Results 251 to 260 of about 300,398 (297)

Lp Norms and the Sinc Function.

Am. Math. Mon., 2010
It’s everywhere! It’s everywhere! … In this note we give elementary proofs of some of the striking asymptotic properties of the p-norm of the ubiquitous sinc function. Based on experimental evidence we conjecture some enticing further properties of the p-norm as a function of p. See, for example, http://www.carma.newcastle.edu.au/~jb616/oscillatory.pdf.
David Borwein, Jonathan M. Borwein, Isaac E. Leonard   +2 more
openaire   +1 more source

Vector and matrix LP norms in polarimetric radar filtering

2012 IEEE International Geoscience and Remote Sensing Symposium, 2012
The paper addresses multi-channel complex image filtering. It provides regularization cost functions associated to non-conventional vector and matrix iv norms for promoting geometry properties. The approach is shown to be efficient for filtering PolSAR images.
Atto, Abdourrahmane, Mercier, Grégoire, Le, Thu Trang, Trouvé, Emmanuel   +3 more
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Lp norm design of stack filters.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society, 1999
This paper addresses the problem of designing optimal stack filters by employing an Lp norm of the error between the desired signal and the estimated one. It is shown that the Lp norm can be expressed as a linear function of the decision errors at the binary levels of the filter.
C. Emanuel Savin, M. Omair Ahmad, M. N. S. Swamy 0001   +2 more
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Combinatorial Search for the Lp-Norm Principal Component of a Matrix

2019 53rd Asilomar Conference on Signals, Systems, and Computers, 2019
We study Lp-norm Principal-Component Analysis (Lp-PCA) of a matrix. For p = 2 (standard PCA), the problem can be solved with standard Singular-Value Decomposition (SVD). For p = 1 (L1-PCA), the problem was recently solved exactly and approximately with efficient iterative algorithms. For general values of p, the exact solution to Lp-PCA remains to date
Dimitris G. Chachlakis, Panos P. Markopoulos   +1 more
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Fast Time Sequence Indexing for Arbitrary Lp Norms [PDF]

, 2018
Fast indexing in time sequence databases for similarity searching has attracted a lot of research recently. Most of the proposals, however, typically centered around the Euclidean distance and its derivatives. We examine the problem of multimodal similarity search in which users can choose the best one from multiple similarity models for their needs.
Byoung-Kee Yi, Christos Faloutsos
openaire   +1 more source

Capped Lp-Norm Graph Embedding for Photo Clustering

Proceedings of the 24th ACM international conference on Multimedia, 2016
Photos are a predominant source of information on a global scale. Cluster analysis of photos can be applied to situation recognition and understanding cultural dynamics. Graph-based learning provides a current approach for modeling data in clustering problems.
Mengfan Tang, Feiping Nie 0001, Ramesh C. Jain   +2 more
openaire   +1 more source

Autoregressive model in the Lp norm space for EEG analysis

Journal of Neuroscience Methods, 2015
The autoregressive (AR) model is widely used in electroencephalogram (EEG) analyses such as waveform fitting, spectrum estimation, and system identification. In real applications, EEGs are inevitably contaminated with unexpected outlier artifacts, and this must be overcome.
Peiyang, Li, Xurui, Wang, Fali, Li, Rui, Zhang, Teng, Ma, Yueheng, Peng, Xu, Lei, Yin, Tian, Daqing, Guo, Tiejun, Liu, Dezhong, Yao, Peng, Xu   +11 more
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Training Lp norm multiple kernel learning in the primal

Neural Networks, 2013
Some multiple kernel learning (MKL) models are usually solved by utilizing the alternating optimization method where one alternately solves SVMs in the dual and updates kernel weights. Since the dual and primal optimization can achieve the same aim, it is valuable in exploring how to perform Lp norm MKL in the primal.
Zhizheng Liang, Shixiong Xia, Yong Zhou 0003, Lei Zhang 0029   +3 more
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Lp Norm Iterative Sparse Solution for EEG Source Localization

IEEE Transactions on Biomedical Engineering, 2007
How to localize the neural electric activities effectively and precisely from the scalp EEG recordings is a critical issue for clinical neurology and cognitive neuroscience. In this paper, based on the spatial sparse assumption of brain activities, proposed is a novel iterative EEG source imaging algorithm, Lp norm iterative sparse solution (LPISS). In
Peng Xu 0001, Yin Tian, Huafu Chen, Dezhong Yao 0001   +3 more
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Lp Normed Spectral Estimation Residual Analysis

Twenty-Second Asilomar Conference on Signals, Systems and Computers, 2005
Seismic sonic log data is characterized by a relatively high signal-to-noise ratio with the possible presence of one or more impulses arising from the data acquisition environment. Frequently, in order to completely analyze sonic log data, a high resolution frequency estimation technique is required that is resistant to the possible presence of ...
J. Schroeder, J. Endsley
openaire   +1 more source