Cellular Neural Networks, Multi-Scroll Chaos And by Johan A K Suykens, Joos P L Vandewalle, Mustak E Yalcin

By Johan A K Suykens, Joos P L Vandewalle, Mustak E Yalcin

For engineering purposes which are in response to nonlinear phenomena, novel info processing structures require new methodologies and layout rules. this angle is the root of the 3 cornerstones of this booklet: mobile neural networks, chaos and synchronization. mobile neural networks and their common computer implementations provide a well-established platform for processing spatial-temporal styles and wave computing. Multi-scroll circuits are generalizations to the unique Chua's circuit, resulting in chip implementable circuits with more and more advanced attractors. numerous functions utilize synchronization concepts for nonlinear platforms. a scientific evaluation is given for Lur'e representable platforms with worldwide synchronization standards for master-slave and mutual synchronization, powerful synchronization, H synchronization, time-delayed structures and impulsive synchronization.

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Additional info for Cellular Neural Networks, Multi-Scroll Chaos And Synchronization (World Scientific Series on Nonlinear Science)

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For a comprehensive bibliography of the many papers written on Chua's circuit, we refer to Chua's historical overview paper [40], which summarizes the main achievements 10 years after its discovery. 1 Chaos in Chua's circuit The Shilnikov method The chaotic nature of the double scroll attractor was proved by Chua et al. [45] by establishing the existence of a homoclinic loop of the saddle focus 48 Cellular Neural Networks, Multi-Scroll Chaos and Synchronization Fig. 2 Phase portrait of the (a) double scroll, (b) spiral, and (c) double hook attractor obtained from Chua's equation.

The algorithm has three instructions which run consecutively. 5, the output of the instruction $3 for the cell dj is settled. Essential features of wave computing on a StISC are [209]: • • • • non-equilibrium type spatial-temporal elementary instructions, spatial logic instruction on masks, spatial-temporal combination of image flows, algorithms using the above three types of instructions. In Chapter 4 of [206], it has been shown that a properly controlled wave computing technique can be efficiently used in segmentation, shape and structure detection/recovery tasks.

Cellular Neural/Nonlinear Networks 39 In a second experiment, it is shown that new autowave sources, called external sources, can be located at any place on the network. A source can be located with black dots on the initial and input images. 10(a) (the box around the figure is not a part of the image) a source is located on the left-bottom corner. Two consecutive snapshots depict the obtained autowave in time. 10(b). While one is the internal source of the network, the other one is located at the black dot.

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