BONI A.

A learning algorithm for radial basis function support vector machines (RBF-SVM) that can be easily implemented in digital VLSI is proposed. It is shown that, as opposed to traditional artificial neural networks, learning in SVMs is very robust with respect to quantization effects deriving from the precision of computations