Design and analysis of direct-action CMAC PID controller
Neurocomputing
Single-input CMAC control system
Neurocomputing
ART-type CMAC network classifier
Neurocomputing
Expert Systems with Applications: An International Journal
An efficient CMAC neural network for stock index forecasting
Expert Systems with Applications: An International Journal
Hi-index | 0.01 |
A new way to look at the learning algorithm in the cerebellar model articulation controller (CMAC) proposed by J.S. Albus (1975) is presented. A proof that the CMAC learning always converges with arbitrary accuracy on any set of training data is obtained. An alternative way to implement CMAC based on the insights obtained in the process is proposed. The scheme is tested with a computer simulation for learning the inverse dynamics of a two-link robot arm