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...
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....
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...
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...
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...