Reaction-diffusion chip implementing excitable lattices with multiple-valued cellular automata

Matsubara, Hiroshi; Asai, Tetsuya; Hirose, Takahisa; Amemiya, Yoshihito

doi:10.1587/elex.1.248

Cited by 18 publications

(4 citation statements)

References 3 publications

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“…having at least one stable and active equilibrium point). On the opposite, wave-type dynamics is favored by the selection of parameter points in the UA (unstable and active) regions of the parameter space (5,6,7,9,10,13). It was also found that most interesting emergent behaviors occur taking cell parameter points from those regions (type 6 to 13) associated with a maximum number of equilibrium points (3 in our case).…”

Section: Locating Emergent Behaviors Genesmentioning

confidence: 54%

“…The advantage of using RD-CNNs for building image processors stands in their inherent parallelism and very simple coupling (resistive grids). Several analogue chips were already proposed in the literature [10] [11][12] [13], although we consider that from a practical point of view, digital models would be better. Speeding-up such models using GPU/CUDA approaches [14] are also convenient solutions in terms of good ratios between performances and costs.…”

Section: Introductionmentioning

confidence: 99%

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Applications of Emergent Computation in Reaction-Diffusion CNNs for Image Processing

Dogaru

2013

2013 19th International Conference on Control Systems and Computer Science

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The possibility to exploit emergent computation in a naturally inspired complex network, namely the reactiondiffusion cellular nonlinear network (RD-CNN), is investigated. The particular application under focus is image processing. It is shown that by implementing a simplified discrete-time model and by using the local activity theory to locate potentially useful regions in the huge parameter space, many useful image processing tasks may be performed in reasonable execution time. Such tasks may include but are not limited to: feature extraction, image enhancement, noise removal, pattern formation, etc. A framework is provided for a systematic design allowing the identification of useful genes (sets of parameters) associated with meaningful image processing tasks.

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Section: Locating Emergent Behaviors Genesmentioning

confidence: 54%

Section: Introductionmentioning

confidence: 99%

Applications of Emergent Computation in Reaction-Diffusion CNNs for Image Processing

Dogaru

2013

2013 19th International Conference on Control Systems and Computer Science

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“…These LSIs, also known as RD chips, were generally influenced by Cellular Neural Networks (CNNs) or Cellular Automata (CA) rules, whereas using digital, analog, or mixed-signal complementary-metal-oxidesemiconductor (CMOS) circuits. Several CA and CNN models of RD systems [68][69][70][71][72], as well as fundamental RD Equations [73][74][75][76] were implemented using electrical cell circuits that emulate chemical reactions. In this design, each cell is placed on a two-dimensional (2-D) rectangular or hexagonal grid and coupled with nearby cells via appropriate devices that imitate 2-D spatial dissipation of chemical species and, like traditional CAs, propagate the state of the central cell to its neighbors.…”

Section: Implementing Reaction-diffusion Dynamics On Memristor-based Lsimentioning

confidence: 99%

Chemical Wave Computing from Labware to Electrical Systems

et al. 2022

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Unconventional and, specifically, wave computing has been repeatedly studied in laboratory based experiments by utilizing chemical systems like a thin film of Belousov–Zhabotinsky (BZ) reactions. Nonetheless, the principles demonstrated by this chemical computer were mimicked by mathematical models to enhance the understanding of these systems and enable a more detailed investigation of their capacity. As expected, the computerized counterparts of the laboratory based experiments are faster and less expensive. A further step of acceleration in wave-based computing is the development of electrical circuits that imitate the dynamics of chemical computers. A key component of the electrical circuits is the memristor which facilitates the non-linear behavior of the chemical systems. As part of this concept, the road-map of the inspiration from wave-based computing on chemical media towards the implementation of equivalent systems on oscillating memristive circuits was studied here. For illustration reasons, the most straightforward example was demonstrated, namely the approximation of Boolean gates.

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“…What is imitated in CA can be imitated in CNN and both offer powerful modelling capability as well. There are several studies published on CNN/CA or hybrid models of reaction-diffusion [6,7,8,9,10,11,12,13,14,15] and prototyping of chemical computers [16,17,18,19,20,21] and molecular computers [22], spatial dynamics of bacterial colonies [23,24,25,26,27]. Other approaches relevant to CNN modelling of MFCs are CA models of fuel loading patterns in nuclear reactors [28], dynamics of nuclear reactors [29,30,31,32], neutron transport [33], waste water treatment by aerobic granules [34], sequencing batch reactor [35], fluid flow in a porous medium [36].…”

Section: Introductionmentioning

confidence: 99%