FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W1932593313> ?p ?o ?g. }

• W1932593313 abstract "The thesis is composed of two parts. In the first part, we deal with the monaural speech separation problem. We propose two algorithms. In the first algorithm, we exploit the joint autoregressive model that models short and long (periodic) correlations of Gaussian speech signals to formulate a state space model with unknown parameters. The EM-Kalman algorithm is then used to estimate jointly the sources (involved in the state vector) and the parameters of the model. In the second algorithm, we use the same speech model but this time in the frequency domain (quasi-periodic Gaussian sources with AR spectral envelope). Observation data is sliced using a well-designed window. Parameters are estimated separately from the sources by optimizing the Gaussian ML criterion expressed using the sample and parameterized covariance matrices. Classical frequency domain asymptotic methods replace linear convolution by circulant convolution leading to approximation errors. We show how the introduction of windows can lead to slightly more complex frequency domain techniques, replacing diagonal covariance matrices by banded covariance matrices, but with controlled approximation error. The sources are then estimated using the Wiener filtering. The second part is about the relative performance of joint vs. marginalized parameter estimation. We consider jointly Gaussian latent data and observations. We provide contributions to Cramer-Rao bounds, then, we investigate three iterative joint estimation approaches: Alternating MAP/ML which suffers from inconsistent parameter bias, EM which converges to ML and VB that we prove converges asymptotically to the ML solution for parameter estimation." @default.
• W1932593313 created "2016-06-24" @default.
• W1932593313 creator A5017099088 @default.
• W1932593313 date "2014-06-06" @default.
• W1932593313 modified "2023-09-28" @default.
• W1932593313 title "Some contributions to joint optimal filtering and parameter estimation with application to monaural speech separation" @default.
• W1932593313 cites W120328284 @default.
• W1932593313 cites W121759451 @default.
• W1932593313 cites W1479979375 @default.
• W1932593313 cites W1496562625 @default.
• W1932593313 cites W1506726567 @default.
• W1932593313 cites W1514558801 @default.
• W1932593313 cites W1514836139 @default.
• W1932593313 cites W1532956126 @default.
• W1932593313 cites W1536252645 @default.
• W1932593313 cites W1540723801 @default.
• W1932593313 cites W1552314771 @default.
• W1932593313 cites W1575829986 @default.
• W1932593313 cites W1603631609 @default.
• W1932593313 cites W160800111 @default.
• W1932593313 cites W165783309 @default.
• W1932593313 cites W1676523307 @default.
• W1932593313 cites W1713818855 @default.
• W1932593313 cites W1755563775 @default.
• W1932593313 cites W1831233010 @default.
• W1932593313 cites W1885397938 @default.
• W1932593313 cites W1904706240 @default.
• W1932593313 cites W1937661627 @default.
• W1932593313 cites W1943178216 @default.
• W1932593313 cites W1944891170 @default.
• W1932593313 cites W1963718895 @default.
• W1932593313 cites W1963835294 @default.
• W1932593313 cites W1965324089 @default.
• W1932593313 cites W1965392255 @default.
• W1932593313 cites W1970433496 @default.
• W1932593313 cites W1974086818 @default.
• W1932593313 cites W1981364618 @default.
• W1932593313 cites W1990768232 @default.
• W1932593313 cites W1991934991 @default.
• W1932593313 cites W1996719383 @default.
• W1932593313 cites W1999439604 @default.
• W1932593313 cites W2000721204 @default.
• W1932593313 cites W2014952101 @default.
• W1932593313 cites W2015143272 @default.
• W1932593313 cites W2016789247 @default.
• W1932593313 cites W2019625237 @default.
• W1932593313 cites W2019945856 @default.
• W1932593313 cites W2027780595 @default.
• W1932593313 cites W2034767804 @default.
• W1932593313 cites W2040832208 @default.
• W1932593313 cites W2048726107 @default.
• W1932593313 cites W2051914727 @default.
• W1932593313 cites W2057077708 @default.
• W1932593313 cites W2057220308 @default.
• W1932593313 cites W2058187269 @default.
• W1932593313 cites W2058269967 @default.
• W1932593313 cites W2058676219 @default.
• W1932593313 cites W2059119686 @default.
• W1932593313 cites W2060822897 @default.
• W1932593313 cites W2071914178 @default.
• W1932593313 cites W2072184010 @default.
• W1932593313 cites W2072817066 @default.
• W1932593313 cites W2073797987 @default.
• W1932593313 cites W2083592286 @default.
• W1932593313 cites W2084044763 @default.
• W1932593313 cites W2086062758 @default.
• W1932593313 cites W2087435860 @default.
• W1932593313 cites W2090064169 @default.
• W1932593313 cites W2094227853 @default.
• W1932593313 cites W2096055753 @default.
• W1932593313 cites W2096529484 @default.
• W1932593313 cites W2097645910 @default.
• W1932593313 cites W2098084154 @default.
• W1932593313 cites W2098571827 @default.
• W1932593313 cites W2099904336 @default.
• W1932593313 cites W2100841352 @default.
• W1932593313 cites W2101051269 @default.
• W1932593313 cites W2101404574 @default.
• W1932593313 cites W2102249043 @default.
• W1932593313 cites W2102334473 @default.
• W1932593313 cites W2102780911 @default.
• W1932593313 cites W210359992 @default.
• W1932593313 cites W2104130465 @default.
• W1932593313 cites W2104298926 @default.
• W1932593313 cites W2104352833 @default.
• W1932593313 cites W2105681560 @default.
• W1932593313 cites W2105934661 @default.
• W1932593313 cites W2106582496 @default.
• W1932593313 cites W2106934198 @default.
• W1932593313 cites W2107189492 @default.
• W1932593313 cites W2108667507 @default.
• W1932593313 cites W2109059146 @default.
• W1932593313 cites W2109349638 @default.
• W1932593313 cites W2111070087 @default.
• W1932593313 cites W2111540686 @default.
• W1932593313 cites W2113131123 @default.
• W1932593313 cites W2113827176 @default.
• W1932593313 cites W2114694381 @default.
• W1932593313 cites W2114757154 @default.
• W1932593313 cites W2115979064 @default.

• next