Portland State University PDXScholar Dissertations and Theses Dissertations and Theses 1-1-2011 Prestructuring Multilayer Perceptrons based on Information-Theoretic Modeling of a Partido-Alto- based Grammar for Afro-Brazilian Music: Enhanced Generalization and Principles of Parsimony, including an Investigation of Statistical Paradigms Mehmet Vurkaç Portland State University Follow this and additional works at: https://pdxscholar.library.pdx.edu/open_access_etds Let us know how access to this document benefits ou.y Recommended Citation Vurkaç, Mehmet, "Prestructuring Multilayer Perceptrons based on Information-Theoretic Modeling of a Partido-Alto-based Grammar for Afro-Brazilian Music: Enhanced Generalization and Principles of Parsimony, including an Investigation of Statistical Paradigms" (2011). Dissertations and Theses. Paper 384. https://doi.org/10.15760/etd.384 This Dissertation is brought to you for free and open access. It has been accepted for inclusion in Dissertations and Theses by an authorized administrator of PDXScholar. Please contact us if we can make this document more accessible:
[email protected]. Prestructuring Multilayer Perceptrons based on Information-Theoretic Modeling of a Partido-Alto -based Grammar for Afro-Brazilian Music: Enhanced Generalization and Principles of Parsimony, including an Investigation of Statistical Paradigms by Mehmet Vurkaç A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Electrical and Computer Engineering Dissertation Committee: George G. Lendaris, Chair Douglas V. Hall Dan Hammerstrom Marek Perkowski Brad Hansen Portland State University ©2011 ABSTRACT The present study shows that prestructuring based on domain knowledge leads to statistically significant generalization-performance improvement in artificial neural networks (NNs) of the multilayer perceptron (MLP) type, specifically in the case of a noisy real-world problem with numerous interacting variables.