A mixed mode real-time VLSI implementation of a shunting inhibition cellular neural network

In this paper a real-time mixed analog digital VLSI implementation of a shunting inhibition cellular neural network (SICNN) is presented. Unlike the usual VLSI implementation of vision chips, this circuit is based on a mixed analog-digital technology where the processing is realized using current mode analog approach while the cellular neural network topology (size of the window and connectivity) is realized using a modified digital read-out circuit. A significant processing speed-up is achieved using this technique since the window-based processing of the SICNN is realized in analog-domain while reading the pixel using the modified digital read-out circuit. A prototype including a 58/spl times/58 pixels and the SICNN processor with a programmable user-defined window size of 3/spl times/3 or 5/spl times/5 has been designed. The circuit also includes an amplifier and a successive approximation analogue-to-digital converter. The circuit has been designed using Alcatel CMOS 0.7 /spl mu/m technology and occupies a silicon area of 11 mm/sup 2/.

[1]  Robert B. Pinter,et al.  Image Motion Processing in Biological and Computer Vision Systems , 1989, Other Conferences.

[2]  Abdesselam Bouzerdoum,et al.  Properties of shunting inhibitory cellular neural networks for colour image enhancement , 1999, ICONIP'99. ANZIIS'99 & ANNES'99 & ACNN'99. 6th International Conference on Neural Information Processing. Proceedings (Cat. No.99EX378).

[3]  R. B. Pinter,et al.  Shunting inhibitory cellular neural networks: derivation and stability analysis , 1993 .

[4]  Abdesselam Bouzerdoum,et al.  Hierarchical model for early visual processing , 1994, Electronic Imaging.