Results 161 to 170 of about 65,242 (175)

Random subspace method based on Canonical Correlation Analysis

2010 3rd International Congress on Image and Signal Processing, 2010
Random subspace method (RSM) is a successful ensemble construction technique for classification and its success mainly lies in that it could generate quite diverse component classifiers. However, the recognition accuracy of the component classifier is often insufficient due to its random selection of inputs.
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Canonical angles, subspace partitioning, and hyrbrid wavelet packets

SPIE Proceedings, 2000
In previous work, hybrid wavelet packets were introduced as a generalization of wavelet packets in which the choice of quadrature mirror filter (QMF) is selected adaptively within the wavelet packet analysis. This was motivated by the observation that for certain classes of signals, the choice of appropriate QMF is not only signal dependent, but may be
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A canonical subspace of modular forms of half-integral weight

Mathematische Annalen, 2009
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Gun, Sanoli, Manickam, M., Ramakrishnan, B.   +2 more
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A canonical representation for distributions of adaptive matched subspace detectors

Conference Record of the Thirty-First Asilomar Conference on Signals, Systems and Computers (Cat. No.97CB36136), 2002
We present a unified derivation of the distributions for adaptive versions of matched subspace detectors (MSDs) derived by Scharf (see Statistical Signal Processing, Addison-Wesley, and IEEE Trans. Signal Processing, 1996). These include: (1) the matched filter detector, (2) the gain invariant (CFAR) matched filter detector (3) the phase invariant ...
S. Kraut, L.T. McWhorter, L.L. Scharf
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Exploring Shared Subspace and Joint Sparsity for Canonical Correlation Analysis

Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management, 2014
Canonical correlation analysis (CCA) has been extensively employed in various real-world applications of multi-label annotation. However, two major challenges are raised by the classical CCA. First, CCA frequently fails to remove noisy and irrelevant features.
Liang Tao, Horace Ip, Yinglin Wang, Xin Shu   +3 more
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THE CANONICAL LATTICE ISOMORPHISM BETWEEN TOPOLOGIES COMPATIBLE WITH A VECTOR SPACE AND SUBSPACES

Tsukuba Journal of Mathematics, 2023
Let \((K,\nu)\) be a non-discrete valued field whose metric completion is a locally compact space, \(X\) be a finite-dimensional vector space over \(K\), let \((\tau_K(X),\subset)\) be the lattice of all compatible topologies on \(X\) and \((\sigma_K(X),\supset)\) be the lattice of all \(K\)-subspaces of \(X\).
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Target detection and identification using canonical correlation analysis and subspace partitioning

2008 IEEE International Conference on Acoustics, Speech and Signal Processing, 2008
We present a data-driven approach for target detection and identification based on a linear mixture model. Our aim is to determine the existence of certain targets in a mixture without specific information on the targets or the background, and to identify the targets from a given library.
Wei Wang, Tulay Adali, Darren Emge
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3D Object Recognition Based on Canonical Angles between Shape Subspaces

2011
We propose a method to measure similarity of shape for 3D objects using 3-dimensional shape subspaces produced by the factorization method. We establish an index of shape similarity by measuring the geometrical relation between two shape subspaces using canonical angles. The proposed similarity measure is invariant to camera rotation and object motion,
Yosuke Igarashi, Kazuhiro Fukui
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Channel estimation in unknown noise: application of canonical correlation decomposition in subspaces

Proceedings of the Eighth International Symposium on Signal Processing and Its Applications, 2005., 2006
The popular subspace algorithm proposed by Mouline et al. performs well when the channel output is corrupted by white noise. However, when the channel noise is correlated as is often encountered in practice, the standard subspace method degrades in performance.
null Xiaojuan He, K.M. Wong
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Invariant Subspace Topologies and Canonical Decompositions

This paper investigates the intricate relationship between the topological properties of the set of invariant subspaces of a linear operator and the operator's canonical decomposition. The set of all k-dimensional subspaces of a vector space forms a Grassmann manifold, which we endow with a natural topology induced by metrics such as the gap metric. We
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