DocumentCode
2250829
Title
CNN Wave Computing: Theory, Architectures, Implementations and Applicaions
Author
Gilli, M. ; Rekeczky, C. ; Shi, B.
Author_Institution
Dept. of Electron., Politecnico di Torino
fYear
2006
fDate
28-30 Aug. 2006
Firstpage
1
Lastpage
1
Abstract
A cellular neural/nonlinear network (CNN) is any spatial arrangement of mainly locally coupled cells, where each cell is a dynamical system which has an input, an output and a state that evolves according to some prescribed dynamical laws. Since the CNN was first introduced in 1988, research in this field has developed rapidly. The goal of this tutorial is to provide participants with a snapshot of the current state of the art and research trends. It covers the broad multi-disciplinary areas of CNN research, from theoretical aspects to applications. The presenters have experience ranging from theoretical analysis of CNN dynamics, VLSI implementation and system level applications
Keywords
VLSI; cellular neural nets; CNN wave computing; VLSI implementation; cellular neural network; cellular nonlinear network; locally coupled cells; theoretical analysis; Analog computers; Biological system modeling; Cellular neural networks; Computer architecture; Computer industry; Computer interfaces; Computer networks; Computer vision; Nonlinear dynamical systems; Very large scale integration;
fLanguage
English
Publisher
ieee
Conference_Titel
Cellular Neural Networks and Their Applications, 2006. CNNA '06. 10th International Workshop on
Conference_Location
Istanbul
Print_ISBN
1-4244-0639-0
Type
conf
DOI
10.1109/CNNA.2006.341587
Filename
4145827
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