130
click to vote
IJCNN
2006
IEEE
15 years 11 months ago
2006
IEEE
— The tristability that a class of two-dimensional neuron models may exhibit is investigated in this paper. One proposition and three corollaries on saddles, which play an import...
91
Voted
IJCNN
2006
IEEE
15 years 11 months ago
2006
IEEE
143
Voted
IJCNN
2006
IEEE
15 years 11 months ago
2006
IEEE
Abstract— Dynamic neural networks with different timescales include the aspects of fast and slow phenomenons. Some applications require that the equilibrium points of these netwo...
159
Voted
IJCNN
2006
IEEE
15 years 11 months ago
2006
IEEE
— From the Bayesian Ying-Yang (BYY) harmony learning theory, a harmony function has been developed for finite mixtures with a novel property that its maximization can make model...
109
Voted
IJCNN
2006
IEEE
15 years 11 months ago
2006
IEEE
— We analyze the generalization performance of a student in a model composed of linear perceptrons: a true teacher, ensemble teachers, and the student. Calculating the generaliza...
134
Voted
IJCNN
2006
IEEE
15 years 11 months ago
2006
IEEE
— We propose a new annealing method for the hyperparameters of several recent Learning Vector Quantization algorithms. We first analyze the relationship between values assigned ...
122
Voted
IJCNN
2006
IEEE
15 years 11 months ago
2006
IEEE
— We consider the application of kernel canonical correlation analysis (K-CCA) to the supervised equalization of Wiener systems. Although a considerable amount of research has be...
127
Voted
IJCNN
2006
IEEE
15 years 11 months ago
2006
IEEE
— Over time, neural networks have proven to be extremely powerful tools for data exploration with the capability to discover previously unknown dependencies and relationships in ...
137
click to vote
IJCNN
2006
IEEE
15 years 11 months ago
2006
IEEE
Abstract— This paper considers the basis vector selection issue invloved in forward selection algorithms to sparse Gaussian Process Regression (GPR). Firstly, we re-examine a pre...
134
Voted
IJCNN
2006
IEEE
15 years 11 months ago
2006
IEEE
— In this paper a Particle Swarm Optimization (PSO)-based training strategy is introduced for fuzzy ARTMAP that minimizes generalization error while optimizing parameter values. ...