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IPPS
2010
IEEE
13 years 5 months ago
Acceleration of spiking neural networks in emerging multi-core and GPU architectures
Recently, there has been strong interest in large-scale simulations of biological spiking neural networks (SNN) to model the human brain mechanisms and capture its inference capabi...
Mohammad A. Bhuiyan, Vivek K. Pallipuram, Melissa ...
CHI
2003
ACM
14 years 8 months ago
Containers: a new hierarchical model for browser interfaces
The development of a low bandwidth, high error tolerant neural browser, called the BrainBrowser, has raised new navigational issues. With this paradigm shift of twodimensional spa...
Chad Owens
ACSC
2008
IEEE
13 years 9 months ago
An investigation of the state formation and transition limitations for prediction problems in recurrent neural networks
Recurrent neural networks are able to store information about previous as well as current inputs. This "memory" allows them to solve temporal problems such as language r...
Angel Kennedy, Cara MacNish
NCA
2007
IEEE
13 years 7 months ago
Using evolution to improve neural network learning: pitfalls and solutions
: Autonomous neural network systems typically require fast learning and good generalization performance, and there is potentially a trade-off between the two. The use of evolutiona...
John A. Bullinaria
AMC
2008
99views more  AMC 2008»
13 years 8 months ago
Markov chain network training and conservation law approximations: Linking microscopic and macroscopic models for evolution
In this paper, a general framework for the analysis of a connection between the training of artificial neural networks via the dynamics of Markov chains and the approximation of c...
Roderick V. N. Melnik