surface has superior antireflective performance, and in particular, the light reflectivity within the wavelength range between 800 and 1,100 nm is less than 3 percent. With application of the method, the super-hydrophobic antireflective silicon surface of the micron and nanometer composite structure can be produced on scale, can be widely applied to a solar cell, a microfluidic chip, a photoelectric device, and the like, and has good industrial application prospect.
Owner:JILIN UNIV

Track and convolutional neural network feature extraction-based behavior identification method

The invention discloses a track and convolutional neural network feature extraction-based behavior identification method, and mainly solves the problems of computing redundancy and low classification accuracy caused by complex human behavior video contents and sparse features. The method comprises the steps of inputting image video data; down-sampling pixel points in a video frame; deleting uniform region sampling points; extracting a track; extracting convolutional layer features by utilizing a convolutional neural network; extracting track constraint-based convolutional features in combination with the track and the convolutional layer features; extracting stack type local Fisher vector features according to the track constraint-based convolutional features; performing compression transformation on the stack type local Fisher vector features; training a support vector machine model by utilizing final stack type local Fisher vector features; and performing human behavior identification and classification. According to the method, relatively high and stable classification accuracy can be obtained by adopting a method for combining multilevel Fisher vectors with convolutional track feature descriptors; and the method can be widely applied to the fields of man-machine interaction, virtual reality, video monitoring and the like.
Owner:XIDIAN UNIV

Commodity property characteristic word clustering method

The present invention relates to a commodity property characteristic word clustering method. The method comprises the following steps: A1: obtaining comment texts of a target commodity from related e-commerce websites, and performing data preprocessing; A2: selecting a comment text containing commodity property characteristic words, performing manual annotation on the commodity property characteristic words, and using the manually annotated commodity property characteristic words as a training sample of an obtained part-of-speech template; A3: training the part-of-speech template according to the manually annotated data in the A2; A4: using data obtained in the A1 to train a language model, thereby obtaining a word vector representation; and A5: using a word vector obtained in the A4 to perform clustering on the commodity property characteristic words obtained in the A3, thereby obtaining a final property characteristic word set of the target commodity. The commodity property characteristic word clustering method provided by the present invention can be applied to a commodity recommendation system based on a commodity comment text. The number of commodity property characteristic words can be reduced by clustering, so that characteristic dimensions and characteristic sparsity are reduced, and the designed recommendation system is faster and more accurate.
Owner:SHENZHEN GRADUATE SCHOOL TSINGHUA UNIV
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