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].
