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NECO
2007
150views more  NECO 2007»
14 years 9 months ago
Reinforcement Learning, Spike-Time-Dependent Plasticity, and the BCM Rule
Learning agents, whether natural or artificial, must update their internal parameters in order to improve their behavior over time. In reinforcement learning, this plasticity is ...
Dorit Baras, Ron Meir
JCNS
2010
126views more  JCNS 2010»
14 years 8 months ago
Calibration of the head direction network: a role for symmetric angular head velocity cells
Abstract Continuous attractor networks require calibration. Computational models of the head direction (HD) system of the rat usually assume that the connections that maintain HD n...
Peter Stratton, Gordon Wyeth, Janet Wiles
70
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ICASSP
2011
IEEE
14 years 1 months ago
Audio recognition in the wild: Static and dynamic classification on a real-world database of animal vocalizations
We present a study on purely data-based recognition of animal sounds, performing evaluation on a real-world database obtained from the Humboldt-University Animal Sound Archive. As...
Felix Weninger, Björn Schuller
NIPS
2008
14 years 11 months ago
Non-stationary dynamic Bayesian networks
Abstract: Structure learning of dynamic Bayesian networks provide a principled mechanism for identifying conditional dependencies in time-series data. This learning procedure assum...
Joshua W. Robinson, Alexander J. Hartemink
ESANN
2004
14 years 11 months ago
Speaker verification by means of ANNs
In text-dependent speaker verification the speech signals have to be time-aligned. For that purpose dynamic time warping (DTW) can be used which performs the alignment by minimizi...
Urs Niesen, Beat Pfister