Journal of Systems Engineering and Electronics ›› 2008, Vol. 19 ›› Issue (1): 119-124.

• SYSTEMS ENGINEERING • Previous Articles     Next Articles

Self-organizing fuzzy clustering neural network and application to electronic countermeasures effectiveness evaluation

Li Zhisheng1,2, Li Junshan1, Feng Fan1 & Zhao Xin3   

  1. 1. The Second Artillery Engineering Coll., Xi’an 710025, P. R. China;
    2. PLA 92941, Huludao 125000, P. R. China;
    3. School of Information Science and Technology, Beijing Inst. of Technology, Beijing 100081, P. R. China
  • Online:2008-02-21 Published:2010-01-03

Abstract:

A self-organizing fuzzy clustering neural network by combining the self-organizing Kohonen clustering network with the fuzzy theory is proposed. This network model is designed for the effectiveness evaluation of electronic countermeasures, which not only exerts the advantages of the fuzzy theory, but also has a good ability in machine learning and data analysis. The subjective value of sample versus class is computed by the fuzzy computing theory, and the classified results obtained by self-organizing learning of Kohonen neural network are represented on output layer. Meanwhile, the fuzzy competition learning algorithm keeps the similar information between samples and overcomes the disadvantages of neural network which has fewer samples. The simulation result indicates that the proposed algorithm is feasible and effective.