Approximation properties of positive Boolean functions

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3931 LNCS, Issue , 2006, Pages 18-22

  Muselli, Marco ^a  

^a CNR   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION (OF INFORMATION); DIGITAL CIRCUITS; FUNCTION EVALUATION; LEARNING SYSTEMS; LOGIC GATES; PROBLEM SOLVING; REGRESSION ANALYSIS;

APPROXIMATION PROPERTIES; DESIRED PRECISION; NOMINAL VARIABLES; UNIVERSAL APPROXIMATORS;

BOOLEAN FUNCTIONS;

EID: 33745791535     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11731177_3     Document Type: Conference Paper

References (7)

1. Hornik, K., Stinchcombe, M., White, H.: Multilayer feedforward networks are universal approximators. Neural Networks 2 (1989) 359-366
2. Park, J., Sandberg, I.W.: Universal approximation using radial-basis-function networks. Neural Computation 3 (1991) 246-257
3. Hammer, B., Gersmann, K.: A note on the universal approximation capability of support vector machines. Neural Processing Letters 17 (2003) 43-53
4. Boros, E., Hammer, P.L., Ibaraki, T., Kogan, A., Mayoraz, E., Muchnik, I.: An implementation of Logical Analysis of Data. IEEE Transactions on Knowledge and Data Engineering 12 (2000) 292-306
5. Muselli, M., Liberati, D.: Binary rule generation via Hamming Clustering. IEEE Transactions on Knowledge and Data Engineering 14 (2002) 1258-1268
6. M. Muselli: Switching Neural Networks: A New Connectionist Model for Classification. In WIRN/NAIS 2005, vol. 3931 of Lecture Notes in Computer Science (2006) Eds. B. Apolloni et al., Berlin: Springer-Verlag, 23-30.
7. Muselli, M., A. Quarati: Reconstructing positive Boolean functions with Shadow Clustering. In Proceedings of the 17th European Conference on Circuit Theory and Design (ECCTD 2005), (Cork, Ireland, August 2005).