Electrical and Computer Engineering ETDs

Publication Date

3-23-1970

Abstract

The performance of several sequential procedures for the following multiple-decision problem is investigated. Samples from k random processes (or populations) are available, k at a time (one from each process), to a receiver or data processor. One process contains a signal; the other k - 1 are statistically-identical noise. The receiver is to select the odd process (locate the signal), with prescribed probability of error. The optimal receiver makes the selection in minimum average time. All computation is done under the hypothesis that the processes sampled are Rayleigh; however, a method for extrapolating results to other cases is given. The parameter k is allowed to vary from 2 to 1000. A number of methods for estimating average sample number (ASN) are used to obtain a substantial quantity of numerical results which may have handbook value. The utility of the various methods is discussed. The several decision procedures investigated are compared on the basis of efficiencies (ratios of ASN's) relative to the optimal fixed­-sample-size procedure and relative to each other. The variation of the problem that allows all k processes to be (statistically-identical) noise is discussed.

Sponsors

Sandia's Doctoral Study Program

Document Type

Dissertation

Language

English

Degree Name

Electrical Engineering

Level of Degree

Doctoral

Department Name

Electrical and Computer Engineering

First Committee Member (Chair)

Daniel Paul Peterson

Second Committee Member

Shelemyahu Zacks

Third Committee Member

Harold Knud Knudsen

Fourth Committee Member

Arnold Herman Koschmann

Download

Share

COinS