Neural networks applied to signal processing
Download
Author
Baehre, Mark D.
Date
1989-09Advisor
Tummala, Murali
Second Reader
Therrien, Charles W.
Metadata
Show full item recordAbstract
The relationship between the structure of a neural network and its ability to
perform nonlinear mapping is analyzed. A new algorithm, called the conjugate gradient
optimization method, for calculating the weights and thresholds of a neural network is
presented. The performance of the conjugate gradient algorithm is then compared to the
well known backpropagation method and shown to be more computationally efficient.
A neural network using the conjugate gradient algorithm is then applied to three simple
examples to demonstrate its signal processing capabilities. The first example illustrates
the ability of the neural network to perform classification. The second compares the
performance of a one-step linear predictor to a neural network for a nonlinear chaotic
time series. The neural network predictor is shown to provide much greater accuracy
than its linear counterpart. The final application presented demonstrates the ability of
a neural network to perform channel equalization for a nonmininmum phase channel. Its
performance is then compared to its linear equivalent.
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.Collections
Related items
Showing items related by title, author, creator and subject.
-
Global evaluation of special sensor microwave/imager ocean surface wind speed retrieval algorithms for the period September 1991 - April 1992
Hesser, William A. (Monterey, California. Naval Postgraduate School, 1995-06);The Fleet Numerical Meteorology and Oceanography Center (FNMOC) has the charter to provide Special Sensor Microwave/Imager (SSMI) data to the DOD and the NOAA. This has led FNMOC to examine new methods for processing SSM/I ... -
Data Consolidation of Disparate Procurement Data Sources for Correlated Performance-Based Acquisition
Nangia, Samantha; Dickover, Ryan; Wardwell, Thomas; Mora, Randall (Monterey, California. Naval Postgraduate School, 2017-03); SYM-AM-17-095Frank Kendall, then Under Secretary of Defense for Acquisition, Technology and Logistics, released the first defense acquisition system performance report in June 2013. This report focused primarily on performance related ... -
Data Consolidation of Disparate Procurement Data Sources for Correlated Performance-Based Acquisition Decision Support
Nangia, Samantha; Dickover, Ryan; Wardwell, Thomas; Mora, Randall (Monterey, California. Naval Postgraduate School, 2017-03); SYM-AM-17-044Frank Kendall, then Under Secretary of Defense for Acquisition, Technology and Logistics, released the first defense acquisition system performance report in June 2013. This report focused primarily on performance related ...