Generating Efficient Techniques for Information Extraction and Processing Using Cellular Automata

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Author(s): Subrata Paul (Vignan Institute of Technology and Management, India)and Anirban Mitra (Vignan Institute of Technology and Management, India)
Copyright: 2017
Pages: 25
Source title: Bio-Inspired Computing for Information Retrieval Applications
Source Author(s)/Editor(s): D.P. Acharjya (School of Computing Science and Engineering, VIT University, India)and Anirban Mitra (Vignan Institute of Technology and Management, India)
DOI: 10.4018/978-1-5225-2375-8.ch008

Keywords: Biologically-Inspired Computing / Information Retrieval / Information Science Reference / Medicine & Healthcare

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Abstract

The evolution of Cellular automaton has proved to be very efficient in carrying out arbitrary information processing. A significant application lies in the theory and practice of finding a technique for unifying the information processing. But, in this case the structures used in conventional computer languages are largely inappropriate. The definite organization of computer memory into named areas, stacks, and so on, is not suitable for cellular automata in which processing elements are not distinguished from memory elements. Rather it can be assumed that the data could be represented by an object like a graph, on which transformations can be performed in parallel. This chapter initiate with basic literature on cellular automata, related definitions and notations and focuses on its applications in information processing.

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Generating Efficient Techniques for Information Extraction and Processing Using Cellular Automata

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