Realisation of a digital cellular neural network for image processing

Author

Doan, M.-D. ; Glesner, M. ; Chakrabaty, R. ; Heidenreich, M. ; Cheung, S.

Author_Institution

Inst. for Mikroelectron. Syst., Darmstadt Univ. of Technol., Germany

fYear

1994

fDate

18-21 Dec 1994

Firstpage

85

Lastpage

90

Abstract

A a digital cellular neural network (DCNN) based on the SIMD-architecture is presented. The network is optimized for image processing applications. Due to the massive parallel architecture of the global structure and due to the local parallel operating blocks of the cells, high calculating speed can be obtained. Processing of images with sizes up to 100×100 pixels in realtime is principally possible. In order to process large images, which are much greater than the physical network, virtual processing is needed, and supported by the hardware. As prototype, a cascadable net of 2×2 cells is implemented on a chip using the 1.0 μ process of ES2

Keywords

cellular neural nets; image processing; neural chips; neural net architecture; parallel architectures; real-time systems; SIMD-architecture; cascadable net; digital cellular neural network; high calculating speed; image processing; image processing applications; local parallel operating blocks; network optimization; neural chip; parallel architecture; pixels; real-time; virtual processing; Array signal processing; Cellular neural networks; Circuits; Hardware; Image processing; Information processing; Parallel architectures; Pixel; Prototypes; 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.1994.381702

Filename

381702