Application of alternating convex projection methods for computation of positive Toeplitz matrices

Application of alternating convex projection methods for computation of positive Toeplitz matrices

Uses alternating convex projection techniques to compute the closest positive definite Toeplitz matrix that satisfies certain inequality constraints to a specified symmetric matrix. Some applications to signal processing and control problems are discussed.< >

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Veröffentlicht in:IEEE transactions on signal processing 1994-07, Vol.42 (7), p.1873-1875
Hauptverfasser: Grigoriadis, K.M., Frazho, A.E., Skelton, R.E.
Format: Artikel
Sprache:eng
Schlagworte:
Applied sciences
Autocorrelation
Constraint optimization
Control design
Control theory
Covariance matrix
Digital signal processing
Exact sciences and technology
Information, signal and communications theory
Linear matrix inequalities
Mathematical methods
Process control
Signal processing
Symmetric matrices
Telecommunications and information theory
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Zusammenfassung:Uses alternating convex projection techniques to compute the closest positive definite Toeplitz matrix that satisfies certain inequality constraints to a specified symmetric matrix. Some applications to signal processing and control problems are discussed.< >
ISSN:1053-587X
1941-0476
DOI:10.1109/78.298303