Generalizing CMAC architecture and training

The cerebellar model articulation controller (CMAC) is a simple and fast neural-network based on local approximations. However, its rigid structure reduces its accuracy of approximation and speed of convergence with heterogeneous inputs. In this paper, we propose a generalized CMAC (GCMAC) network that considers different degrees of generalization for each input. Its representation abilities are analyzed, and a set of local relationships that the output function must satisfy are derived. An adaptive growing method of the network is also presented. The validity of our approach and methods are shown by some simulated examples.

[1]  J. Albus.  Mechanisms of planning and problem solving in the brain , 1979 .

[2]  Lin Chun-Shin,et al.  CMAC with General Basis Functions. , 1996, Neural networks : the official journal of the International Neural Network Society.

[3]  Neil E. Cotter,et al.  The CMAC and a theorem of Kolmogorov , 1992, Neural Networks.

[4]  James S. Albus,et al.  New Approach to Manipulator Control: The Cerebellar Model Articulation Controller (CMAC)1 , 1975 .

[5]  Youji Iiguni.  Hierarchical image coding via cerebellar model arithmetic computers , 1996, IEEE Trans. Image Process..

[6]  Antonio Artés-Rodríguez,et al.  Fourier analysis of the generalized CMAC neural network , 1998, Neural Networks.

[7]  James S. Albus,et al.  I A New Approach to Manipulator Control: The I Cerebellar Model Articulation Controller , 1975 .

[8]  N. J. A. Sloane,et al.  Sphere Packings, Lattices and Groups , 1987, Grundlehren der mathematischen Wissenschaften.

[9]  D.A. Handelman,et al.  Integrating neural networks and knowledge-based systems for intelligent robotic control , 1990, IEEE Control Systems Magazine.

[10]  C.-S. Lin,et al.  Use of adaptive resolution for better CMAC learning , 1992, [Proceedings 1992] IJCNN International Joint Conference on Neural Networks.

[11]  W. T. Miller,et al.  Deconvolution and nonlinear inverse filtering using a neural network , 1989, International Conference on Acoustics, Speech, and Signal Processing,.

[12]  W. T. Miller,et al.  CMAC: an associative neural network alternative to backpropagation , 1990, Proc. IEEE.

[13]  Chris J. Harris,et al.  The interpolation capabilities of the binary CMAC , 1993, Neural Networks.

[14]  Patrick C. Parks,et al.  A comparison of five algorithms for the training of CMAC memories for learning control systems , 1992, Autom..