Neural network controller using autotuning method for nonlinear functions
Takayuki Yamada, Tetsuro Yabuta · IEEE Transactions on Neural Networks · 1992
An autotuning method for the optimum sigmoid function of neural networks is proposed. It is based on the steepest descent method. Simulated results using a learning-type direct controller confirm both the practicality and the characteristics of the autotuning method.