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» Neural networks for computational neuroscience
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ICANN
2010
Springer
15 years 4 months ago
Dynamics and Function of a CA1 Model of the Hippocampus during Theta and Ripples
The hippocampus is known to be involved in spatial learning in rats. Spatial learning involves the encoding and replay of temporally sequenced spatial information. Temporally seque...
Vassilis Cutsuridis, Michael E. Hasselmo
FOCI
2007
IEEE
16 years 23 days 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
SENSYS
2006
ACM
16 years 12 days ago
Capturing high-frequency phenomena using a bandwidth-limited sensor network
Small-form-factor, low-power wireless sensors—motes—are convenient to deploy, but lack the bandwidth to capture and transmit raw high-frequency data, such as human voices or n...
Ben Greenstein, Christopher Mar, Alex Pesterev, Sh...

Book
640views
17 years 5 months ago
Introduction to Pattern Recognition
"Pattern recognition techniques are concerned with the theory and algorithms of putting abstract objects, e.g., measurements made on physical objects, into categories. Typical...
Sargur Srihari
IJCNN
2007
IEEE
16 years 22 days ago
Parallel Learning of Large Fuzzy Cognitive Maps
— Fuzzy Cognitive Maps (FCMs) are a class of discrete-time Artificial Neural Networks that are used to model dynamic systems. A recently introduced supervised learning method, wh...
Wojciech Stach, Lukasz A. Kurgan, Witold Pedrycz