Fusion methods for multiple sensor systems with unknown error densities

DOI10.1016/0016-0032(94)90035-3zbMath0832.93057OpenAlexW2030707380WikidataQ116677362 ScholiaQ116677362MaRDI QIDQ1898158

Nageswara S. V. Rao

Publication date: 5 March 1996

Published in: Journal of the Franklin Institute (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0016-0032(94)90035-3

zbMATH Keywords

fusion rulesestimation and detectionmultiple sensor data fusion

Mathematics Subject Classification ID

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Some special Vapnik-Chervonenkis classes
• Estimation of dependences based on empirical data. Transl. from the Russian by Samuel Kotz
• Multilayer feedforward networks are universal approximators
• Probably Approximate Learning of Sets and Functions
• On the complexity of decentralized decision making and detection problems
• Learnability and the Vapnik-Chervonenkis dimension
• A theory of the learnable
• Recursive hybrid algorithm for non-linear system identification using radial basis function networks
• Universal approximation bounds for superpositions of a sigmoidal function
• NAND-AND Circuits
• Majority and location based fusers for systems of PAC concept learners
• Team Decision Problems
• Approximation by superpositions of a sigmoidal function

This page was built for publication: Fusion methods for multiple sensor systems with unknown error densities