Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/46786
Title: Pattern classification of overlapping data using probabilistic neural network
Authors: Roy Irawan
Keywords: DRNTU::Engineering::Electrical and electronic engineering
Issue Date: 2009
Abstract: As one of the Artificial Intelligence methods, Artificial Neural Networks (ANN) emerges as significant discipline which is potentially and rapidly developed in many fields. The design of ANN is inspired by biological neural network principles which allow this technique to tackle problems that our brain is good at solving, such as pattern recognition / classification. Even more, in pattern classification problems, our brain can recognize overlapping patterns in a very good manner. This is the main topic of this dissertation, where we could adopt this ability into ANN classifier socalled Probabilistic Neural Network (PNN).
Description: 159 p.
URI: http://hdl.handle.net/10356/46786
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Theses

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