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http://hdl.handle.net/2108/580
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| 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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Files in This Item:
| File |
Description |
Size | Format |
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| testo tesi.pdf | | 6349Kb | Adobe PDF | View/Open |
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