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Our brain continuously self-organizes to construct and maintain an internal representation of the world based on the information arriving through sensory stimuli. Remarkably, cortical areas related to different sensory modalities appear to share the same f ...
We present a new programmable neighborhood mechanism for hardware implemented Kohonen self-organizing maps (SOMs) with three different map topologies realized on a single chip. The proposed circuit comes as a fully parallel and asynchronous architecture. T ...
Institute of Electrical and Electronics Engineers2011
The connectivity of a neuronal network has a major effect on its functionality and role. It is generally believed that the complex network structure of the brain provides a physiological basis for information processing. Therefore, identifying the network’ ...
Inference from data is of key importance in many applications of informatics. The current trend in performing such a task of inference from data is to utilise machine learning algorithms. Moreover, in many applications that it is either required or is pref ...
We consider the problem of finding the minimum number of transmissions in an ad-hoc network for all-to-all broadcasting using network coding. This work generalizes previous results for canonical topologies such as the circle and the wrap around grid to the ...
Analytic queueing network models constitute a flexible tool for the study of network flow. These aggregate models are simple to manipulate and their analytic aspect renders them suitable for use within an optimization framework. Analytic queueing network m ...
Analytic queueing network models often assume infinite capacity for all queues. For real systems this infinite capacity assumption does not hold, but is often maintained due to the difficulty of grasping the between-queue correlation structure present in f ...
Distributed adaptive algorithms are proposed to address the problem of estimation in distributed networks. We extend recent work by relying on static and adaptive diffusion strategies. The resulting adaptive networks are robust to node and link failures an ...
Analytic queueing network models constitute a flexible tool for the study of network flow. These aggregate models are simple to manipulate and their analytic aspect renders them suitable for use within an optimization framework. Analytic queueing network m ...
In this paper we develop a multi-agent simulation model to explore the issue of learning in interorganizational networks. Though interorganizational network researchers generally agree that when firms form into networks they will gain access to new knowled ...