Showing papers by "Kamala Krithivasan published in 2000"
TL;DR: This paper initially considers representation of 2D black–white images and 3D objects using finite state automata, and defines minimization of WFAs and presents an algorithm to minimize a WFA.
Abstract: In this paper, we initially consider representation of 2D black–white images and 3D objects using finite state automata. We describe transformation of scaling on the 2D image by an operation on the FSA. We also give constructions for getting the projections of a 3D object on to coordinate planes and for reconstructing the 3D object from its projections. We define minimization of nondeterministic FSAs and give an O(e2) (e is the number of edges in the FSA) algorithm for minimization of NFAs. Later, we define a WFA and describe various properties of WFA. We define four normal forms of WFA and show how a WFA can be normalized into any of these forms. We show the equivalence of WFAs with ∊ edges and ∊-free WFAs. Then, we define minimization of WFAs and present an algorithm to minimize a WFA.
5 citations
Journal Article•
2 citations
TL;DR: It is proved that control languages indeed add to the power of contextual grammars and investigate certain hierarchy results.
Abstract: Contextual Grammars arc widely investigated as models of natural languages and currently find applications related to DNA Computing. In this paper, we extend the concept of control languages to contextual grammars. We prove that control languages indeed add to the power of contextual grammars and investigate certain hierarchy results.
2 citations
TL;DR: The problem of approximately matching matrix languages is considered, given a matrix grammar M, a cost function and an input image I, and algorithms to approximately match the input image with images generated by the grammar are given.
Abstract: In this paper we consider the problem of exact and approximate matching of matrix languages. In the exact image testing problem, we have given polynomial time algorithms for the membership problem for matrix grammars. We then consider the problem of approximately matching matrix languages. Given a matrix grammar M, a cost function and an input image I, we give algorithms to approximately match the input image with images generated by the grammar. The algorithms return the cost of matching the input image with an image generated by the matrix grammar. These approximation schemes can be used for pattern recognition.
1 citations
21 Aug 2000
TL;DR: In this article, the authors consider several classes of P systems with symbol-objects where the catalysts can move in and out of a membrane, and prove universality results for these variants with a very small number of membranes.
Abstract: P systems, introduced by Gh. P?un, form a new class of distributed computing models. Many variants of P systems were shown to be computationally universal. In this paper, we consider several classes of P systems with symbol-objects where we allow the catalysts to move in and out of a membrane. We prove universality results for these variants of P systems with a very small number of membranes.