Application of the Klopfian neuron model to function minimization

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.<>