Home Articles FAQs XREF Games Software Instant Books BBS About FOLDOC RFCs Feedback Sitemap
irt.Org

Cellular Neural Network

You are here: irt.org | FOLDOC | Cellular Neural Network

<architecture> (CNN) The CNN Universal Machine is a low cost, low power, extremely high speed supercomputer on a chip. It is at least 1000 times faster than equivalent DSP solutions of many complex image processing tasks. It is a stored program supercomputer where a complex sequence of image processing algorithms is programmed and downloaded into the chip, just like any digital computer. Because the entire computer is integrated into a chip, no signal leaves the chip until the image processing task is completed.

Although the CNN universal chip is based on analogue and logic operating principles, it has an on-chip analog-to-digital input-output interface so that at the system design and application perspective, it can be used as a digital component, just like a DSP. In particular, a development system is available for rapid design and prototyping. Moreover, a compiler, an operating system, and a user-friendly CNN high-level language, like the C language, have been developed which makes it easy to implement any image processing algorithm.

[Professor Leon Chua, University of California at Berkeley].

(1995-04-27)

Nearby terms: cellular automaton « Cellular Digital Packet Data « cellular multiprocessing « Cellular Neural Network » CELP » CEN » CENELEC

FOLDOC, Topics, A, B, C, D, E, F, G, H, I, J, K, L, M, N, O, P, Q, R, S, T, U, V, W, X, Y, Z, ?, ALL

©2018 Martin Webb