Title :
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
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;
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
DOI :
10.1109/CNNA.1994.381702
