Improved FastICA algorithm for data optimization processing in intrusion detection

For the purpose of achieving the better data optimizat sing results in intrusion detection, an improved FastICA algorithm was proposed. The weighted correlation coefficient was adopted in the phase of albinism processing to reduce information loss, and the Newton's iterative method was improved...

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Bibliographic Details
Main Authors: Ye DU, dan ZHANGYa, hong LIMei, wei ZHANGDa
Format: Article
Language:zho
Published: Editorial Department of Journal on Communications 2016-01-01
Series:Tongxin xuebao
Subjects:
Online Access:http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2016006/
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Summary:For the purpose of achieving the better data optimizat sing results in intrusion detection, an improved FastICA algorithm was proposed. The weighted correlation coefficient was adopted in the phase of albinism processing to reduce information loss, and the Newton's iterative method was improved for third-order convergence. The algorithm was introduced concretely, meanwhile the time complexity was analyzed in detail. The experiment shows that the method has the advantages of less times of iteration and fast speed of convergence, which can effectively decrease the losses of data and increase the efficiency of data optimization in in ion detection.
ISSN:1000-436X