Title :
Application of the Klopfian neuron model to function minimization
Author :
Politis, Demetrios T.
Author_Institution :
Adv. Concepts Div., Environ. Res. Inst. of Michigan, Ann Arbor, MI, USA
Abstract :
The author discusses the use of the adaptive learning controller (ALC) algorithms developed by A.G. Barto and R.S. Sutton (1981), based on the Klopfian neuron model, for function minimization. In this application the ALC is placed directly into the signal processing loop of a synthetic aperture radar and the task assigned to it is to minimize the 3-dB width of the system impulse response function. This results in the correction of the quadratic and possibly higher-order system phase errors
Keywords :
adaptive systems; learning systems; minimisation; neural nets; radar systems; signal processing; transient response; Klopfian neuron model; adaptive learning controller; function minimization; signal processing loop; synthetic aperture radar; system impulse response function; Adaptive control; Adaptive signal processing; Additive noise; Automatic logic units; Control systems; Minimization methods; Neurons; Programmable control; Radar signal processing; Signal processing algorithms;
Conference_Titel :
Artificial Intelligence for Industrial Applications, 1988. IEEE AI '88., Proceedings of the International Workshop on
Conference_Location :
Hitachi City
DOI :
10.1109/AIIA.1988.13344
