Systematic Design For Emergence In Cellular Nonlinear Networks With Applications In Natural Computing And Signal Processing 9783540768005 31120 pdf (3540768009)

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Radu Dogaru, «Systematic Design for Emergence in Cellular Nonlinear Networks»

The main problem addressed in this book came out during a Fulbright research fellowship stage at U.C. Berkeley (California, USA, 1996–1998). Then, I had the opportunity to work in the research group of Leon Chua on a subject called CNN (cellular neural/nonlinear network). The CNN, developed in the end of the 1980s was an important step ahead in getting cellular computing closer to practical applications. The CNN is actually a cellular array made of many identical elements interconnected in a neighborhood. But unlike the cellular automata (CA) the CNN was designed as a circuit-oriented architecture being developed up to the point where it serves as a low-power smart sensor or visual microprocessor capable to acquire and process images or multi-dimensional signals in general with processing speeds of the order of 1012 (Tera) operations per second. Today, there are several academic and industrial groups providing CNN-based solutions for various practical problems, particularly when high speed processing at low power is needed. Also, researchers in the area of nano-technology recognize cellular computing as a suitable computing paradigm to the specific of these technologies where many identical active elements are available on a mass proportion. Researchers in biology also recognize the cellular paradigm as a well-suited paradigm for models of natural systems. Indeed there is a similarity, as biological systems essentially are functionally meaningful aggregates of mostly local interconnected cells. A brief review of the cellular computing paradigm, its relation to natural computing in general and the state of the art of its use in applications are given in Chaps. 1 and 2 of this book.

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