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129
Voted
ICASSP
2010
IEEE
15 years 2 months ago
Training a support vector machine to classify signals in a real environment given clean training data
When building a classifier from clean training data for a particular test environment, knowledge about the environmental noise and channel should be taken into account. We propos...
Kevin Jamieson, Maya R. Gupta, Eric Swanson, Hyrum...
105
Voted
ICASSP
2011
IEEE
14 years 6 months ago
Angular regularization of vector-valued signals
—A new class of pair-wise regularizers is proposed for vector-valued signals, including several new regularizers that penalize the angular difference between neighboring vectors....
Kevin M. Holt
125
Voted
ICIP
2002
IEEE
16 years 4 months ago
Perceptual watermarking of non i.i.d. signals based on wide spread spectrum using side information
The theoretical foundations of data hiding have been revealed by formulating the problem as message communication over a noisy channel, i.e. the host document. In light of this de...
Christine Guillemot, Gaëtan Le Guelvouit, St&...
106
Voted
ICASSP
2009
IEEE
15 years 9 months ago
Instantaneous frequency rate estimation for high-order polynomial-phase signal
—Instantaneous frequency rate (IFR) estimation for high-order polynomial phase signals (PPSs) is considered. Specifically, an IFR estimator with only a second-order nonlinearity ...
Pu Wang, Hongbin Li, Igor Djurovic, Jianyu Yang
120
Voted
ICASSP
2009
IEEE
15 years 9 months ago
A variational EM algorithm for learning eigenvoice parameters in mixed signals
We derive an efficient learning algorithm for model-based source separation for use on single channel speech mixtures where the precise source characteristics are not known a pri...
Ron J. Weiss, Daniel P. W. Ellis