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Catalog : EECE.6870 Applied Stochastic Estimation (Formerly 16.687)

EECE.6870 — Graduate

Id: 003368 Offering: 1 Credits: 3-3

Description

Review of random processes and key elements of probability theory. State space description of systems and random processes, relation to frequency domain techniques. Numerical methods of continuous and discrete time random system modeling. Optimal Kalman filtering for discrete and continuous random systems. Sensitivity analysis. Design considerations in the face of model uncertainty, numerical instabilities, bad data. Optimal smoothing. Nonlinear filtering. Parameter identification. Applications throughout.

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EECE.6870 — Online and Continuing Education

Id: 003368 Offering: 2 Credits: 3-3

Description

Review of random processes and key elements of probability theory. State space description of systems and random processes, relation to frequency domain techniques. Numerical methods of continuous and discrete time random system modeling. Optimal Kalman filtering for discrete and continuous random systems. Sensitivity analysis. Design considerations in the face of model uncertainty, numerical instabilities, bad data. Optimal smoothing. Nonlinear filtering. Parameter identification. Applications throughout.

Prerequisites

Students with a CSCE or UGRD career need permission to take Graduate Level Courses.

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