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» Neural Network Trainer through Computer Networks
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FOCI
2007
IEEE
15 years 6 months ago
Opposite Transfer Functions and Backpropagation Through Time
— Backpropagation through time is a very popular discrete-time recurrent neural network training algorithm. However, the computational time associated with the learning process t...
Mario Ventresca, Hamid R. Tizhoosh
90
Voted
BMCBI
2006
109views more  BMCBI 2006»
14 years 11 months ago
GPNN: Power studies and applications of a neural network method for detecting gene-gene interactions in studies of human disease
Background: The identification and characterization of genes that influence the risk of common, complex multifactorial disease primarily through interactions with other genes and ...
Alison A. Motsinger, Stephen L. Lee, George Mellic...
ARC
2009
Springer
175views Hardware» more  ARC 2009»
15 years 6 months ago
A Hardware Accelerated Simulation Environment for Spiking Neural Networks
Spiking Neural Networks (SNNs) model the biological functions of the human brain enabling neuro/computer scientists to investigate how arrays of neurons can be used to solve comput...
Brendan P. Glackin, Jim Harkin, T. Martin McGinnit...
96
Voted
ECAI
2004
Springer
15 years 5 months ago
Towards Efficient Learning of Neural Network Ensembles from Arbitrarily Large Datasets
Advances in data collection technologies allow accumulation of large and high dimensional datasets and provide opportunities for learning high quality classification and regression...
Kang Peng, Zoran Obradovic, Slobodan Vucetic
AES
2007
Springer
78views Cryptology» more  AES 2007»
14 years 12 months ago
Reliability and performance-based design by artificial neural network
Whilst conventional approach in structural design is based on reliability-calibrated factored design formula, performance-based design customizes a solution to the specific circum...
K. W. Chau