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].

Last updated: 1995-04-27

Nearby terms:

Cellular Digital Packet Datacellular multiprocessingCellular Neural NetworkCELPCEN

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