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Pure Infinitely Self-Modifying Code is Realizable and Turing-complete

Morse G.

International Journal of Electronics and Telecommunications

2018

Vol. 64, No. 2

123--129

Although self-modifying code has been shyed away from due to its complexity and discouragement due to safety issues, it nevertheless provides for a very unique obfuscation method and a different perspective on the relationship between data and code. The generality of the von Neumann architecture is hardly realized by today’s processor models. A code-only model is shown where every instruction merely modifies other instructions yet achieves the ability to compute and Turing machine operation is easily possible.

A Note on Spiking Neural P Systems with Homogenous Neurons and Synapses

Yu Y., Wu T., Xu J., Wang Y., He J.

Fundamenta Informaticae

2017

Vol. 150, nr 2

231--240

Spiking neural (SN, for short) P systems are a class of computation models inspired from the way in which neurons communicate by exchanging spikes. SN P systems with homogenous neurons and synapses are a new variant of SN P systems, where the spiking and forgetting rules are placed on synapses instead of in neurons and each synapse has the same set of spiking and forgetting rules. Recent studies illustrated that this variant of SN P systems is Turing universal as both number generating and accepting devices. In this note, we prove that SN P systems with homogenous neurons and synapses without the feature of delay are also Turing universal. This result gives a positive answer to an open problem formulated in [K. Jiang, et al. Neurocomputing 171(2016) 1548-1555] “whether SN P systems with homogenous neurons and synapses are Turing universal when the feature of delay is not used”.

Small Universal Spiking Neural P Systems with Homogenous Neurons and Synapses

Wu T., Wang Y., Jiang S., Shi X.

Fundamenta Informaticae

2016

Vol. 149, nr 4

451--470

Spiking neural (SN, for short) P systems are a class of distributed parallel computing models inspired by the way in which neurons communicate with each other by means of electrical impulses. Recently, a new variant of SN P systems, called SN P systems with homogenous neurons and synapses (HRSSN P systems for short) was proposed, where the spiking and forgetting rules are placed on synapses instead of in neurons and each synapse has the same set of spiking and forgetting rules. This variant of SN P systems has already been proved to be Turing universal as both number generating and accepting devices. In this work, we consider the problem of looking for small universal HRSSN P systems. Specifically, a universal HRRSN P system with standard rules and weight at most 5 having 70 neurons is constructed as a device of computing functions; as a number generator, we find a universal system with standard rules and weight at most 5 having 71 neurons.