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A convex optimization approach to jump nonlinear systems

Capponi, Agostino (2008) A convex optimization approach to jump nonlinear systems. Computer Science Technical Reports, 2005.004. California Institute of Technology . (Submitted)

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We introduce a new methodology to approximate the lter density in hybrid Markovian switching systems. We relax the assumption that the mode transition process is a Markov chain and allow it to depend on the actual and unobservable state of the target. The approximation density is obtained as an expansion of gaussian densities. Such densities are selected as the solution of a convex programming problem which trades off sparsity of the solution with goodness of fit. We provide an analytical bound on the total variation distance between our approximation density and the actual filter density. A meaningful example shows that the proposed method can outperform the widely used interacting multiple model (IMM) in terms of accuracy.

Item Type:Report or Paper (Technical Report)
Group:Computer Science Technical Reports
Series Name:Computer Science Technical Reports
Issue or Number:2005.004
Record Number:CaltechCSTR:2005.004
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Usage Policy:You are granted permission for individual, educational, research and non-commercial reproduction, distribution, display and performance of this work in any format
ID Code:26649
Deposited By: Imported from CaltechCSTR
Deposited On:20 Jan 2023 00:24
Last Modified:20 Jan 2023 00:24

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