Itakura–Saito distance

Known as: Itakura Saito Distance, Itakura-Saito Distance 
The Itakura–Saito distance (or Itakura–Saito divergence) is a measure of the difference between an original spectrum and an approximation of that… (More)
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Topic mentions per year

Topic mentions per year

2002-2016
024620022016

Papers overview

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2016
2016
Coresets are e cient representations of data sets such that models trained on the coreset are provably competitive with models… (More)
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2014
2014
It is known that a footstep is useful tool to estimate a human state. Various surveillance systems using footstep are proposed… (More)
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2012
2012
It has recently been shown that a multi-channel linear prediction can effectively achieve blind speech dereverberation based on… (More)
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2011
2011
We present a live drum separation system for a specific target drumset to be used as a front end in a complete live drum… (More)
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Highly Cited
2011
Highly Cited
2011
Gaussian process (GP) models are very popular for machine learning and regression and they are widely used to account for spatial… (More)
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2010
2010
Blind audio source separation (BASS) arises in a number of applications in speech and music processing such as speech enhancement… (More)
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Review
2010
Review
2010
In Euclidean spaces, the geometric notions of nearest-points map, farthestpoints map, Chebyshev set, Klee set, and Chebyshev… (More)
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2008
2008
Identification of power spectral densities rely on measured second order statistics such as, e.g. covariance estimates. In the… (More)
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2008
2008
In this paper, we proposed a new speech enhancement system, which integrates a perceptual filterbank and minimum mean square… (More)
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Highly Cited
2004
Highly Cited
2004
A wide variety of distortion functions, such as squared Euclidean distance, Mahalanobis distance, Itakura-Saito distance and… (More)
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