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Results 1 - 10
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1,280
Batch Means and Spectral Variance Estimation in Markov Chain Monte Carlo
, 2009
"... Calculating a Monte Carlo standard error (MCSE) is an important step in the statistical analysis of the simulation output obtained from a Markov chain Monte Carlo experiment. An MCSE is usually based on an estimate of the variance of the asymptotic normal distribution. We consider spectral and batch ..."
Abstract
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Cited by 27 (9 self)
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Calculating a Monte Carlo standard error (MCSE) is an important step in the statistical analysis of the simulation output obtained from a Markov chain Monte Carlo experiment. An MCSE is usually based on an estimate of the variance of the asymptotic normal distribution. We consider spectral
Improved speech spectral variance estimation under the generalized Gamma distribution
- in IEEE BENELUX/DSP Valley Signal Process. Symp
, 2007
"... DFT-based single-microphone speech enhancement meth-ods need an estimate of the clean speech spectral variance. Often the ”decision-directed ” spectral variance estimator is used, because of its good performance: it strongly re-duces the musical noise phenomenon. It has recently been shown that this ..."
Abstract
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Cited by 1 (1 self)
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DFT-based single-microphone speech enhancement meth-ods need an estimate of the clean speech spectral variance. Often the ”decision-directed ” spectral variance estimator is used, because of its good performance: it strongly re-duces the musical noise phenomenon. It has recently been shown
Article Image Segmentation Based on Constrained Spectral Variance Difference and Edge Penalty
"... www.mdpi.com/journal/remotesensing ..."
RESEARCH ARTICLE Central Auditory Processing of Temporal and Spectral-Variance Cues in Cochlear Implant Listeners
"... Cochlear implant (CI) listeners have difficulty understanding speech in complex listening environments. This deficit is thought to be largely due to peripheral encoding problems aris-ing from current spread, which results in wide peripheral filters. In normal hearing (NH) lis-teners, central process ..."
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contri-butions to signal detection. Introduction of temporal asynchrony between the signal and masker improved signal detection in both peripheral and central masking conditions for all CI listeners. Randomly varying components of the masker created spectral-variance cues,
Characterization of Near-Infrared Spectral Variance in the Authentication of Skim and Nonfat Dry Milk Powder Collection Using
"... *S Supporting Information ABSTRACT: Forty-one samples of skim milk powder (SMP) and nonfat dry milk (NFDM) from 8 suppliers, 13 production sites, and 3 processing temperatures were analyzed by NIR diffuse reflectance spectrometry over a period of 3 days. NIR reflectance spectra (1700−2500 nm) were c ..."
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converted to pseudoabsorbance and examined using (a) analysis of variance-principal component analysis (ANOVA-PCA), (b) pooled-ANOVA based on data submatrices, and (c) partial least-squares regression (PLSR) coupled with pooled-ANOVA. ANOVA-PCA score plots showed clear separation of the samples with respect
Spectral
, 2003
"... We estimate output growth rate spectra for 58 countries. The spectra exhibit diverse shapes. To study the sources of this diversity, we estimate the short-run, business cycle, and long-run frequency components of the sampled series. For most OECD countries the bulk of the spectral mass is in the bus ..."
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We estimate output growth rate spectra for 58 countries. The spectra exhibit diverse shapes. To study the sources of this diversity, we estimate the short-run, business cycle, and long-run frequency components of the sampled series. For most OECD countries the bulk of the spectral mass
Spectral Subtraction with Variance Reduced Noise Spectrum Estimates
"... Spectral subtraction has the drawback that it introduces an unpleasant residual noise. This noise is a result of under-subtraction which occurs due to high variance of noise magnitude spectrum estimates. In this study we investigate a number of smoothing techniques that can be employed to reduce thi ..."
Abstract
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Cited by 2 (0 self)
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Spectral subtraction has the drawback that it introduces an unpleasant residual noise. This noise is a result of under-subtraction which occurs due to high variance of noise magnitude spectrum estimates. In this study we investigate a number of smoothing techniques that can be employed to reduce
Cosmic Variance of the Spectral Index from Mode Coupling
"... Abstract. We demonstrate that local, scale-dependent non-Gaussianity can generate cosmic variance uncertainty in the observed spectral index of primordial curvature perturbations. In a universe much larger than our current Hubble volume, locally unobservable long wavelength modes can induce a scale- ..."
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Abstract. We demonstrate that local, scale-dependent non-Gaussianity can generate cosmic variance uncertainty in the observed spectral index of primordial curvature perturbations. In a universe much larger than our current Hubble volume, locally unobservable long wavelength modes can induce a scale
Results 1 - 10
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