Showing papers on "Bhattacharyya distance published in 1975"

Synthesis of Input Signals in Parameter Estimation Problems.

Abstract: : Design of input signals to enhance the estimation on unknown parameters in discrete time dynamics is considered. The system identification problem can be considered as the initial phase of a stochastic control problem of a dynamic system. In such a situation it is desirable to estimate the parameters as rapidly as possible without disturbing the normal operation of the process. The problem is represented in a Baysian framework. The optimality criterion for the synthesis problem is defined in terms of the statistical distance measure between distributions characterized by distinct parameter values. In this dissertation we define this quantity in terms of the pairwise Bhattacharyya distance. The distance measure has the desirable property of ordering the Bayes' probability of error as a function of two experimental design programs. The statistical distance measures have been successfully used in studying taxonomy and characterization of racial distributions. It is shown that such an approach is also feasible in applications to more general dynamic situation.

Target Spectra Feature Selection Using a Priori Information

Abstract: This correspondence gives a method of selecting n features out of k (n < k) FFT filter outputs which characterize them classes of target signatures to be recognized. The method differs from other known techniques in that it uses a priori information of the target measurements. It is based on an error bound established by Lainiotis which is a weighted sum of Bhattacharyya coefficients.