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» Optimizing number of hidden neurons in neural networks
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NIPS
2004
13 years 9 months ago
Bayesian inference in spiking neurons
We propose a new interpretation of spiking neurons as Bayesian integrators accumulating evidence over time about events in the external world or the body, and communicating to oth...
Sophie Deneve
ICANN
2007
Springer
13 years 11 months ago
Text-Independent Speaker Authentication with Spiking Neural Networks
This paper presents a novel system that performs text-independent speaker authentication using new spiking neural network (SNN) architectures. Each speaker is represented by a set ...
Simei Gomes Wysoski, Lubica Benuskova, Nikola Kasa...
RAS
2002
168views more  RAS 2002»
13 years 7 months ago
Neural predictive control for a car-like mobile robot
: This paper presents a new path-tracking scheme for a car-like mobile robot based on neural predictive control. A multi-layer back-propagation neural network is employed to model ...
Dongbing Gu, Huosheng Hu
NPL
2000
135views more  NPL 2000»
13 years 7 months ago
Towards the Optimal Learning Rate for Backpropagation
A backpropagation learning algorithm for feedforward neural networks with an adaptive learning rate is derived. The algorithm is based upon minimising the instantaneous output erro...
Danilo P. Mandic, Jonathon A. Chambers
ICPR
2006
IEEE
14 years 9 months ago
Competitive Mixtures of Simple Neurons
We propose a competitive finite mixture of neurons (or perceptrons) for solving binary classification problems. Our classifier includes a prior for the weights between different n...
Karthik Sridharan, Matthew J. Beal, Venu Govindara...