An adaptive control system for biological and robotic simulations
An adaptive control system for biological and robotic simulations
A comparison of five algorithms for the training of CMAC memories for learning control systems
Automatica (Journal of IFAC)
Credit assigned CMAC and its application to online learning robust controllers
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Learning convergence of CMAC technique
IEEE Transactions on Neural Networks
Neighborhood sequential and random training techniques for CMAC
IEEE Transactions on Neural Networks
Minimal Structure of Self-Organizing HCMAC Neural Network Classifier
Neural Processing Letters
CMAC-Based PID Control of an XY Parallel Micropositioning Stage
ISNN 2009 Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II
Gait Pattern Based on CMAC Neural Network for Robotic Applications
Neural Processing Letters
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A Credit-Assignment CMAC (CA-CMAC) algorithm is proposed to reduce learning interference in conventional CMAC. In the proposed CA-CMAC, the error of the training sample distributed to the addressed memory cell is proportional to the cell's credibility, which is the inverse of the cell's activated times. The learning process of CA-CMAC is analyzed and conventional CMAC is proved to be a special case of CA-CMAC. Furthermore, the convergence properties of CA-CMAC both in batch learning and in incremental learning are investigated; meanwhile, the convergence theorems in the two learning schemes are obtained, respectively. Finally, simulations are carried out to testify the theorems and compare the performance of CA-CMAC with that of CMAC. Simulation results prove that CA-CMAC converges faster than conventional CMAC.