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» On the weight dynamics of recurrent learning
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ICML
2009
IEEE
14 years 9 months ago
Herding dynamical weights to learn
A new "herding" algorithm is proposed which directly converts observed moments into a sequence of pseudo-samples. The pseudosamples respect the moment constraints and ma...
Max Welling
IJCNN
2006
IEEE
14 years 2 months ago
Echo State Networks for Determining Harmonic Contributions from Nonlinear Loads
—This paper investigates the application of a new kind of recurrent neural network called Echo State Networks (ESNs) for the problem of measuring the actual amount of harmonic cu...
Joy Mazumdar, Ganesh K. Venayagamoorthy, Ronald G....
SBRN
2008
IEEE
14 years 2 months ago
Imitation Learning of an Intelligent Navigation System for Mobile Robots Using Reservoir Computing
The design of an autonomous navigation system for mobile robots can be a tough task. Noisy sensors, unstructured environments and unpredictability are among the problems which mus...
Eric A. Antonelo, Benjamin Schrauwen, Dirk Strooba...
ISCAS
1999
IEEE
73views Hardware» more  ISCAS 1999»
14 years 25 days ago
Correlation learning rule in floating-gate pFET synapses
We study the weight dynamics of the floating-gate pFET synapse and the effects of the pFET's gate and drain voltages on these dynamics. We show that we can derive a weight upd...
Paul E. Hasler, Jeff Dugger
ACSC
2008
IEEE
13 years 10 months ago
An investigation of the state formation and transition limitations for prediction problems in recurrent neural networks
Recurrent neural networks are able to store information about previous as well as current inputs. This "memory" allows them to solve temporal problems such as language r...
Angel Kennedy, Cara MacNish