Adaptive spectrum estimation in one and two dimensions

Vallverdú, Francesc; Lagunas, M.A.

doi:10.1109/spect.1988.206231

Cited by 1 publication

(2 citation statements)

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“…Hence, whenf(S) = 0 for all S, S(w) may show any shape consistent with the constraints. Moreover, when f(S) has a constant non-zero value K 3 , we can choose x 1 such that (15) resulting in F(1 +AS)= F(l-AS), for AS :s;; 1.…”

Section: Analytical Comparison Of Methodsmentioning

confidence: 99%

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A flatness-based generalized optimization approach to spectral estimation

Nadeu

Bertran

1990

Signal Processing

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Abstract. In the optimization formulation, once the known autocorrelations are fixed as constraints, the objective functional completely characterizes the corresponding method of spectral estimation. After observing that this functional involves a sort of spectral flatness maximization, the relationship between the form of its integrand and the salient trends of the various methods is pointed out. This serves as a basis to propose a generalized optimization approach that encompasses some classical estimators and originates new ones.Zusammenfassung. In der Optimierungs-Beschreibung charakterisiert das Funktional die jeweilige Methode zur Spektralschalzung vollstandig, wenn von festen Autokorrelationswerten ausgegangen wird. Nach dem Aufzeigen der Tatsache, daB dieses Funktional eine Art von Maximierung der Flachheit des Spektrums beinhaltet, wird die Beziehung zwischen der Form des Integranden und den herausragenden Richtungen der verschiedenen Methdden herausgestellt. Auf dieser Grundlage wird ein verallgemeinerter Optimierungs-Ansatz vorgeschlagen, der einige klassische Schatzer einschlieBt und neue hervorbringt. SchlieBlich wird die Brauchbarkeit der Vorstellung der spektralen Flachheit fiir die Spektralschatzung diskutiert.Resume. Dans un contexte d'optimisation,la fonction objectif caracterise completement la methode correspondante d'estimation spectrale des que les valeurs d'autocorrelation connues sent fixees comme contraintes. Observant que cette fonction objectif implique une certaine maximisation du caractere plat du spectre (en anglais spectral flatness), la relation entre la forme de !'integration et les traits saillants de differentes methodes est mise en evidence. Ceci sert de base a une approche generalisee de l'optimisation qui recouvre certains estimateurs classiques et permet d'en creer de nouveaux.

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Section: Analytical Comparison Of Methodsmentioning

confidence: 99%

“…Unfortunately, the algorithm does not exhibit a convergence as good as the Newton-Raphson's one. However, other algorithms which are more specific and show a better convergence performance have recently been developed [15]. …”

Section: !(E(s S 0 )+E(s 0 S))mentioning

confidence: 99%

A flatness-based generalized optimization approach to spectral estimation

Nadeu

Bertran

1990

Signal Processing

View full text Add to dashboard Cite

show abstract

Adaptive spectrum estimation in one and two dimensions

Cited by 1 publication

References 9 publications

A flatness-based generalized optimization approach to spectral estimation

A flatness-based generalized optimization approach to spectral estimation

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