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| THE STUDY ON RECOGNITION TECHNIQUE OF RADAR TARGET S ONE DIMENSIONAL IMAGE BASED ON RADIAL BASIS FUNCTION NETWORK |
| Huang Deshuang; Bao Zheng |
| Xidian University, Xi'an 710071 |
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Abstract This paper studies the problem applying Radial Basis Function Network (RBFN) which is trained by the traditional Recursive Least Square Algorithm (RLSA) to the recognition of one dimensional image of radar targets. The equivalence between RBFN and the estimation of Parzen window probabilistic density is proved, it is pointed out that the I/O functions in RBFN hidden units can be extended to general Parzen window probabilistic kernel function or potential function, too. This paper discusses the effects of the shape parameter α in RBFN and the forgotten factor λ, in RLSA on the results of the recognition of three kinds of kernel function such as Gaussian, Triangle, Double-exponential kernel functions, at the same time, and discusses also the relationship between λ and the training time in RBFN.
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Received: 14 June 1993
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1995, Vol. 17 
