Iterative Analog Computation and the Representation of Signals

Abstract

The advent of iterative analog computers has greatly increased the class of problems that can efficiently be simulated with a hybrid system. The iterative analog computer has placed wide bandwidth analog components under the control of high-speed digital logic. This enables one both to increase the sophistication of the control used for the analog components and to acquire statistically significant samples of the process in a reasonable period of time. An iterative analog computer has been used to investigate methods of increasing the efficiency of signal representation systems by combining analog measurements with digital control and storage. A hybrid system has been developed that is capable of adjusting the exponential basis as well as the coefficients of the representation to minimize the integrated squared error between a signal and its representative. Since the efficiency of the representation depends upon the sampling instant chosen for measurement of the coefficients, methods of detecting this instant were investigated. A detection system has been developed that can adaptively adjust its parameters to correspond to the signal that is being processed. The data presented illustrates the dynamic accuracy of the iterative analog computer, the convergence properties of the optimization procedure, and the statistical properties of the detector when noise is present.