Publications associées à Optimization of high order perceptrons

Power Efficient Hardware Implementation of a Fuzzy Neural Network

This paper presents a digital, transistor level implemented neo-fuzzy neural network. This type of neural network is particularly well suited for real-time applications like those encountered in signal processing and nonlinear system identification. We con ...

Technical University of Lodz2010

Kohonen Winner Takes All Neural Network Realized on Microcontrollers with AVR and ARM Cores

Rafal Tomasz Dlugosz

This paper presents realization and the laboratory tests of the Kohonen winner takes all (WTA) neural network (NN) realized on microcontrollers (μC) with the AVR and ARM CortexM3 cores. Both μCs have been placed on a single testing board especially designe ...

Technical University of Lodz2010

Network Simplification: the Gaussian N-Relay Diamond Network

Christina Fragouli, Ayfer Özgür Aydin

We consider the Gaussian

N

-relay diamond network, where a source wants to communicate to a destination through a layer of

N

-relay nodes. We investigate the following question: What fraction of the capacity can we maintain by using only

k

out of the $ ...

2010

Perceptual learning: why mice do not play backgammon

Elisa Tartaglia

Perceptual learning is the ability to modify perception through practice. As a form of brain plasticity, perceptual learning has been studied for more than thirty years in different fields including psychology, neurophysiology and computational neuroscienc ...

EPFL2009

Multiple task learning in recurrent neural networks using layered reservoirs

Martin Hasler, Ali Ajdari Rad, Mahdi Jalili

In this paper, to learn multiple tasks sharing same inputs, a two-layer architecture for a reservoir based recurrent neural network is proposed. The inputs are fed into the general workspace layer where the weights are adapted to provide maximum informatio ...

2009

Application of Artificial Neural Network to Predict Survival Time for Patients with Bladder Cancer

Rafal Tomasz Dlugosz

This paper presents an application of an artificial neural network to determine survival time of patients with a bladder cancer. Different learning methods have been investigated to find a solution, which is most optimal from a computational complexity poi ...

Springer-Verlag2009

Evolutionary Selection of Features for Neural Sleep/Wake Discrimination

Dario Floreano, Claudio Mattiussi, Walter Karlen, Peter Dürr, Jérémie Guignard

In biomedical signal analysis, artificial neural networks are often used for pattern classification because of their capability for nonlinear class separation and the possibility to efficiently implement them on a microcontroller. Typically, the network to ...

Hindawi Publishing Corporation2009

Networks of mixed canonical-dissipative systems and dynamic hebbian learning

Max-Olivier Hongler, Julio Rodriguez

We study the dynamics of a network consisting of N diffusively coupled, stable- limit-cycle oscillators on which individual frequencies are parametrized by

w_k, k = 1, . . . ,N

. We introduce a learning rule which influences the wk by driving the system t ...

2009

A New Fast Training Algorithm of the WTM Kohonen Neural Network Implemented for Classification of Biomedical Signals

Rafal Tomasz Dlugosz

A new optimized algorithm for the learning process suitable for hardware implemented Winner Takes Most Kohonen Neural Network (KNN) has been proposed in the paper. In networks of this type a neighborhood mechanism is used to improve the convergence propert ...

2009

Networks of limit cycle oscillators with parametric learning capability

Max-Olivier Hongler, Julio Rodriguez

The fundamental idea that synchronized patterns emerge in networks of interacting oscillators is revisited by allowing a parametric learning mechanism to operate on the local dynamics. The local dynamics consist of stable limit cycle oscillators which, due ...

Springer2009

Optimization of high order perceptrons

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Power Efficient Hardware Implementation of a Fuzzy Neural Network

Kohonen Winner Takes All Neural Network Realized on Microcontrollers with AVR and ARM Cores

Network Simplification: the Gaussian N-Relay Diamond Network

Perceptual learning: why mice do not play backgammon

Multiple task learning in recurrent neural networks using layered reservoirs

Application of Artificial Neural Network to Predict Survival Time for Patients with Bladder Cancer

Evolutionary Selection of Features for Neural Sleep/Wake Discrimination

Networks of mixed canonical-dissipative systems and dynamic hebbian learning

A New Fast Training Algorithm of the WTM Kohonen Neural Network Implemented for Classification of Biomedical Signals

Networks of limit cycle oscillators with parametric learning capability

Kohonen Winner Takes All Neural Network Realized on Microcontrollers with AVR and ARM Cores

Application of Artificial Neural Network to Predict Survival Time for Patients with Bladder Cancer

Power Efficient Hardware Implementation of a Fuzzy Neural Network

Multiple task learning in recurrent neural networks using layered reservoirs

Networks of mixed canonical-dissipative systems and dynamic hebbian learning

A New Fast Training Algorithm of the WTM Kohonen Neural Network Implemented for Classification of Biomedical Signals

Network Simplification: the Gaussian N-Relay Diamond Network

Perceptual learning: why mice do not play backgammon

Evolutionary Selection of Features for Neural Sleep/Wake Discrimination

Networks of limit cycle oscillators with parametric learning capability