First Advisor

Andrew M. Fraser

Date of Publication

7-8-1993

Document Type

Thesis

Degree Name

Master of Science (M.S.) in Electrical Engineering

Department

Electrical Engineering

Subjects

Signal processing -- Mathematical models, Chaotic behavior in systems -- Mathematical models

DOI

10.15760/etd.6448

Physical Description

1 online resource (x, 76 p.)

Abstract

In this thesis we apply chaotic dynamic data analysis to the area of discrete time signal processing. A newly developed Hidden Filter Hidden Markov Model is introduced in detection of chaotic signals. Numerical experiments have verified that this novel nonlinear model outperforms linear AR model in detecting chaotic signals buried by noise having similar power spectra. A simple Histogram Model is proposed which can also be used to do detection on the data sets with chaotic behavior. Receiver Operating Characteristics for a variety of noise levels and model classes are reported.

Comments

If you are the rightful copyright holder of this dissertation or thesis and wish to have it removed from the Open Access Collection, please submit a request to pdxscholar@pdx.edu and include clear identification of the work, preferably with URL

Persistent Identifier

https://archives.pdx.edu/ds/psu/26538

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