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https://hdl.handle.net/20.500.14279/2532
Τίτλος: | Classification of noisy signals using fuzzy ARTMAP neural networks | Συγγραφείς: | Kasparis, Takis Georgiopoulos, Michael N. Charalampidis, Dimitrios |
metadata.dc.contributor.other: | Κασπαρής, Τάκης | Major Field of Science: | Engineering and Technology | Field Category: | Electrical Engineering - Electronic Engineering - Information Engineering | Λέξεις-κλειδιά: | Neural networks;Fractals;Fuzzy sets;Image analysis | Ημερομηνία Έκδοσης: | Ιου-2000 | Πηγή: | International Joint Conference on Neural Networks, 2000, Como, Italy | Conference: | International Joint Conference on Neural Networks | Περίληψη: | This paper describes an approach to classification of noisy signals using a technique based on the Fuzzy ARTMAP neural network (FAM). A variation of the testing phase of Fuzzy ARTMAP is introduced, that exhibited superior generalization performance than the standard Fuzzy ARTMAP in the presence of noise. We present an application of our technique for textured grayscale images. We perform a large number of experiments to verify the superiority of the modified over the standard Fuzzy ARTMAP. More specifically, the modified and the standard FAM were evaluated on two different sets of features (fractal-based and energy-based), for three different types of noise (Gaussian, uniform, exponential) and for two different texture sets (Brodatz, aerial). Furthermore, the classification performance of the standard and modified Fuzzy ARTMAP was compared for different network sizes. | ISSN: | 1098-7576 | DOI: | 10.1109/IJCNN.2000.859372 | Rights: | © 2000 IEEE | Type: | Conference Papers | Affiliation: | University of Central Florida | Affiliation: | University of Central Florida | Publication Type: | Peer Reviewed |
Εμφανίζεται στις συλλογές: | Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation |
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