Results 71 to 80 of about 12,007,100 (152)

Robust subspace methods for outlier detection in genomic data circumvents the curse of dimensionality. [PDF]

R Soc Open Sci, 2020
Shetta O, Niranjan M.
europepmc   +1 more source

Time- and Frequency-Domain-Spread Generalized Multicarrier DS-CDMA Using Subspace-Based Blind and Group-Blind Space–Time Multiuser Detection

, 2008
—Subspace-based blind and group-blind space–time (ST) multiuser detection (MUD) is invoked for a smart-antenna-aided gen-eralized multicarrier direct-sequence code-division multiple-access (MC DS-CDMA) system communicating over a dispersive ST Rayleigh ...
Lie-liang Yang, Yang, Lie-Liang, Hu, Bin, Hanzo, Lajos, Lajos Hanzo, Bin Hu   +5 more
core  

Learning binary code for fast nearest subspace search

, 2020
Subspace is widely used to represent objects under different viewpoints, illuminations, identities, and more. Due to the growing amount and dimensionality of visual contents, fast search in a large-scale database with high-dimensional subspaces is an ...
Liu, X, Hancock, ER, Zhou, J, Bai, X, Zhou, L   +4 more
core   +1 more source

Reduced-Rank Adaptive Filtering Using Krylov Subspace

EURASIP Journal on Advances in Signal Processing, 2002
A unified view of several recently introduced reduced-rank adaptive filters is presented. As all considered methods use Krylov subspace for rank reduction, the approach taken in this work is inspired from Krylov subspace methods for iterative solutions ...
Burykh Sergueï, Abed-Meraim Karim
doaj   +1 more source

SUBSPACE IDENTIFICATION METHOD FOR STOCHASTIC LINEAR CONTROL SYSTEMS

Ural Mathematical Journal
Subspace identification is studied for stochastic linear control systems in state-space form. PO-MOESP (Past Outputs Multivariable Output-Error State sPace) algorithm is described, implemented and compared with other subspace identification methods and ...
Nikita M. Kharkovskii, Nikolai B. Melnikov   +1 more
doaj   +1 more source

Subspace Learning for Dual High-Order Graph Learning Based on Boolean Weight

Entropy
Subspace learning has achieved promising performance as a key technique for unsupervised feature selection. The strength of subspace learning lies in its ability to identify a representative subspace encompassing a cluster of features that are capable of
Yilong Wei, Jinlin Ma, Ziping Ma, Yulei Huang   +3 more
doaj   +1 more source

Subspace-hypercyclic weighted shifts

, 2018
Our aim in this paper is to obtain necessary and sufficient conditions for bilateral and unilateral weighted shift operators to be subspace-transitive. We show that the Herrero question [6] holds true even on a subspace of a Hilbert space, i.e.
Nareen Bamerni, Kılıçman, Adem, Adem Kılıçman, Bamerni, Nareen   +3 more
core   +1 more source

Subspace-Based Blind and Group-Blind Space-Time Multiuser Detection for the Generalized Multicarrier DS-CDMA Uplink

, 2006
Subspace-based blind and group-blind space-time multiuser detection is invoked for a smart antenna aided generalized MC DS-CDMA system communicating over a dispersive Space-Time (ST) Rayleigh fading channel, where the channel estimates are attained by ...
Yang, L-L., Hanzo, L., Hu, B.
core   +1 more source

Linear Invariant Systems Theory for Signal Enhancement [PDF]

, 2011
This paper discusses a linear time invariant (LTI) systems approach to signal enhancement via projective subspace techniques. It provides closed form expressions for the frequency response of data adaptive finite impulse response eigenfilters.
Lang, Elmar W., Georgieva, P., Teixeira, A. J. S., Miguel, G., Tomé, A.M., Teixeira, Ana Rita   +5 more
core  

Deep Consistent-Inherent Learning for Cross-Modal Subspace Clustering

Guidance, Navigation and Control
Deep cross-modal clustering has been developing at a rapid pace and attracted great attention. It aims to pursue a consistent subspace from different modalities by conventional neural network and achieve remarkable clustering performance.
Yuzhuo Feng, Demin Zhou
doaj   +1 more source