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Complex networks are a technique for the modeling and analysis of large data sets in many scientific and engineering disciplines. Due to their excessive size conventional algorithms and single core processors struggle with the efficient processing of such networks. Employing multi-core graphic processing units (GPUs) could provide sufficient processing power for the analysis of such networks. However,...
The analysis of large scale, complex networks using dynamic programming is of great use in many scientific and engineering disciplines. Current applications often require the analysis of scale-free networks with many millions of nodes and edges, presenting a huge computational challenge. Employing a distributed networks-on-chip infrastructure presents a unique opportunity of delivering power efficient...
Rapid advances in multichannel neural signal recording technologies in recent years have spawned broad applications in neuro-prostheses and neuro-rehabilitation. The dramatic increase in data bandwidth and volume associated with multichannel recording requires a significant computational effort which presents major design challenges for brain-machine interface (BMI) system in terms of power dissipation...
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