Dynamic memory allocation for CMAC using binary search trees

Authors:
Peter Scarfe;Euan Lindsay
Affiliations:
Department of Mechanical Engineering, Curtin University of Technology, Bentley, Western Australia, Australia;Department of Mechanical Engineering, Curtin University of Technology, Bentley, Western Australia, Australia
Venue:
NN'07 Proceedings of the 8th Conference on 8th WSEAS International Conference on Neural Networks - Volume 8
Year:
2007

Citing 3
Cited 2

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Abstract

Cerebellar Model Articulation Controllers (CMACs) are a biologically-inspired neural network system suitable for trajectory control. Traditionally, CMACs have been implemented using hash-coding for their memory allocation, requiring static allocation of fixed amounts of memory in advance to the training of the system. This paper presents a method for implementing CMACs using Binary Search Trees to provide dynamic memory allocation, allowing for lower memory usage without compromising the functionality of the CMAC.