School of Information Engineering, Shandong University at Weihai, Weihai 264209 College of Mathematical and Physical Sciences, Shandong Institute of Light Industry, Jinan 250100
Abstract：An improved learning algorithm for Resource Allocating Network (RAN) is presented in this paper, which is called IRAN algorithm. It allocates hidden neurons of network by a fourpart novelty criterion, removes redundant neurons according to their error reduction rates, and updates outputlayer weights by a recursive leastsquares algorithm with GivensQR decomposition. Simulations on two Benchmark problems in the function approximation area indicate that the IRAN algorithm can provide smaller networks and consume less training time than RAN, RANEKF and MRAN algorithms.
[1] Platt J. A Resource-Allocating Network for Function Interpolation. Neural Computation, 1991, 3(2): 213-225 [2] Chen S, Grant P M, Cowan C F N. Orthogonal Least-Squares Algorithm for Training Multioutput Radial Basis Function Networks. IEE Proceedings-F: Radar and Signal Processing, 1992, 139(6): 378-384 [3] Kadirkamanathan V, Niranjan M. A Function Estimation Approach to Sequential Learning with Neural Networks. Neural Computation, 1993, 5(6): 954-975 [4] Lu Y W, Sundararajan N, Saratchandran P. A Sequential Learning Scheme for Function Approximation Using Minimal Radial Basis Function Neural Networks. Neural Computation, 1997, 9: 461-478 [5] Kalouptsidis N, Theodoridis S. Adaptive System Identification and Signal Processing Algorithms. Upper Saddle River, USA: Prentice Hall, 1993 [6] Li Y, Sundararajan N, Saratchandran P. Analysis of Minimal Radial Basis Function Network Algorithm for Real-Time Identification of Nonlinear Dynamic Systems. IEE Proc on Control Theory and Applications, 2000, 147(4): 476-484 [7] Fun M H . Recursive Time-and Order-Update Algorithms for Radial Basis Function Networks. Ph.D. Dissertation. School of Electrical and Computer Engineering, Oklahoma State University, Oklahoma, USA, 2001 [8] Blake C, Merz J. UCI Repository of Machine Learning Databases. 1998. http://www.ics.uci.edu/~mlearn/MLRepository.html [9] Rosipal R, Koska M, Farka I. Prediction of Chaotic Time-Series with a Resource-Allocating RBF Network. Neural Processing Letters, 1998, 7(3): 185-197
2006, Vol. 19 
