Title :
Dynamic neural controller with somatic adaptation
Author :
Rao, D.H. ; Gupta, M.M.
Author_Institution :
Intelligent Syst. Res. Lab., Saskatchewan Univ., Saskatoon, Sask., Canada
Abstract :
A neural structure which is comprised of dynamic neural units with time-varying sigmoidal functions is proposed. The effect of sigmoidal gain on nonlinear dynamic systems is discussed. The learning and adaptive algorithm to determine the optimum sigmoidal gain, which results in selftuning of the neuron, is derived. The effectiveness of the proposed neural network is demonstrated through computer simulation studies
Keywords :
adaptive control; neural nets; nonlinear control systems; self-adjusting systems; time-varying systems; adaptive algorithm; dynamic neural units; learning algorithm; nonlinear dynamic systems; selftuning; somatic adaptation; time-varying sigmoidal functions; Adaptive algorithm; Artificial neural networks; Biological system modeling; Computer networks; Computer simulation; Delay; Neural networks; Neurofeedback; Neurons; Shape control;
Conference_Titel :
Neural Networks, 1993., IEEE International Conference on
Conference_Location :
San Francisco, CA
Print_ISBN :
0-7803-0999-5
DOI :
10.1109/ICNN.1993.298618
