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Please use this identifier to cite or link to this item: http://hdl.handle.net/2108/580

Title: Neural network approach to problems of static/dynamic classification
Authors: Salerno, Mario
Carota, Massimo
Keywords: neural networks
classification
clustering
neural classifiers
static classification
dynamic classification
locally recurrent neural networks
fuzzy logic
exclusive classification
Simpson’s classifier
musical instrument recognition
automatic tanscription of music
human motor acts
nervous system diseases
Issue Date: 26-Aug-2008
Abstract: The purpose of my doctorate work has consisted in the exploration of the potentialities and of the effectiveness of different neural classifiers, by experimenting their application in the solution of classification problems occurring in the fields of interest typical of the research group of the “Laboratorio Circuiti” at the Department of Electronic Engineering in Tor Vergata. Moreover, though inspired by works already developed by other scholars, the adopted neural classifiers have been partially modified, in order to add to them interesting peculiarities not present in the original versions, as well as to adapt them to the applications of interest. These applications can be grouped in two great families. As regards the first application, the objects to be classified are identified by features of static nature, while as regards the second family, the objects to be classified are identified by features evolving in time. In relation to the research fields taken as reference, t...
Description: 19. ciclo
URI: http://hdl.handle.net/2108/580
Appears in Collections:Tesi di dottorato in ingegneria

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