Memristive learning cellular automata for edge detection

Karamani, Rafailia-Eleni; Fyrigos, Iosif-Angelos; Tsakalos, Karolos-Alexandros; Ntinas, Vasileios; Tsompanas, Michail‐Antisthenis; Sirakoulis, Georgios Ch.

doi:10.1016/j.chaos.2021.110700

Cited by 14 publications

(2 citation statements)

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“…In addition, memristor-based CA has been suggested for image processing in medical applications [42], pseudorandomness generation [43], the simulation of the propagation of epileptic brain activity [44], and the development of patterns via simulating the Game of Life [45]. Moreover, a unique strategy for edge detection using memristor-based CA has been developed by including the adaptation of CA's neighborhood [46]. Aside from their early uses, memristorbased CA lack a general architecture that would allow a broad range of individuals to utilize this computational tool.…”

Section: Introductionmentioning

confidence: 99%

MemCA: All-Memristor Design for Deterministic and Probabilistic Cellular Automata Hardware Realization

et al. 2023

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Inspired by the behavior of natural systems, Cellular Automata (CA) tackle the demanding long-distance information transfer of conventional computers by the massive parallel computation performed by a set of locally-coupled dynamical nodes. Although CA are envisioned as powerful deterministic computers, their intrinsic capabilities are expanded after the memristor's probabilistic switching is introduced into CA cells, resulting in new hybrid deterministic and probabilistic memristor-based CA (MemCA). In the proposed MemCA hardware realization, memristor devices are incorporated in both the cell and rule modules, composing the very first all-memristor CA hardware, designed with mixed CMOS/Memristor circuits. The proposed implementation accomplishes high operating speed and reduced area requirements, exploiting also memristor as an entropy source in every CA cell. MemCA's functioning is showcased in deterministic and probabilistic operation, which can be externally modified by the selection of programming voltage amplitude, without changing the design. Also, the proposed MemCA system includes a reconfigurable rule module implementation that allows for spatial and temporal rule inhomogeneity.

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Section: Introductionmentioning

confidence: 99%

MemCA: All-Memristor Design for Deterministic and Probabilistic Cellular Automata Hardware Realization

et al. 2023

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“…Interesting computational properties feature CA, such as mass parallelism, local interactions, and emerging computation (Karamani et al. 2021 ). Therefore, CA usually provide the operational framework for complex models that simulate physical systems.…”

Section: Introductionmentioning

confidence: 99%

A GIS-aided cellular automata system for monitoring and estimating graph-based spread of epidemics

Kyriakou¹,

Georgoudas²,

Papanikolaou³

2022

Nat Comput

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In this study, we introduce an application of a Cellular Automata (CA)-based system for monitoring and estimating the spread of epidemics in real world, considering the example of a Greek city. The proposed system combines cellular structure and graph representation to approach the connections among the area’s parts more realistically. The original design of the model is attributed to a classical SIR (Susceptible–Infected–Recovered) mathematical model. Aiming to upgrade the application’s effectiveness, we have enriched the model with parameters that advances its functionality to become self-adjusting and more efficient of approaching real situations. Thus, disease-related parameters have been introduced, while human interventions such as vaccination have been represented in algorithmic manner. The model incorporates actual geographical data (GIS, geographic information system) to upgrade its response. A methodology that allows the representation of any area with given population distribution and geographical data in a graph associated with the corresponding CA model for epidemic simulation has been developed. To validate the efficient operation of the proposed model and methodology of data display, the city of Eleftheroupoli, in Eastern Macedonia—Thrace, Greece, was selected as a testing platform (Eleftheroupoli, Kavala). Tests have been performed at both macroscopic and microscopic levels, and the results confirmed the successful operation of the system and verified the correctness of the proposed methodology.

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