Download Brain-Inspired Computing: International Workshop, BrainComp by Lucio Grandinetti, Thomas Lippert, Nicolai Petkov PDF

By Lucio Grandinetti, Thomas Lippert, Nicolai Petkov

This ebook constitutes the completely refereed convention court cases of the overseas Workshop on Brain-inspired Computing, BrainComp 2013, held in Cetraro, Italy, in July 2013. The sixteen revised complete papers have been rigorously reviewed and chosen from quite a few submissions and canopy themes akin to mind constitution and serve as as a neuroscience standpoint, computational versions and brain-inspired computing, HPC and visualization for human mind simulations.

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Additional info for Brain-Inspired Computing: International Workshop, BrainComp 2013, Cetraro, Italy, July 8-11, 2013, Revised Selected Papers

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The meta-simulation language PyNN [32] takes a step in this direction by striving to provide both a model specification language with a high degree of expressiveness, and the ability to instantiate and run the model with different simulation engines. The developer community of NEST maintains the NEST backend of PyNN and contributes to the improvement of the model specification language. Full-scale simulations of the human brain at the resolution of neurons and synapses addressed by NEST require the use of exa-scale supercomputers.

2 for 2D examples), the so-called N-jet of Gaussian derivatives [36]. A Gaussian derivative is a regularized derivative. It has been shown that Gaussian blurring is equivalent to Tikhonov regularization [16]. e. by the convolution integral. It may be counterintuitive to perform a blurring operation when differentiating, but there is no way out: differentiation always involves some blurring by necessity. The scale σ of the differential operator cannot be taken arbitrarily small. There is a fundamental limit to the upper and lower bound of the scale σ given the order of differentiation, accuracy and scale [16].

Supercomputers ready for use as discovery machines for neuroscience. Front. Neuroinform. 6, 26 (2012) 25. RIKEN BSI: Largest neuronal network simulation achieved using K computer. Press release, 2 August 2013 26. : PyNEST: a convenient interface to the NEST simulator. Front. Neuroinf. 2, 12 (2009) 27. : CyNEST: a maintainable Cython-based interface for the NEST simulator. Front. Neuroinf. 8, 23 (2014) 28. : Meeting the memory challenges of brain-scale simulation. Front. Neuroinform. J. van Albada et al.

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