Autowaves and spatio-temporal chaos in CNNs. I. A tutorial

Pivka, Ladislav

doi:10.1109/81.473570

Cited by 40 publications

(41 citation statements)

References 15 publications

(9 reference statements)

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“…Among others, V. Perez-Dlunuzuri et al adopted Chua's chaos circuit to realize CNN us ing chaos circuit [5], [6]. This CNN employing Chua's chaos circuits can demonstrate binary-valued traveling wave phenomena.…”

Section: Discussionmentioning

confidence: 99%

“…The CNN using chaos circuits opens up new vistas for application systems, for example, models for the transport phenomenaa in biological and physical systems, shortest-path finding systems, and so on [1]- [7]. For this reason, many re searcher's have shown prototypes of the CNN using chaos circuits [3]- [5]. These CNNs exploit Chua's chaos circuits [8]- [10] as the cell circuits.…”

Section: Introductionmentioning

confidence: 99%

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Synthesis and analysis of a discrete-time CNN using 1-dimensional cell circuits with S stable points (S=2, 3, 4, ...)

et al. 2001

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In this paper, a discrete-time CNN using 1-dimensional cell circuits with S stable points (S=2, 3, 4,... ) is proposed. The circuit structure and the behavior of the proposed CNN is simple by exploiting discrete-time 1-dimensional circuits as the cell circuits. Since the proposed cell circuit takes as much as S of states, the proposed CNN can demonstrate the multiple-valued traveling wave phenomena. Furthermore, the proposed cell circuit is suitable for integration thanks to the circuit design by using switched-current (SI) techniques. The computer simulations are performed concerning a 2-dimensional CNN which is constructed with the proposed cell circuits. The 1-dimensional cell circuit with S stable points is designed by a standard CMOS process. Furthermore, the proposed cell circuit is built with commercially-available IC's. The experimental result is in close agreement with the simulation result. The proposed CNN is integrable by a standard CMOS technology.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Synthesis and analysis of a discrete-time CNN using 1-dimensional cell circuits with S stable points (S=2, 3, 4, ...)

et al. 2001

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“…Figure 14 shows the error of the approximated nonlinear function in Fig.13 Table 2 shows the comparison with conventional methods. In Table 2, the modeling using mutually coupled chaos circuits is one of the most famous meth ods to investigate nonlinear dynamical systems [7]- [9] . In point of accuracy, the estimation employing digital computers is the most excellent method.…”

Section: Numerical Simulationmentioning

confidence: 99%

“…In previous studies, many physical, biological and chemical systems have been studied by means of large ensembles of inter acting analog chaos circuits [7]- [9]. Among those, Pivka has modeled traveling waves by using resistor-coupled Chua's circuits [9]. However, it is difficult for these method to make rigorous models of unknown nonlin ear systems, because they cannot accurately represent the nonlinear functions.…”

Section: Introductionmentioning

confidence: 99%

“…For this reason, a chaos circuit is one of the most efficient tools for experimental observation of chaos. In previous studies, many physical, biological and chemical systems have been studied by means of large ensembles of inter acting analog chaos circuits [7]- [9]. Among those, Pivka has modeled traveling waves by using resistor-coupled Chua's circuits [9].…”

Section: Introductionmentioning

confidence: 99%

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FPGA design of a digital circuit for estimating chaotic characteristics from approximated nonlinear functions

et al. 2002

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In this paper, an FPGA circuit for estimating chaotic characteristics of unknown nonlinear systems is proposed. From particular solutions corresponding to chaotic signals of the unknown system, the proposed circuit approximates nonlinear functions. The approximation of these nonlinear functions are performed by using supervised learning. From the approximated functions, chaotic characteristics of the unknown system are estimated.An understanding of the behavior of unknown nonlinear system will be provided by uti lizing the estimated chaotic characteristics.The proposed circuit is implemented onto an FPGA by using Verilog-HDL. This implementation confirmed that the proposed circuit can achieve high-speed operation and low-cost development.

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