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NECO
2011
13 years 12 days ago
Least-Squares Independent Component Analysis
Accurately evaluating statistical independence among random variables is a key element of Independent Component Analysis (ICA). In this paper, we employ a squared-loss variant of ...
Taiji Suzuki, Masashi Sugiyama
IJCSS
2006
116views more  IJCSS 2006»
13 years 5 months ago
Extracting Motor Unit Firing Information by Independent Component Analysis of Surface Electromyogram: A Preliminary Study Using
Decomposition of electromyogram (EMG) provides a valuable means of obtaining motor unit recruitment and firing rate information. The feasibility of decomposing surface EMG signals...
Ping Zhou, M. M. Lowery, W. Zev Rymer
DELTA
2010
IEEE
13 years 10 months ago
Independent Component Analysis Applied to Watermark Extraction and its Implemented Model on FPGAs
: Most of published audio watermark algorithms are suffered a trade-off between inaudibility and detectibility, and the detection performance depends greatly on the strength of noi...
Thuong Le-Tien, Dien Vo-Ngoc, Lan Ngo-Hoang, Sung ...
IDA
2009
Springer
13 years 3 months ago
Hierarchical Extraction of Independent Subspaces of Unknown Dimensions
Abstract. Independent Subspace Analysis (ISA) is an extension of Independent Component Analysis (ICA) that aims to linearly transform a random vector such as to render groups of it...
Peter Gruber, Harold W. Gutch, Fabian J. Theis
BMCBI
2010
155views more  BMCBI 2010»
13 years 5 months ago
A flexible R package for nonnegative matrix factorization
Background: Nonnegative Matrix Factorization (NMF) is an unsupervised learning technique that has been applied successfully in several fields, including signal processing, face re...
Renaud Gaujoux, Cathal Seoighe