You are in:Home/Publications/CMAC Neural Network: Modeling, Simulation and a Comparative Study of Learning Algorithms

Ass. Lect. Amro Abdelalim Shafik Mohamed Ibrahim :: Publications:

Title:
CMAC Neural Network: Modeling, Simulation and a Comparative Study of Learning Algorithms
Authors: Magdy Abdelhameed, Ahmed Kassem, and Amro Shafik
Year: 2010
Keywords: Not Available
Journal: Not Available
Volume: Not Available
Issue: Not Available
Pages: Not Available
Publisher: Not Available
Local/International: International
Paper Link:
Full paper Amro Abdelalim Shafik Mohamed Ibrahim_NEUR_01.pdf
Supplementary materials Not Available
Abstract:

Cerebellar Model Articulation Controller Neural Networks (CMAC NN) is one of the intelligent systems used for modeling, identification, classification, and controlling of nonlinear systems. In this paper, the mathematical model of CMAC is presented. CMAC is implemented using Simulink environment and its parameters are tuned to get the best CMAC control action. Three different learning algorithms are tested, using a constant learning rate, a variable learning rate, and learning by the control action of the conjugate conventional controller. The effect of varying CMAC parameters is studied and discussed. The simulation results showed that the learning algorithm based on constant learning rate gives the best performance.

Google ScholarAcdemia.eduResearch GateLinkedinFacebookTwitterGoogle PlusYoutubeWordpressInstagramMendeleyZoteroEvernoteORCIDScopus