Title :
Adaptive processing with neural network controlled resonator-banks
Author :
Sztipanovits, Janos
Author_Institution :
Dept. of Electr. Eng., Vanderbilt Univ., Nashville, TN, USA
Abstract :
The author describes a novel neuromorphic architecture for structurally adaptive control systems. The neural network controlled resonator-bank (NCRB) architecture consists of two main components, a resonator-bank filter structure and a neural network which controls the transfer characteristics of the filter. The architecture offers an attractive alternative to the approximation of nonlinear dynamic systems having a finite number of stable operating points with quasi-linear behavior. The first results of the experimental analysis of the NCRB structure are encouraging. The system is apparently able to approximate a wide range of nonlinear dynamic behaviors
Keywords :
adaptive control; neural nets; adaptive processing; neural network controlled resonator-banks; neuromorphic architecture; nonlinear dynamic systems; quasi-linear behavior; resonator-bank filter structure; structurally adaptive control systems; transfer characteristics; Adaptive control; Adaptive filters; Adaptive systems; Control systems; Neural networks; Neuromorphics; Nonlinear dynamical systems; Process design; Programmable control; Resonator filters;
Conference_Titel :
Intelligent Control, 1989. Proceedings., IEEE International Symposium on
Conference_Location :
Albany, NY
Print_ISBN :
0-8186-1987-2
DOI :
10.1109/ISIC.1989.238677