R. I. Damper, S. R. Gunn, and M. O. Gore. Extracting phonetic knowledge from learning systems: Perceptrons, support vector machines and linear discriminants. Applied Intelligence, 12:43-62, 2000. Home/Search Document Details and Download
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Using Costs Varying from Object to Object to Construct.. - Geibel, Wysotzki (2002) (Correct)
....the equality holds are called the support vectors. Support vector machines (SVMs, see [24, 2] are known to produce good results with respect to the expected error. A comparison of perceptrons and support vector machines with respect to their ability to learn phonetic knowledge can be found in [5]. The SVM approach can be extended to non linear decision functions and multi modal distributions by introducing so called kernel functions that correspond to transforming the original feature space to a higher dimensional space where the classes are linearly separable, even if the original ....
R. I. Damper, S. R. Gunn, and M. O. Gore. Extracting phonetic knowledge from learning systems: Perceptrons, support vector machines and linear discriminants. Applied Intelligence, 12:43-62, 2000.
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