A computationally efficient subband noise estimation algorithm for speech enhancement

2006 ◽  
Author(s):  
Xia Zou ◽  
Hanwu Zhao ◽  
Tieyong Cao ◽  
Xiongwei Zhang
Keyword(s):  
Speech Enhancement ◽  
Estimation Algorithm ◽  
Noise Estimation ◽  
Computationally Efficient

Adaptive noise estimation algorithm for speech enhancement

2003 ◽  
Vol 39 (9) ◽  
pp. 754 ◽  
Author(s):  
L. Lin ◽  
W.H. Holmes ◽  
E. Ambikairajah
Keyword(s):  
Speech Enhancement ◽  
Estimation Algorithm ◽  
Noise Estimation ◽  
Adaptive Noise

scholarly journals Conditional Analysis for Mixed Covariates, with Application to Feed Intake of Lactating Sows

2019 ◽  
Vol 2019 ◽  
pp. 1-14
Author(s):  
S. Y. Park ◽  
C. Li ◽  
S. M. Mendoza Benavides ◽  
E. van Heugten ◽  
A. M. Staicu
Keyword(s):  
Feed Intake ◽  
Dynamic Change ◽  
Estimation Algorithm ◽  
Joint Estimation ◽  
Efficient Estimation ◽  
Specific Information ◽  
Computationally Efficient ◽  
Modeling Framework ◽  
Lactating Sows ◽  
Information Vector

We propose a novel modeling framework to study the effect of covariates of various types on the conditional distribution of the response. The methodology accommodates flexible model structure, allows for joint estimation of the quantiles at all levels, and provides a computationally efficient estimation algorithm. Extensive numerical investigation confirms good performance of the proposed method. The methodology is motivated by and applied to a lactating sow study, where the primary interest is to understand how the dynamic change of minute-by-minute temperature in the farrowing rooms within a day (functional covariate) is associated with low quantiles of feed intake of lactating sows, while accounting for other sow-specific information (vector covariate).

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