A reconfigurable architecture mapping multilayer CNN paradigms

Author

Raffo, Luigi ; Sabatini, Silvio P. ; Bisio, Giacormo M.

Author_Institution

Istituto di Elettrotecnica, Cagliari Univ., Italy

fYear

1994

fDate

18-21 Dec 1994

Firstpage

393

Lastpage

398

Abstract

A digital VLSI implementation of linear template cellular neural nets (CNNs) is presented. A reconfigurable architecture is organized as 12 layers of 64×64 cells. The CNNs are reformulated introducing sets of generalized cloning templates to enucleate more sharply the structure of both intra- and inter-layer cooperative computations. In this way it is possible to develop CNN algorithms for complex vision machine tasks. Various applications are considered in edge and connected component detection and in texture segregation

Keywords

VLSI; cellular neural nets; multilayer perceptrons; reconfigurable architectures; complex vision machine tasks; connected component detection; digital VLSI implementation; generalized cloning templates; linear template cellular neural nets; reconfigurable architecture mapping multilayer CNN paradigms; texture segregation; Cellular neural networks; Cloning; Computer architecture; Concurrent computing; Face; Hardware; Neural networks; Nonhomogeneous media; Reconfigurable architectures; Very large scale integration;

fLanguage

English

Publisher

ieee

Conference_Titel

Cellular Neural Networks and their Applications, 1994. CNNA-94., Proceedings of the Third IEEE International Workshop on

Conference_Location

Rome

Print_ISBN

0-7803-2070-0

Type

conf

DOI

10.1109/CNNA.1994.381643

Filename

381643