Recursive prediction of stochastic nonlinear systems based on optimal Dirac mixture approximations

Proceedings of the American Control Conference

Volumn , Issue , 2007, Pages 1768-1774

  Schrempf, Oliver C ^a   Hanebeck, Uwe D ^a  

^a UNIVERSITY OF KARLSRUHE   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

DYNAMIC PROGRAMMING; DYNAMICAL SYSTEMS; FORECASTING; NONLINEAR SYSTEMS; RECURSIVE FUNCTIONS; RISK ASSESSMENT; SCHRODINGER EQUATION; SOUND REPRODUCTION; STOCHASTIC PROGRAMMING;

DISCRETE TIME (DT); DISTANCE MEASURES; EVOLUTION (CO); INDIVIDUAL COMPONENTS; NEW APPROACHES; NON-LINEAR DYNAMIC SYSTEMS; OPTIMAL APPROXIMATION; PROBABILITY DENSITIES; RECURSIVE PREDICTION; RECURSIVE PROCEDURES; STOCHASTIC NONLINEAR SYSTEMS;

PROBABILITY DENSITY FUNCTION;

EID: 35348864141     PISSN: 07431619     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ACC.2007.4282938     Document Type: Conference Paper

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