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Author

Mutyam Madhu

Bio: Mutyam Madhu is an academic researcher from Indian Institute of Technology Madras. The author has contributed to research in topics: Rewriting & Recursively enumerable language. The author has an hindex of 4, co-authored 6 publications receiving 59 citations.

Papers
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Journal Article
TL;DR: This paper considers the contextual way of handling string-objects in P systems and proves that contextual P systems with rules corresponding to these variants are more powerful than ordinary contextual grammars and their variants.
Abstract: Generally, in P systems with string-objects one uses the Chomsky way of rewriting for processing the objects. In this paper we consider the contextual way of handling string-objects in P systems. We introduce some variants of contextual grammars and prove that contextual P systems with rules corresponding to these variants are more powerful than ordinary contextual grammars and their variants. We also show that one-sided contextual P systems with right-sided erased contexts and insertion contextual P systems with right-sided erased contexts are computationally complete.

17 citations

Journal ArticleDOI
TL;DR: A variant of P systems is defined, namely, probabilistic rewriting P systems, where the selection of rewriting rules is probabilists, and it is shown that, with non-zero cut-point, probable rewriting rules are chosen.
Abstract: In this paper we define a variant of P systems, namely, probabilistic rewriting P systems, where the selection of rewriting rules is probabilistic. We show that, with non-zero cut-point, probabilis...

16 citations

Journal ArticleDOI
TL;DR: It is shown that P automata characterize the recursively enumerable sets of vectors of natural numbers.
Abstract: In this paper, we propose a class of P automata in which each membrane has a state, like in tissue P systems [5], and the computation starts at some initial state and ends in a final state. Unlike the automaton considered in [2], where rules are used in sequential manner, here we consider a variant such that the rules can be applied in maximal mode (as defined in tissue P systems). We show that P automata characterize the recursively enumerable sets of vectors of natural numbers.

14 citations

Journal Article
TL;DR: It is proved that all these systems accept the family of recursively enumerable languages both in the centralized and in the non-centralized strategies and in both returning and non-returning communication modes with only two components.
Abstract: We consider automata systems consisting of several pushdown automata working in parallel and communicating the contents of their stacks by request. We show that centralized non-returning parallel communicating pushdown automata systems with three components recognize all recursively enumerable languages. We also show that centralized returning pushdown automata systems accept non-ET0L languages. We study two variants of communication: one uses filters in communication and in the other only specified number of symbols are communicated. We prove that all these systems accept the family of recursively enumerable languages both in the centralized and in the non-centralized strategies and in both returning and non-returning communication modes with only two components.

7 citations

Book ChapterDOI
TL;DR: A brief survey of some variants of P systems and their computational capacity is given and an improvement of a known result about rewriting P systems with leftmost derivation is given.
Abstract: In this paper we give a brief survey of some variants of P systems and their computational capacity. An improvement of a known result about rewriting P systems with leftmost derivation is given. We also give the generalized definition for normal forms of rewriting P systems.

3 citations


Cited by
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Journal ArticleDOI
TL;DR: This work introduces all necessary definitions of dynamical probabilistic P systems, describes the functioning of the parallel and stochastic algorithm used in computer simulation, and evaluates its time complexity.
Abstract: Dynamical probabilistic P systems are discrete, stochastic, and parallel devices, where the probability values associated with the rules change during the evolution of the system. These systems are proposed as a novel approach to the analysis and simulation of the behavior of complex systems. We introduce all necessary definitions of these systems and of their dynamical aspects, we describe the functioning of the parallel and stochastic algorithm used in computer simulation, and evaluate its time complexity. Finally, we show some applications of dynamical probabilistic P systems for the investigation of the dynamics of the Lotka-Volterra system and of metapopulation systems.

104 citations

Book ChapterDOI
14 Jun 2004
TL;DR: In this article, the authors discuss P automata, i.e., accepting P systems using in most cases only communication rules, and briefly describe the most important variants of these systems and report on their important properties, with special emphasis on their computational power and size.
Abstract: In this paper we discuss P automata, i.e., accepting P systems, using in most cases only communication rules. We briefly describe the most important variants of these systems and report on their important properties, with special emphasis on their computational power and size. We also propose some new topics and problems for future research.

56 citations

Journal ArticleDOI
TL;DR: A sequential rewriting strategy for P systems based on Gillespie's stochastic simulation algorithm is introduced, and it is shown that the resulting formalism of Stochastic P systems makes it possible to simulate biochemical processes in dynamically changing, nested compartments.
Abstract: We introduce a sequential rewriting strategy for P systems based on Gillespie's stochastic simulation algorithm, and show that the resulting formalism of stochastic P systems makes it possible to simulate biochemical processes in dynamically changing, nested compartments. Stochastic P systems have been implemented using the spatially explicit programming language MGS. Implementation examples include models of the Lotka-Volterra auto-catalytic system, and the life cycle of the Semliki Forest virus.

55 citations

Book ChapterDOI
TL;DR: This work investigates a variant of purely communicating P systems, where multisets of activators can open channels for certain objects to pass through membranes in one direction, and shows that for such systems with only one membrane and using only singleton activator and prohibitor sets, universal computational power is obtained.
Abstract: We investigate a variant of purely communicating P systems, where multisets of activators can open channels for certain objects to pass through membranes in one direction; however, the permeability of a channel can be controlled by multisets of prohibitors, too.We will show that for such systems with only one membrane and using only singleton activator and prohibitor sets, we already obtain universal computational power. When using systems with activating multisets for membrane channels only, we obtain a similar result. By showing a close correspondence to P systems with symport/antiport as introduced in [13] we can optimize some results given there.

47 citations

Journal Article
TL;DR: In this paper, a new formalization based on place/transition nets is presented, which can adopt one transition to implement the structural operational semantics of one evolving rule in P systems and utilize the incidence matrix to analyze the computation of one macro-step.
Abstract: We propose an intriguing relationship between P systems and Petri nets. For a basic model of P systems, this paper presents a new formalization based on place/transition nets, which can adopt one transition to implement the structural operational semantics of one evolving rule in P systems and utilize incidence matrix to analyze the computation of one macro-step. We also define the behavioral properties in P systems such as terminating, liveness, and boundedness based on this formalization. For a general class of P systems, we briefly describe a high-level framework called membrane Petri nets (MP-nets). MP-nets extend ordinary colored Petri nets (CPN) through introducing the dynamic features such as dissolve, divide, and move inspired by P systems. Therefore, MP-nets can be a graphical as well as an algebraic modelling tool for both generic P systems and dynamic CPN.

37 citations