Title: Characteristic selecting method based on artificial nerve network
Application Number: 200610019570 Application Date: 2006.07.07
Publication Number: 1945602 Publication Date: 2007.04.11
Approval Pub. Date: Granted Pub. Date:
International Classifi-cation: G06K9/62;G06N3/02
Applicant(s) Name: Central China Univ. of Science and Technology Address:
Inventor(s) Name: Sang Nong;Cao Zhiguo;Zhang Tianxu;Xie Yantao;Zhang
Attorney & Agent: caobao jing
Abstract:
    The invention discloses an features selection method based on the artificial neural network, including: (1) the user gives all the features for selection, and the sample for training the artificial neural network; (2) selecting the number of blurring subjection function, setting the number of nodes on each layer of artificial neural network, link weight among layers and the initial value of blurring subjection function; (3) using the back-propagation algorithm to train the network in the mode of batch processing, to adjust the network linking weights and parameters of blurring subjection function; (4) calculating all the importance of characteristics, and ranking the features. The invention avoids the problem of data normalization, in which, calculating is simple and training network is just once, and is easy to combine with various algorithm to be a complete features selection system. The invention has been successfully used in the pattern recognition and target classification with a variety of multi-dimensional characteristics, and also can be applied to all types of pattern recognition with the data characteristics.
Time: 5