### Abstract

Current very-large-scale integration (VLSI) technologies provide for the fabrication of chips with several million transistors. With these technologies a single chip may contain one powerful digital processor, a huge memory containing millions of very simple units placed in a regular structure, and other complex functions. A powerful combination of a simple logic processor placed in a regular structure is the cellular automaton invented by John von Neumann. The cellular automaton is a highly parallel computer architecture. Although many living neural circuits resemble this architecture, the neurons do not function in a simple logical mode: they are analog “devices.” The cellular neural network architecture, invented by Chua and his graduate student Yang [1], has both the properties: the cell units are nonlinear continuoustime dynamic elements placed in a cellular array. Of course, the resulting nonlinear dynamics in space could be extremely complex. The inventors, however, showed that these networks can be designed and used for a variety of engineering purposes, while maintaining stability and keeping the dynamic range within well-designed limits. Subsequent developments have uncovered the many inherent capabilities of this architecture (IEEE conferences: CNNA-90, CNNA-92, CNNA-94, 96, 98, 00, 02; Special issues: International Journal of Circuit Theory and Applications, 1993, 1996, 1998, 2002; and IEEE Transactions on Circuits and Systems, I and II, 1993, 1999, etc.). In the circuit implementation, unlike analog computers or general neural networks, the cellular neural/nonlinear network (CNN) cells are not the ubiquitous highgain operational amplifiers. In most practical cases, they are either simple unity-gain amplifiers or simple second-or third-order simple dynamic circuits with one to two simple nonlinear components. Tractability as well as the trillion operations per second (TeraOPS) computing speed in a single chip are but some of the many attractive properties of cellular neural networks. The trade-off is in the accuracy; however, in many cases, the accuracy achieved with current technologies is enough to solve a lot of real-life problems.

Original language | English |
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Title of host publication | Feedback, Nonlinear, and Distributed Circuits |

Publisher | CRC Press |

Pages | 15-1-15-19 |

ISBN (Electronic) | 9781420058826 |

ISBN (Print) | 1420058819, 9781420058819 |

Publication status | Published - Jan 1 2009 |

### ASJC Scopus subject areas

- Engineering(all)
- Computer Science(all)

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## Cite this

*Feedback, Nonlinear, and Distributed Circuits*(pp. 15-1-15-19). CRC Press.