Minimal Itakura-Saito distance and covariance interpolation

Enqvist, Per; Karlsson, Johan

doi:10.1109/cdc.2008.4739312

Cited by 22 publications

(25 citation statements)

References 11 publications

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“…Besides signal processing, significant applications of this theory are found in modeling and identification [12], [24], [25], robust control [8], [11], and biomedical engineering [26]. The first, inevitable step in this procedure is to test for feasibility of the generalized moment problem.…”

Section: Three-type Spectral Estimationmentioning

confidence: 99%

“…Hence, it is equivalent to minimize the functional (23) over . The first variation at in direction is given by By annihilating the first variation for each , we get (24) It is then natural to restrict our attention to multiplier matrices satisfying the inequality (25) For such , we get that the form of the optimal solution is (26) where (27) It is quite interesting to notice that gives another characterization of as stated by the following proposition. Proposition 4.1: Let and be defined by (27).…”

Section: New Approach To Findingmentioning

confidence: 99%

“…Proof: Let be and consider (28) where we employed condition (7). Thus, the original Problem 1 is reduced to finding satisfying (25) and such that satisfies (7). This is accomplished in the next section via duality theory.…”

Section: New Approach To Findingmentioning

confidence: 99%

See 2 more Smart Citations

A Maximum Entropy Enhancement for a Family of High-Resolution Spectral Estimators

Ferrante

Pavon

Zorzi

2012

IEEE Trans. Automat. Contr.

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Abstract-Structured covariances occurring in spectral analysis, filtering and identification need to be estimated from a finite observation record. The corresponding sample covariance usually fails to possess the required structure. This is the case, for instance, in the Byrnes-Georgiou-Lindquist THREE-like tunable, high-resolution spectral estimators. There, the output covariance 6 of a linear filter is needed to initialize the spectral estimation technique. The sample covariance estimate6, however, is usually not compatible with the filter. In this paper, we present a new, systematic way to overcome this difficulty. The new estimate 6 is obtained by solving an ancillary problem with an entropic-type criterion. Extensive scalar and multivariate simulation shows that this new approach consistently leads to a significant improvement of the spectral estimators performances.

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Section: Three-type Spectral Estimationmentioning

confidence: 99%

Section: New Approach To Findingmentioning

confidence: 99%

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A Maximum Entropy Enhancement for a Family of High-Resolution Spectral Estimators

Ferrante

Pavon

Zorzi

2012

IEEE Trans. Automat. Contr.

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“…Chart 2: CEP distance for coders 7.2 Itakura Saito Distance IS [18] evaluates the perceptual distance between original spectrum and an approximation of that spectrum. The estimation is based on divergence between power spectra of original and reconstructed speech.…”

Section: Perceptual Measurement 61pesqmentioning

confidence: 99%

Comparative Analysis of Speech Compression Algorithms with Perceptual and LP based Quality Evaluations

Saleem¹,

Nasir²,

Ali³

2012

IJCA

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Speech compression is one of the leading vicinity of digital signal processing that spotlight on dipping the bit rate of speech signals for transmission and storage devoid of considerable loss of quality. In past decades many speech coding techniques have been proposed for speech analysis. This paper attempts to assess and compare two compression techniques on speech signals. To execute this idea we have chosen two low bit rate and widely used speech analysis methods called VELP and MELP. The performances of both are evaluated by performing objective quality tests including PESQ, IS and CEP. Similar speech files are tested with both coders. The objective assessments show that at low bit rate the MELP shows better performance as compared to VELP.

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“…These problems pose a number of theoretical and computational challenges, especially in the multivariable framework, for which we also refer the reader to [15][16][17][18][19][20][21][22]. Besides signal processing, significant applications of this theory are found in modeling and identification [23][24][25], H ∞ robust control [26,27], and biomedical engineering [28].…”

Section: Introductionmentioning

confidence: 99%