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SIAMCO
2000
117views more  SIAMCO 2000»
14 years 11 months ago
The O.D.E. Method for Convergence of Stochastic Approximation and Reinforcement Learning
It is shown here that stability of the stochastic approximation algorithm is implied by the asymptotic stability of the origin for an associated ODE. This in turn implies convergen...
Vivek S. Borkar, Sean P. Meyn
ISNN
2010
Springer
14 years 10 months ago
Particle Swarm Optimization Based Learning Method for Process Neural Networks
Abstract. This paper proposes a new learning method for process neural networks (PNNs) based on the Gaussian mixture functions and particle swarm optimization (PSO), called PSO-LM....
Kun Liu, Ying Tan, Xingui He
NECO
2002
104views more  NECO 2002»
14 years 11 months ago
An Unsupervised Ensemble Learning Method for Nonlinear Dynamic State-Space Models
A Bayesian ensemble learning method is introduced for unsupervised extraction of dynamic processes from noisy data. The data are assumed to be generated by an unknown nonlinear ma...
Harri Valpola, Juha Karhunen
ICIP
2010
IEEE
14 years 9 months ago
A new subspace learning method in Fourier domain for texture classification
This paper proposes a new texture classification approach. There are two main contributions in the proposed method. First, input texture images are transformed to the composite Fo...
Shu Liao, Albert C. S. Chung
TSMC
2002
144views more  TSMC 2002»
14 years 11 months ago
COR: a methodology to improve ad hoc data-driven linguistic rule learning methods by inducing cooperation among rules
This paper introduces a new learning methodology to quickly generate accurate and simple linguistic fuzzy models, the cooperative rules (COR) methodology. It acts on the consequent...
Jorge Casillas, Oscar Cordón, Francisco Her...