Adaptive signal detection with finite memory
The purpose of this presentation is to develop and evaluate an algorithm for determining a finite memory detector applicable to statistical signal detection theory. In the Bayesian signal detection theory, infinite soft or changeable memory is tacitly assumed. Since an infinite memory is physically unrealizable, this study postulates a finite memory scheme which is applicable to a large class of signal detection problems. A general sequentially operating finite memory detector design is obtained and then evaluated for the signal known exactly and the signal known except amplitude problems. Detection performance as a function of memory size is presented for finite observation records using the receiver operating characteristic and plots of probability of decision error versus time
