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Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.13/916281
- Maximum likelihood estimation of state space models from frequency domain data
- The University of Newcastle. Faculty of Engineering & Built Environment, School of Electrical Engineering and Computer Science
- This paper addresses the problem of estimating linear time invariant models from observed frequency domain data. Here an emphasis is placed on deriving numerically robust and efficient methods that can reliably deal with high order models over wide bandwidths. This involves a novel application of the expectation-maximization algorithm in order to find maximum likelihood estimates of state space structures. An empirical study using both simulated and real measurement data is presented to illustrate the efficacy of the solutions derived here.
- IEEE Transactions on Automatic Control Vol. 54, Issue 1, p. 19-33
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- Institute of Electrical and Electronics Engineers (IEEE)
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- journal article
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