Novel optimization methods for scalar and vector quantization design
"Computational Intelligence (CI) aims to provide solutions to real-life problems using mathematical models which mimic artificial intelligence. Many CI paradigms, like Neural Networks and Evolutionary Computation, offer advantages in a variety of applications in digital signal processing. In this thesis, several CI techniques, namely Neural Networks, Particle Swarm Optimization (PSO), Differential Evolution (DE) and Adaptive Critic Designs (ACDs), are applied to scalar and vector quantization problems"--Abstract, leaf iii.
Venayagamoorthy, Ganesh K.
Smith, Scott C.
Grant, Steven L.
Electrical and Computer Engineering
M.S. in Computer Engineering
National Science Foundation (U.S.)
University of Missouri--Rolla
xii, 204 leaves
© 2006 Wenwei Zha, All rights reserved.
Thesis - Citation
Library of Congress Subject Headings
Program transformation (Computer programming)
Scalar field theory
Vector processing (Computer science)
Print OCLC #
Link to Catalog Record
Full-text not available: Request this publication directly from Missouri S&T Library or contact your local library.http://laurel.lso.missouri.edu/record=b5790963~S5
Zha, Wenwei, "Novel optimization methods for scalar and vector quantization design" (2006). Masters Theses. 3882.