The Tapestry Cellular Automata phase unwrapping algorithm for interferogram analysis
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In this paper we propose a hardware version for two-dimensional cellular automata. Since cellular automata are parallel systems containing a large number of simple processing elements, their hardware version is necessary for their real-time study and applications. A cellular automata chip is described both at the architectural and cell level. The paper outlines the main functions of the cellular automata chip and describes how they operate. We also present some quantitative aspects that determine the chip dimension. The chip can be succesfully used for experiments with large CA implying long-time evolution.
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Cellular Automata is one of the ways of performing computations which necessitates extremely the processing of data at a high speed. In cellular machine, a great deal of data should be processed in a short time in order to use the outcome results. There are different methods to implement cellular automata one of which is to implement cellular automata on serial bases. This article studies implementing cellular automata on serial bases and compares the speed of operation on this base for one-dimensional cellular automata using a uniform rule with that of the one-dimensional cellular automata having available cells in odd and even positions. If serial bases are use to implement cellular automata, the rule of cellular automata does not have any effect on the time spent.
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A cellular automaton consists of a lattice (consisting of cells), states, rules (which determine the next state of each cell), and a neighborhood (the surrounding cells that each cell uses in determining its next state). A standard cellular automaton advances at a discrete time interval, and changes every cell concurrently; however, we can consider cellular automata in which only a specific cell is chosen, and it, along with its neighborhood, is changed based upon the rules of the automaton. Thus, we can consider a game in which two players take turns attempting to cause the cellular automaton to achieve some specific configuration, although this configuration is possibly different for each player. My project will investigate such cellular automata, specifically ones with tic-tac-toe like winning formations (a win is created by achieving some number, say five, of one state in a row).
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This paper investigates the theoretical aspects of two-dimensional linear cellular automata with image applications.We consider geometrical and visual aspects of patterns generated by cellular automata evolution.The present work focuses on the theory of two-dimensional linear cellular automata with respect to uniform periodic and adiabatic boundary cellular automata conditions.Multiple copies of any arbitrary image corresponding to cellular automata nd so many applications in real life situation e.g.textile design, DNA genetics research, etc.
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In this chapter, the biological roots of cellular automata are described and formal definitions of cellular automata (CA) are provided. CA are characterized by a regular lattice, a set of elementary states, a local interaction interaction local , a neighborhood template cellular automaton neighborhood , and a space- and time-independent transition rule cellular automaton transition rule which is applied to each cell in the lattice. In particular, we introduce deterministic, probabilistic, and lattice-gas cellular automata cellular automaton probabilistic cellular automaton deterministic lattice-gas cellular automaton (LGCA) . Furthermore, we present strategies to analyze spatio-temporal pattern formation in cellular automaton models. In subsec. 4.4.2, the so-called mean-field theory mean-field theory approximations is presented as an approximative method to study dynamic properties of cellular automata.
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Based on the standard cellular automata, by extending the definition of cell component and cell neighborhood relation, the formal definition of extended cellular automata is proposed and the extended cellular automata is proved to be an extension of the standard cellular automata. The model of the extended cellular automata provides a new effective approach to describe complicated systems composed of interacting multiple subsystems.
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Cellular automata (CA) are discrete dynamical systems consist of a regular finite grid of cell; each cell encapsulating an equal portion of the state, and arranged spatially in a regular fashion to form an n-dimensional lattice. A cellular automata is like computers, data represented by initial configurations which is processed by time evolution to produce output. This paper is an empirical study of elementary cellular automata which includes concepts of rule equivalence, evolution of cellular automata and classification of cellular automata. In addition, explanation of behaviour of cellular automata is revealed through example.
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