Special purpose neural net computer system for pattern recognition and application method

A computer system, neural network technology, applied in character and pattern recognition, biological neural network model, computer parts and other directions, can solve the problem of high false recognition rate

Active Publication Date: 2005-11-23
INST OF SEMICONDUCTORS - CHINESE ACAD OF SCI
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AI Technical Summary

Problems solved by technology

[0005] The object of the present invention is to provide a special neural network computer system for pattern recognition and its application method, practice the theory of bionic pattern recognition, improve the sample recognition rate of the pattern recognition system, overcome the high misrecognition rate of untrained samples in traditional pattern recognition and the addition of New samples require retraining of all samples

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  • Special purpose neural net computer system for pattern recognition and application method
  • Special purpose neural net computer system for pattern recognition and application method
  • Special purpose neural net computer system for pattern recognition and application method

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Embodiment

[0044] The application example of the special neural network computer system for pattern recognition of the present invention is required to perform recognition demonstration on physical models with different angles on the horizontal plane. The collection of samples is to use the microcomputer to observe the collected Bmp files from different directions for screening and sorting to form a training sample set S={S i '|i=0...j}. Then, the special neural network computer system for pattern recognition of the present invention performs feature extraction on the samples in the training sample set, and each sample image obtains a 256-dimensional feature vector. Since the observation directions are all horizontal, it can be said that the change of direction has only one variable. Therefore, the distribution of sample points in the feature space is a one-dimensional manifold distribution Pa. Therefore, we use the method of super-sausage sub-coverage to approximately construct the app...

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Abstract

The invention relates to a neural net computer system and its method of mode identification single-purpose which comprises: a bus, a storage part to provide data storage space, an arithmetic / logical calculation and control part to do arithmetic / logical calculation, and controls the operation and data exchanging of other parts by bus control system, a neural net hardware which receives data from storage part to do arithmetic / logical calculation through bus according to the order of arithmetic / logical calculation and control part, and stores the results into storage part, an environment interface part which obtains information by the order of arithmetic / logical calculation and control part or expresses system operation results by voice or other modes.

Description

technical field [0001] The invention belongs to the field of computers, and more specifically relates to a special neural network computer system for pattern recognition and an application method. Background technique [0002] The development of pattern recognition represented by Fisher and Vapnik has a history of several decades and has achieved remarkable results. However, these traditional pattern recognition methods only pay attention to the "division" between various sample types, and do not pay attention to the characteristics of the same sample itself. This pattern recognition method based on the idea of ​​"dividing" cannot overcome the problem of large misrecognition rate of untrained samples, and every time a new type of sample is added, all types of samples need to be retrained. [0003] In recent years, academician Wang Shoujue has proposed a new theory of bionic pattern recognition, which fundamentally breaks through the idea of ​​"division" in traditional patte...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/02
Inventor 王守觉李卫军赵顾良孙华
Owner INST OF SEMICONDUCTORS - CHINESE ACAD OF SCI
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