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DATE
2003
IEEE
114views Hardware» more  DATE 2003»
14 years 28 days ago
Extraction of Piecewise-Linear Analog Circuit Models from Trained Neural Networks Using Hidden Neuron Clustering
This paper presents a new technique for automatically creating analog circuit models. The method extracts - from trained neural networks - piecewise linear models expressing the l...
Simona Doboli, Gaurav Gothoskar, Alex Doboli
IJCNN
2000
IEEE
14 years 19 hour ago
Analog Hardware Implementation of the Random Neural Network Model
This paper presents a simple continuous analog hardware realization of the Random Neural Network (RNN) model. The proposed circuit uses the general principles resulting from the u...
Hossam Abdelbaki, Erol Gelenbe, Said E. El-Khamy
NECO
2010
147views more  NECO 2010»
13 years 6 months ago
Connectivity, Dynamics, and Memory in Reservoir Computing with Binary and Analog Neurons
Abstract: Reservoir Computing (RC) systems are powerful models for online computations on input sequences. They consist of a memoryless readout neuron which is trained on top of a ...
Lars Büsing, Benjamin Schrauwen, Robert A. Le...
NIPS
2008
13 years 9 months ago
On Computational Power and the Order-Chaos Phase Transition in Reservoir Computing
Randomly connected recurrent neural circuits have proven to be very powerful models for online computations when a trained memoryless readout function is appended. Such Reservoir ...
Benjamin Schrauwen, Lars Buesing, Robert A. Legens...
TNN
2010
234views Management» more  TNN 2010»
13 years 2 months ago
Novel maximum-margin training algorithms for supervised neural networks
This paper proposes three novel training methods, two of them based on the back-propagation approach and a third one based on information theory for Multilayer Perceptron (MLP) bin...
Oswaldo Ludwig, Urbano Nunes