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» VLSI Implementation of Neural Networks
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IPPS
1998
IEEE
13 years 12 months ago
Hyper Butterfly Network: A Scalable Optimally Fault Tolerant Architecture
Boundeddegreenetworks like deBruijn graphsor wrapped butterfly networks are very important from VLSI implementation point of view as well as for applications where the computing n...
Wei Shi, Pradip K. Srimani
IJCNN
2007
IEEE
14 years 2 months ago
A Hardware-friendly Support Vector Machine for Embedded Automotive Applications
— We present here a hardware–friendly version of the Support Vector Machine (SVM), which is useful to implement its feed–forward phase on limited–resources devices such as ...
Davide Anguita, Alessandro Ghio, Stefano Pischiutt...
KES
2004
Springer
14 years 1 months ago
Towards Cortex Sized Artificial Nervous Systems
We characterize the size and complexity of the mammalian cortices of human, macaque, cat, rat, and mouse. We map the cortical structure onto a Bayesian confidence propagating neura...
Christopher Johansson, Anders Lansner
ACL
1994
13 years 9 months ago
Dual-Coding Theory and Connectionist Lexical Selection
We introduce the bilingual dual-coding theory as a model for bilingual mental representation. Based on this model, lexical selection neural networks are implemented for a connecti...
Ye-Yi Wang
JMLR
2010
227views more  JMLR 2010»
13 years 6 months ago
PyBrain
PyBrain is a versatile machine learning library for Python. Its goal is to provide flexible, easyto-use yet still powerful algorithms for machine learning tasks, including a vari...
Tom Schaul, Justin Bayer, Daan Wierstra, Yi Sun, M...