Title :
Dynamic neural unit and function approximation
Author :
Rao, D.H. ; Gupta, M.M.
Author_Institution :
Intelligent Syst. Res. Lab., Saskatchewan Univ., Saskatoon, Sask., Canada
Abstract :
A dynamic model of a neuron for applications in robotics and control is developed. The proposed model, called the dynamic neural unit (DNU), comprises two distinct operations: the synaptic operation, which determines the optimum feedforward and feedback synaptic weights controlling the dynamics of the neuron; and the somatic operation, which determines the optimum gain of the nonlinear activation function for a given task. The function approximation capability of the network of DNUs is described by considering linear and trigonometric operators. Computer simulation results are presented
Keywords :
computerised control; function approximation; neural nets; robots; DNU; dynamic neural unit; feedback synaptic weights; function approximation; linear operators; nonlinear activation function; optimum feedforward synaptic weights; somatic operation; synaptic operation; trigonometric operators; Artificial neural networks; Biological neural networks; Biological system modeling; Central nervous system; Circuits; Function approximation; Intelligent robots; Neurofeedback; Neurons; Output feedback;
Conference_Titel :
Neural Networks, 1993., IEEE International Conference on
Conference_Location :
San Francisco, CA
Print_ISBN :
0-7803-0999-5
DOI :
10.1109/ICNN.1993.298648
