DocumentCode
2624748
Title
Analogic CNN computing: architectural, implementation, and algorithmic advances-a review
Author
Roska, Tamás
Author_Institution
Analogical & Neural Comput. Lab., Hungarian Acad. of Sci., Budapest, Hungary
fYear
1998
fDate
14-17 Apr 1998
Firstpage
3
Lastpage
10
Abstract
In this paper, first, an overview is given about the whole scenario of analogic cellular neural net (CNN) computing. Next, two areas of CNN computing technology are considered briefly: (i) the architectural advances, especially variable resolution and adaptation in space, time, and value and (ii) the computational infrastructure from high-level language and compiler to physical implementations. Three basic physical implementations are considered: analogic CMOS, emulated digital CMOS and optical. The computational infrastructure is the same for all implementations, except the physical interfaces
Keywords
CMOS analogue integrated circuits; analogue processing circuits; cellular neural nets; neural net architecture; optical neural nets; reviews; analogic CNN computing; analogue CMOS; cellular neural net; compiler; computational infrastructure; emulated digital CMOS; high-level language; neural net architecture; optical implementation; physical implementations; variable resolution; Analog computers; Application software; Cellular neural networks; Cloning; Computer architecture; High level languages; Image processing; Morphology; Physics computing; Space technology;
fLanguage
English
Publisher
ieee
Conference_Titel
Cellular Neural Networks and Their Applications Proceedings, 1998 Fifth IEEE International Workshop on
Conference_Location
London
Print_ISBN
0-7803-4867-2
Type
conf
DOI
10.1109/CNNA.1998.685320
Filename
685320
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