Tseren-Onolt Ishdorj

Boolean circuits and a DNA algorithm in membrane computing

In the present paper we propose a way to simulate Boolean gates and circuits in the framework of P systems with active membranes using inhibiting/de-inhibiting rules. This new approach on the simulation of Boolean gates has the advantage of a self-embedded synchronization, an extra system to solve this problem not being needed. Moreover, the number of membranes and objects we use for the simulation of Boolean gates is only two. NP-complete problems, particularly CIRCUIT-SAT, are also considered here. In addition, we simulate a ‘DNA-like’ way of (experimentally) solving SAT problem using the tools given by polarization, merging, and separation in P systems.

Inhibiting/de-inhibiting rules in p systems

We introduce in the P systems area a mechanism, inspired from neural-cell behavior, which controls computations by inhibiting and de-inhibiting evolution rules. We investigate the computational power of this mechanism in both generative and accepting P systems. In particular, we prove that universality can be obtained by using one catalyst. If we use only non-cooperative rules and one membrane, then we can obtain at least the family of Parikh images of the languages generated by ET0L systems. Several research proposals are also suggested.

Modeling neural processes in lindenmayer systems

Computing in nature as is the case with the human brain is an emerging research area in theoretical computer science. The present papers aim is to explore biological neural cell processes of interest and to model them with foundational concepts of computer science. We have started by discovering and studying certain primitive symbolic neural operations of neuron functions, and we have formalized them with Lindenmayer (L) systems.