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» SSNNS -: a suite of tools to explore spiking neural networks
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GECCO
2008
Springer
261views Optimization» more  GECCO 2008»
10 years 5 months ago
SSNNS -: a suite of tools to explore spiking neural networks
We are interested in engineering smart machines that enable backtracking of emergent behaviors. Our SSNNS simulator consists of hand-picked tools to explore spiking neural network...
Heike Sichtig, J. David Schaffer, Craig B. Laramee
CDC
2008
IEEE
147views Control Systems» more  CDC 2008»
10 years 10 months ago
Clustering neural spike trains with transient responses
— The detection of transient responses, i.e. non– stationarities, that arise in a varying and small fraction of the total number of neural spike trains recorded from chronicall...
John D. Hunter, Jianhong Wu, John G. Milton
IJCNN
2007
IEEE
10 years 10 months ago
Compact hardware for real-time speech recognition using a Liquid State Machine
Abstract— Hardware implementations of Spiking Neural Networks are numerous because they are well suited for implementation in digital and analog hardware, and outperform classic ...
Benjamin Schrauwen, Michiel D'Haene, David Verstra...
NN
2008
Springer
150views Neural Networks» more  NN 2008»
10 years 4 months ago
Neural network based pattern matching and spike detection tools and services - in the CARMEN neuroinformatics project
In the study of information flow in the nervous system, component processes can be investigated using a range of electrophysiological and imaging techniques. Although data is diff...
Martyn Fletcher, Bojian Liang, Leslie Smith, Alast...
BMCBI
2005
126views more  BMCBI 2005»
10 years 4 months ago
GANN: Genetic algorithm neural networks for the detection of conserved combinations of features in DNA
Background: The multitude of motif detection algorithms developed to date have largely focused on the detection of patterns in primary sequence. Since sequence-dependent DNA struc...
Robert G. Beiko, Robert L. Charlebois
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