Looking for the lost noise

Gheorghe, Ștefan

doi:10.1109/smicnd.1998.733816

Cited by 3 publications

(3 citation statements)

References 2 publications

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“…The complexity of the resulting structure, as a digital system, is depending on the number of cells' states, the number of cells (the dimension), and the dimension of the neighborhood, related to the type of interconnection network [9].…”

Section: The Model-ideal and Realmentioning

confidence: 99%

“…Another important trend of research is to improve the properties of the pseudorandom sequence introducing more substantial modifications to the cellular automata model, in order to obtain a more complex structure and expected behavior. A first example, presented in [9], uses a homogenous programmable cellular automata of 256 cells, with a global feedback loop. Each cell supports any of the 256 possible rules, but the actual rule is selected by the feedback (depending on the global state, with a simple transformation like module 2 sum).…”

Section: Examples Based On Variations Of the Cellular Automata Modelmentioning

confidence: 99%

“…The technique of self-programming, meaning that the local rules are changed during the evolution, was presented in [27]. The local rules are changed based on local conditions (in [9], the global configuration determines the rule). The result is a hierarchical structure of cellular automata.…”

Section: Examples Based On Variations Of the Cellular Automata Modelmentioning

confidence: 99%

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Cellular Automata and Randomization: A Structural Overview

Dascălu¹

2018

From Natural to Artificial Intelligence - Algorithms and Applications

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The chapter overviews the methods, algorithms, and architectures for random number generators based on cellular automata, as presented in the scientific literature. The variations in linear and two-dimensional cellular automata model and their features are discussed in relation to their applications as randomizers. Additional memory layers, functional nonuniformity in space or time, and global feedback are examples of such variations. Successful applications of cellular automata random number/signal generators (both software and hardware) reported in the scientific literature are also reviewed. The chapter includes an introductory presentation of the mathematical (ideal) model of cellular automata and its implementation as a computing model, emphasizing some important theoretical debates regarding the complexity and universality of cellular automata.

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Section: The Model-ideal and Realmentioning

confidence: 99%

Section: Examples Based On Variations Of the Cellular Automata Modelmentioning

confidence: 99%

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Cellular Automata and Randomization: A Structural Overview

Dascălu¹

2018

From Natural to Artificial Intelligence - Algorithms and Applications

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A VLSI implementation of cellular automata randomizers

Dascălu

Franti²

IEEE. APCCAS 1998. 1998 IEEE Asia-Pacific Conference on Circuits and Systems. Microelectronics and Integrating Systems. Proceed

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The paper presents the general design of integrated cellular automata randomizers. An importani aim of the paper is to highlight the specificity of pseudo-random sequence generation between other cellular automata applications and to present the structures and types of output of cellular automatabased pseudo-random sequence generator. The paper also presents a new model of generalized cellular automata, that include a supplementary memory layer for improving the statistical properties of the random signal and sequence generator. One important aspect of the dynamics of cellular automata is that in many cases there are no means to predict the behavior of the system (excepting, of course, to run the system itself).Therefore, in these cases -which are also the cases most appropriate for our application -the experiment is the only one solution to guarantee the quality of the generator. The VLSI implementation of cellular automata randomizers is dedicated first of all for testing the properties of these randomizers.

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A Recursive Growing & Featuring Mechanism for Nanocomputing Structures

Maliţa

Gheorghe

2018

Proceedings of the 14th IEEE/ACM International Symposium on Nanoscale Architectures

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Looking for the lost noise

Cited by 3 publications

References 2 publications

Cellular Automata and Randomization: A Structural Overview

Cellular Automata and Randomization: A Structural Overview

A VLSI implementation of cellular automata randomizers

A Recursive Growing & Featuring Mechanism for Nanocomputing Structures

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