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DATE
2003
IEEE
114views Hardware» more  DATE 2003»
13 years 10 months 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
13 years 9 months 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 3 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 6 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»
12 years 11 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