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Tensor Decompositions for Signal Processing Applications: From two-way to multiway component analysis
- A. Cichocki, D. Mandic, A. Phan
- Computer ScienceIEEE Signal Processing Magazine
- 17 March 2014
TLDR
Recurrent Neural Networks for Prediction: Learning Algorithms, Architectures and Stability
- D. Mandic, J. Chambers
- Computer Science
- 7 August 2001
TLDR
Filter Bank Property of Multivariate Empirical Mode Decomposition
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Multivariate multiscale entropy: a tool for complexity analysis of multichannel data.
- Mosabber Uddin Ahmed, D. Mandic
- Computer SciencePhysical review. E, Statistical, nonlinear, and…
- 27 December 2011
TLDR
A generalized normalized gradient descent algorithm
- D. Mandic
- Computer ScienceIEEE Signal Processing Letters
- 30 January 2004
TLDR
Complex Valued Nonlinear Adaptive Filters: Noncircularity, Widely Linear and Neural Models
This book was written in response to the growing demand for a text that provides a unified treatment of linear and nonlinear complex valued adaptive filters, and methods for the processing of general…
Tensor Networks for Dimensionality Reduction and Large-scale Optimization: Part 1 Low-Rank Tensor Decompositions
- A. Cichocki, Namgil Lee, I. Oseledets, A. Phan, Qibin Zhao, D. Mandic
- Computer ScienceFound. Trends Mach. Learn.
- 19 December 2016
TLDR
Empirical Mode Decomposition-Based Time-Frequency Analysis of Multivariate Signals: The Power of Adaptive Data Analysis
- D. Mandic, N. Rehman, Zhaohua Wu, N. Huang
- EngineeringIEEE Signal Processing Magazine
- 16 October 2013
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Empirical Mode Decomposition for Trivariate Signals
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Multivariate Multiscale Entropy Analysis
- Mosabber Uddin Ahmed, D. Mandic
- Computer ScienceIEEE Signal Processing Letters
- 1 February 2012
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