Learning algorithm for nonlinear support vector machines suited for digital VLSI

Electronics Letters

Volumn 35, Issue 16, 1999, Pages 1349-1350

  Anguita, D ^a   Boni, A ^a   Ridella, S ^a  

^a UNIVERSITY OF GENOA   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

CONVERGENCE OF NUMERICAL METHODS; DATA STRUCTURES; LEARNING SYSTEMS; MATRIX ALGEBRA; NEURAL NETWORKS; OPTIMIZATION; QUADRATIC PROGRAMMING; SHIFT REGISTERS; VECTORS; VLSI CIRCUITS;

DATA SETS; DIGITAL VLSI; FINITE REGISTER LENGTH; QUANTISATION EFFECTS; RADIAL BASIS FUNCTION SUPPORT VECTOR;

LEARNING ALGORITHMS;

EID: 0032669291     PISSN: 00135194     EISSN: None     Source Type: Journal    
DOI: 10.1049/el:19990950     Document Type: Article

References (6)

1. VAPNIK, V.N.: 'Statistical learning theory' (Springer-Verlag, 1999)
2. IIEARST, M.A.: 'Support vector machines', IEEE Intell. Syst., 1998, 13, (4), pp. 18-28
3. ANGUITA, D., RIDELLA, s., and ROVETTA, s.: 'Circuital implementation of support vector machines', Electron. Lett., 1998, 34, (16), pp. 1596-1597
4. FRIESS, T.T., CRiSTiANiNi, N., and CAMPBELL, c: 'The Kernel Adatron algorithm: a fast and simple learning procedure for support vector machines', in SHAVLIK, j.: Proc. 15th Int. Conf. Machine Learning, 1998 (Morgan Kaufmann Pub.)
5. PEREZ-ILZARBE, M.J.: 'Convergence analysis of a discrete-time recurrent neural network to perform quadratic real optimisation with bound constraints', IEEE Trans. Neural Net:, 1998, 9, (6), pp. 1344-1351
6. TORRES-MORENO, J.M., and GORDON, M.B.: 'Characterisation of the sonar signals benchmark', Neural Process. Lett., 1998, 7, pp. 1-4