Pub Date : 1900-01-01DOI: 10.4018/978-1-61350-092-7.CH004
N. Yusoff, Ioana Sporea, André Grüning
In this chapter we give a brief overview of the biological and technical background of artificial neural networks as are used in cognitive modelling and in technical applications.This will be complemented by three instructive case studies which demonstrate the use of different neural networks in cognitive modelling
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Pub Date : 1900-01-01DOI: 10.4018/978-1-61350-092-7.CH012
K. Gomez, D. Miorandi, D. Lowe
The design of efficient routing algorithms is an important issue in dense ad hoc wireless networks. Previous theoretical work has shown that benefits can be achieved through the creation of a set of data "highways" that carry packets across the network, from source(s) to sink(s). Current approaches to the design of these highways however require a-priori knowledge of the global network topology, with consequent communications burden and scalability issues, particularly with regard to reconfiguration after node failures. In this chapter, we describe a bio-inspired approach to generating these data highways through a distributed reaction-diffusion model that uses localized convolution with activation-inhibition filters. The result is the distributed emergence of data highways that can be tuned to provide appropriate highway separation and connection to data sinks. In this chapter, we present the underlying models, algorithms, and protocols for generating data highways in a dense wireless sensor network. The proposed methods are validated through extensive simulations performed using OMNeT++.
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