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Implementing Sorting Networks with Spiking Neural P Systems

100%

Ceterchi R. , Tomescu A. I.

Fundamenta Informaticae

2008

tom Vol. 87, nr 1

35-48

Spiking neural P systems simulate the behavior of neurons sending signals through axons. Recently, some applications concerning Boolean circuits and sorting algorithms have been proposed. In this paper, we study the ability of such systems to simulate a well known parallel sorting model, sorting networks. First, we construct spiking neural P systems which act as comparators of two values, and then show how to assemble these building blocks according to the topology of a sorting network of N values. In the second part of the paper, we formalize a framework to transform any sorting network into a network composed of comparators which sort n values, 2 < n < N, having the same behaviour as the original sorting network, but using fewer neurons and synapses than the direct simulation. A comparison between the two models proposed here and the sorting model of Ionescu and Sburlan is also given.

Mapping Sets and Hypersets into Numbers

80%

D’Agostino G. , Omodeo E. G. , Policriti A. , Tomescu A. I.

Fundamenta Informaticae

2015

tom Vol. 140, nr 3/4

307--328

We introduce and prove the basic properties of encodings that generalize to non-wellfounded hereditarily finite sets the bijection defined by Ackermann in 1937 between hereditarily finite sets and natural numbers.