Accession Number : AD0489190
Title : PATTERN RECOGNITION OF STOCHASTIC PROCESSES.
Descriptive Note : Technical rept.,
Corporate Author : INFORMATION RESEARCH ASSOCIATES INC LEXINGTON MA
Personal Author(s) : Owen, Joel
Report Date : 07 JUL 1966
Pagination or Media Count : 21
Abstract : The class of differential processes are considered. For their class of processes, it is shown that there is an advantage to transforming the observed process x(t) into an infinite vector. Having derived the properties of the vector, it is then shown that the Decision Theory solution to the K-category recognition problems can be formulated in terms of the components of this vector. An example of signal detection is then worked out. It yields the optimum detector when the signal is a saw-tooth function. Finally, the K-category solution is explicitly derived.
Descriptors : *PATTERN RECOGNITION), (*STOCHASTIC PROCESSES, ARTIFICIAL INTELLIGENCE, BIONICS, INFORMATION THEORY, CYBERNETICS, PROBABILITY, DISTRIBUTION FUNCTIONS, THEOREMS, STATISTICAL PROCESSES.
Subject Categories : Statistics and Probability
Distribution Statement : APPROVED FOR PUBLIC RELEASE