Portland State University. Department of Electrical Engineering
Andrew M. Fraser
Date of Award
Master of Science (M.S.) in Electrical Engineering
1 online resource (x, 76 p.)
Signal processing -- Mathematical models, Chaotic behavior in systems -- Mathematical models
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.
Cai, Qin, "Detecting Chaotic Signals with Nonlinear Models" (1993). Dissertations and Theses. Paper 4564.