Function approximation in the framework of evidence theory: A connectionist approach

IEEE International Conference on Neural Networks - Conference Proceedings

Volumn 1, Issue , 1997, Pages 199-203

  Denoeux, Thierry ^a  

^a UNIVERSITÉ DE TECHNOLOGIE DE COMPIÈGNE   (France)

Author keywords

[No Author keywords available]

Indexed keywords

BELIEF STRUCTURES; CONNECTIONIST APPROACH; DEMPSTER-SHAFER THEORY OF EVIDENCE; EVIDENCE THEORIES; FUNCTION APPROXIMATION; FUNCTIONAL REGRESSION; REFERENCE VECTORS; TRANSFERABLE BELIEF MODEL;

ARTIFICIAL INTELLIGENCE; COGNITIVE SYSTEMS; APPROXIMATION THEORY; MATHEMATICAL MODELS; VECTORS;

NEURAL NETWORKS;

DEMPSTER SHAFER THEORY; TRANSFERABLE BELIEF MODEL;

EID: 0030658518     PISSN: 10987576     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICNN.1997.611664     Document Type: Conference Paper

References (7)

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3. T. Denoeux. A fc-nearest neighbor classification rule based on Dempster-Shafer theory. IEEE Transactions on Systems, Man and Cybernetics, 25(05):804-813, 1995.
4. T. Denoeux. Analysis of evidence-theoretic decision rules for pattern classification. Pattern Recognition (In press), 1997.
5. J. A. Leonard, M. A. Kramer, and L. H. Ungar. Using radial basis functions to approximate a function and its error bounds. IEEE Transactions on Neural. Networks, 3(6):624-627,1992.
6. G. Shafer. A mathematical theory of evidence. Princeton University Press, Princeton, N. J., 1976.
7. P. Smets and R. Kennes. The Transferable Belief Model. Artificial Intelligence, 66:191-243,1994.