IWANN '01 Proceedings of the 6th International Work-Conference on Artificial and Natural Neural Networks: Connectionist Models of Neurons, Learning Processes and Artificial Intelligence-Part I
Evolving RBF neural networks for time-series forecasting with EvRBF
Information Sciences—Informatics and Computer Science: An International Journal - Special issue: Informatics and computer science intelligent systems applications
A learning rule to model the development of orientation selectivity in visual cortex
IWANN'03 Proceedings of the Artificial and natural neural networks 7th international conference on Computational methods in neural modeling - Volume 1
Global models for patient-ventilator interactions in noninvasive ventilation with asynchronies
Computers in Biology and Medicine
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In the context of regression analysis with penalised linear models (such as RBF networks) certain model selection criteria can be differentiated to yield a re-estimation formula for the regularisation parameter such that an initial guess can be iteratively improved until a local minimum of the criterion is reached. In this paper we discuss some enhancements of this general approach including improved computational efficiency, detection of the global minimum and simultaneous optimisation of the basis function widths. The benefits of these improvements are demonstrated on a practical problem.