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The Stochastic Loss of Spikes in Spiking Neural P Systems : Design and Implementation of Reliable Arithmetic Circuits

Xu Z., Cavaliere M., An P., Vrudhula S., Cao Y

Fundamenta Informaticae

2014

Vol. 134, nr 1/2

183--200

Spiking neural P systems (in short, SN P systems) have been introduced as computing devices inspired by the structure and functioning of neural cells. The presence of unreliable components in SN P systems can be considered in many different aspects. In this paper we focus on two types of unreliability: the stochastic delays of the spiking rules and the stochastic loss of spikes. We propose the implementation of elementary SN P systems with DRAM-based CMOS circuits that are able to cope with these two forms of unreliability in an efficient way. The constructed bio-inspired circuits can be used to encode basic arithmetic modules.

Tuning of agent-based computing

Byrski A.

Computer Science

2013

Vol. 14 (3)

491--512

In this paper, an Evolutionary Multi-agent system-based computing process is subjected to a detailed analysis of its parameters in order to establish a base for a better understanding of the meta-heuristics from the practitioner’s point of view. After reviewing the concepts of EMAS and its immunological variant, a series of experiments is shown, and results of the influence of the search outcomes by certain parameters is discussed.

The Artificial Immune System Approach for Smart Air-Conditioning Control

Chaczko Z., Aslanzadeh S., Kuleff J. A.

International Journal of Electronics and Telecommunications

2012

Vol. 58, No. 2

193-199

Biologically inspired computing that looks to nature and biology for inspiration is a revolutionary change to our thinking about solving complex computational problems. It looks into nature and biology for inspiration rather than conventional approaches. The Human Immune System with its complex structure and the capability of performing pattern recognition, self-learning, immune-memory, generation of diversity, noise tolerance, variability, distributed detection and optimisation - is one area that has been of strong interest and inspiration for the last decade. An air conditioning system is one example where immune principles can be applied. This paper describes new computational technique called Artificial Immune System that is based on immune principles and refined for solving engineering problems. The presented system solution applies AIS algorithms to monitor environmental variables in order to determine how best to reach the desired temperature, learn usage patterns and predict usage needs. The aim of this paper is to explore the AIS-based artificial intelligence approach and its impact on energy efficiency. It will examine, if AIS algorithms can be integrated within a Smart Air Conditioning System as well as analyse the impact of such a solution.