Classifying method based on sparse measurement

A classification method and sparse technology, applied in the fields of biomedical information and brain-computer interface, can solve problems such as hindering subsequent analysis and research of EEG signals, wrong estimation of projection w, signal matrix singularity, etc. The requirements of sexuality and the effect of improving stability

Inactive Publication Date: 2013-05-01
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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Problems solved by technology

Although the solution based on the L2 mode method has good smoothness, it does not have sparsity, and is easily affected by outliers (Outliers) and isolated noise points caused by loose electrodes, eye blinking and improper operation during the experiment. Even sometimes the signal matrix becomes singular, which may cause a wrong estimate of the projection w, which will eventually affect the classification effect; and these interferences will increase the difficulty of reading the EEG signal and hinder the subsequent analysis and research of the EEG signal

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  • Classifying method based on sparse measurement
  • Classifying method based on sparse measurement
  • Classifying method based on sparse measurement

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Embodiment Construction

[0029] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0030] due to S B , S W Both are real symmetric matrices, which are essentially composed of the product of two matrices and their own transposed matrices, so formula (1) can also be expressed as:

[0031]

[0032] S B , S W The corresponding φ can be found by a certain matrix decomposition theorem B and Therefore the method of the present invention can be described as follows:

[0033] S1. Calculate the inter-class dispersion matrix S according to the EEG signal training samples B and the intra-class dispersion matrix S W ;

[0034] In order to construct the corresponding inter-class scatter matrix and intra-class scatter matrix, the sample mean μ of each class can be calculated separately in the training samples in advance i and the overall sample mean value μ, calculate the inter-class dispersion matrix S according to formula (2)...

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Abstract

The invention discloses a classifying method based on sparse measurement. The classifying method specifically comprises the following steps of: culturing a distribution information matrix among classes and a distribution information matrix among classes; decomposing the obtained matrixes; converting a Fisher criterion to an L1 module structure; and estimating a projection vector for enabling an objective function to obtain the maximum value. As the existing LDA (Linear Discriminant Analysis) based on L2 mode measure function generates unfavorable amplification to the noises such as Outliers and the like, the classifying method disclosed by the invention can overcome the problem that the existing linear discriminant analysis based on L2 mode is affected by the Outliers and noise isolated points by adopting a measure function based on L1 mode during a discriminant analysis constructing process, so that stable classifying and identifying effect is obtained, and the stability of a BCI (Brain Computer Interface) system is improved to certain extent.

Description

technical field [0001] The invention belongs to the technical field of biomedical information, in particular to a pattern classification method in the field of brain-computer interface. Background technique [0002] Brain Computer Interface (BCI) is a channel for direct communication and control between the human brain and the outside world using computers or other external electronic devices (Wolpaw JR, Birbaumer N, McFarland DJ, Pfurtscheller G, Vaughan TM (2002 ) Brain-computer interfaces for communication and control. Clin Neurophysiol 113, 767-791). BCI research involves many disciplines, such as: neuroscience, signal detection, signal processing, pattern recognition, control theory, etc. The cross-development of these disciplines promotes the advancement of BCI research. The basic theory and clinical application research of BCI has been included in the scope of brain science and neuroengineering, and is also considered by many international authoritative organizations...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F19/00
Inventor 徐鹏李沛洋张锐田春阳郭兰锦尧德中
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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