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» Nonlinear Predictive Control with a Gaussian Process Model
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BC
2000
95views more  BC 2000»
15 years 1 months ago
Cerebellar learning of accurate predictive control for fast-reaching movements
Long conduction delays in the nervous system prevent the accurate control of movements by feedback control alone. We present a new, biologically plausible cerebellar model to study...
Jacob Spoelstra, Nicolas Schweighofer, Michael A. ...
ICASSP
2010
IEEE
15 years 2 months ago
Statistical approach to enhancing esophageal speech based on Gaussian mixture models
This paper presents a novel method of enhancing esophageal speech using statistical voice conversion. Esophageal speech is one of the alternative speaking methods for laryngectome...
Hironori Doi, Keigo Nakamura, Tomoki Toda, Hiroshi...
ICDM
2008
IEEE
224views Data Mining» more  ICDM 2008»
15 years 8 months ago
A Non-parametric Approach to Pair-Wise Dynamic Topic Correlation Detection
We introduce dynamic correlated topic models (DCTM) for analyzing discrete data over time. This model is inspired by the hierarchical Gaussian process latent variable models (GP-L...
Yang Song, Lu Zhang 0007, C. Lee Giles
119
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CIDM
2007
IEEE
15 years 8 months ago
Application of Neural Networks for Data Modeling of Power Systems with Time Varying Nonlinear Loads
— Nowadays power distribution systems typically operate with nonsinusoidal voltages and currents. Harmonic currents from nonlinear loads propagate through the system and cause ha...
Joy Mazumdar, Ganesh K. Venayagamoorthy, Ronald G....
CVPR
2011
IEEE
14 years 5 months ago
Nonlinear Shape Manifolds as Shape Priors in Level Set Segmentation and Tracking
We propose a novel nonlinear, probabilistic and variational method for adding shape information to level setbased segmentation and tracking. Unlike previous work, we represent sha...
Victor Prisacariu, Ian Reid