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ICASSP
2008
IEEE
13 years 11 months ago
Contextually adaptive signal representation using conditional principal component analysis
The conventional method of generating a basis that is optimally adapted (in MSE) for representation of an ensemble of signals is Principal Component Analysis (PCA). A more ambitio...
Rosa M. Figueras i Ventura, Umesh Rajashekar, Zhou...
GLOBECOM
2009
IEEE
13 years 11 months ago
Data Acquisition through Joint Compressive Sensing and Principal Component Analysis
—In this paper we look at the problem of accurately reconstructing distributed signals through the collection of a small number of samples at a data gathering point. The techniqu...
Riccardo Masiero, Giorgio Quer, Daniele Munaretto,...
ICASSP
2010
IEEE
13 years 5 months ago
Visual emotion recognition using compact facial representations and viseme information
Emotion expression is an essential part of human interaction. Rich emotional information is conveyed through the human face. In this study, we analyze detailed motion-captured fac...
Angeliki Metallinou, Carlos Busso, Sungbok Lee, Sh...
ICASSP
2009
IEEE
13 years 11 months ago
Independent component analysis for noisy speech recognition
Independent component analysis (ICA) is not only popular for blind source separation but also for unsupervised learning when the observations can be decomposed into some independe...
Hsin-Lung Hsieh, Jen-Tzung Chien, Koichi Shinoda, ...
ICA
2010
Springer
13 years 5 months ago
Adaptive Segmentation and Separation of Determined Convolutive Mixtures under Dynamic Conditions
Abstract. In this paper, we propose a method for blind source separation (BSS) of convolutive audio recordings with short blocks of stationary sources, i.e. dynamically changing so...
Benedikt Loesch, Bin Yang