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» Structured decomposition of adaptive applications
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CSDA
2007
106views more  CSDA 2007»
13 years 10 months ago
Parsimonious additive models
A new method for function estimation and variable selection, specifically designed for additive models fitted by cubic splines is proposed.This new method involves regularizing ...
Marta Avalos, Yves Grandvalet, Christophe Ambroise
ML
2000
ACM
157views Machine Learning» more  ML 2000»
13 years 9 months ago
A Multistrategy Approach to Classifier Learning from Time Series
We present an approach to inductive concept learning using multiple models for time series. Our objective is to improve the efficiency and accuracy of concept learning by decomposi...
William H. Hsu, Sylvian R. Ray, David C. Wilkins
TIP
2008
195views more  TIP 2008»
13 years 9 months ago
Image Coding Using Dual-Tree Discrete Wavelet Transform
In this paper, we explore the application of 2-D dual-tree discrete wavelet transform (DDWT), which is a directional and redundant transform, for image coding. Three methods for sp...
Jingyu Yang, Yao Wang, Wenli Xu, Qionghai Dai
KES
2010
Springer
13 years 8 months ago
Evolving takagi sugeno modelling with memory for slow processes
Evolving Takagi Sugeno (eTS) models are optimised for use in applications with high sampling rates. This mode of use produces excellent prediction results very quickly and with lo...
Simon McDonald, Plamen P. Angelov
ICASSP
2011
IEEE
13 years 1 months ago
Instantaneous phase tracking of oscillatory signals using emd and Rao-Blackwellised particle filtering
A new method for instantaneous phase tracking of oscillatory signals in a narrow band frequency range is proposed. Empirical mode decomposition (EMD), as an adaptive and data-driv...
Delaram Jarchi, Bahador Makkiabadi, Saeid Sanei