A survey of spectral factorization methods

By Ali H. Sayed, Thomas Kailath. Numerical Linear Algebra with Applications, 2001

308 citations recorded by the source corpus.

Subfields: Control and Systems Engineering, Numerical Analysis

View Paper: https://www.semanticscholar.org/paper/f76856d6d658d10529fc4af961bac574859ea0ea

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In Control and Systems Engineering

1. Robert C. Williamson
2. Mark D. Reid
3. Govindan Rangarajan
4. M. Dhamala
5. Mingzhou Ding

In Numerical Analysis

1. Robert C. Williamson
2. Sundeep Rangan
3. Mark D. Reid
4. Govindan Rangarajan
5. M. Dhamala
6. Mingzhou Ding

Citations in the corpus

• Analyzing information flow in brain networks with nonparametric Granger causality (2008, methodology): “Spectral matrix factorization is a procedure for constructing a sequence of unique generating functions (or minimum-phase spectral factors) out of spectral density matrices (Sayed and Kaylath, 2001).”
• Identifying the New Keynesian Phillips Curve (2008, background): “For discussion and examples, see Hansen and Sargent (1981) and Sayed and Kailath (2001).”
• Information, Divergence and Risk for Binary Experiments (2009, background): “This is analogous to the question of spectral factorisation (Sayed and Kailath, 2001) for ordinary linear convolution.”
• Compressive phase retrieval via generalized approximate message passing (2012, background): “Closely connected to the problem of phase retrieval is the problem of spectral factorization [6].”