Accession Number:

ADA282954

Title:

Investigation of Spectral-Based Techniques for Classification of Wideband Transient Signals in Additive White Gaussian Noise

Descriptive Note:

Master's thesis

Corporate Author:

NAVAL POSTGRADUATE SCHOOL MONTEREY CA

Personal Author(s):

• DeRieux, David A.

Report Date:

1994-03-01

Pagination or Media Count:

163.0

Abstract:

Spectral-based classification schemes designed to separate various wide band transient signals in added noise have been identified and their performances compared along with those obtained using a back-propagation neural network implementation. The spectral-based measures used include the normalized cross-correlation coefficient the modified normalized cross-correlation coefficient, and the divergence and the Bhattacharyya distance. Noise was added to the signals to create signal to noise ratios of 0 dB to -20 dB. Results show that as noise levels increase, the modified normalized cross-correlation coefficient spectral measure remains the most robust scheme.

Descriptors:

• *NEURAL NETS
• *WHITE NOISE
• *GAUSSIAN NOISE
• *SPECTRA
• COMPUTER PROGRAMS
• SIGNALS
• NOISE
• CROSS CORRELATION
• FAST FOURIER TRANSFORMS
• THESES
• SIGNAL PROCESSING
• SIGNAL TO NOISE RATIO
• TRANSIENTS

Subject Categories:

• Cybernetics
• Acoustics
• Atomic and Molecular Physics and Spectroscopy

Distribution Statement:

APPROVED FOR PUBLIC RELEASE