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Related papers: Blind Source Separation over Space

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We examine the problem of estimating the trace of a matrix $A$ when given access to an oracle which computes $x^\dagger A x$ for an input vector $x$. We make use of the basis vectors from a set of mutually unbiased bases, widely studied in…

Numerical Analysis · Computer Science 2016-08-02 J. K. Fitzsimons , M. A. Osborne , S. J. Roberts , J. F. Fitzsimons

In this paper we propose a method for separation of moving sound sources. The method is based on first tracking the sources and then estimation of source spectrograms using multichannel non-negative matrix factorization (NMF) and extracting…

Sound · Computer Science 2017-10-30 Joonas Nikunen , Aleksandr Diment , Tuomas Virtanen

Underdetermined Blind Source Separation(UBSS) is an important issue, for sparse signals, a novel two-step approach for UBSS based on the law of large numbers and minimum intersection angle rule (LM method) is presented. In the first step,…

Signal Processing · Electrical Eng. & Systems 2018-10-08 Xu Peng-fei , Jia Yin-jie , Wang Zhi-jian

We propose a new and easy-to-use method for identifying cointegrated components of nonstationary time series, consisting of an eigenanalysis for a certain non-negative definite matrix. Our setting is model-free, and we allow the…

Methodology · Statistics 2018-03-13 Rongmao Zhang , Peter Robinson , Qiwei Yao

Blind source separation is a common processing tool to analyse the constitution of pixels of hyperspectral images. Such methods usually suppose that pure pixel spectra (endmembers) are the same in all the image for each class of materials.…

Methodology · Statistics 2022-10-03 Charlotte Revel , Yannick Deville , Véronique Achard , Xavier Briottet

Convolutive blind source separation (BSS) is intended to recover the unknown components from their convolutive mixtures. Contrary to the contrast functions used in instantaneous cases, the spatial-temporal prewhitening stage and the…

Signal Processing · Electrical Eng. & Systems 2021-07-30 YunPeng Li

A class of robust estimators of scatter applied to information-plus-impulsive noise samples is studied, where the sample information matrix is assumed of low rank; this generalizes the study of (Couillet et al., 2013b) to spiked random…

Probability · Mathematics 2014-05-01 Romain Couillet

In this work, we develop a provable fast algorithm for blind super-resolution based on the low rank structure of vectorized Hankel matrix associated with the target matrix. Theoretical results show that the proposed method converges to the…

Information Theory · Computer Science 2022-01-27 Zengying Zhu , Jinchi Chen , Weiguo Gao

Achieving resolution in the sub-Rayleigh regime (superresolution) is one of the rapidly developing topics in quantum optics and metrology. Recently, it was shown that perfect measurement based on spatial mode demultiplexing (SPADE) in…

Quantum Physics · Physics 2025-04-01 Konrad Schlichtholz , Łukasz Rudnicki

In this paper, we present an information theoretic analysis of the blind signal classification algorithm. We show that the algorithm is equivalent to a Maximum A Posteriori (MAP) estimator based on estimated parametric probability models.…

Information Theory · Computer Science 2010-01-13 Xudong Ma

Improving axial resolution is crucial for three-dimensional optical imaging systems. Here we present a scheme of axial superresolution for two incoherent point sources based on spatial mode demultiplexing. A radial mode sorter is used to…

We review our recent results on pseudo-hermitian random matrix theory which were hitherto presented in various conferences and talks. (Detailed accounts of our work will appear soon in separate publications.) Following an introduction of…

Mathematical Physics · Physics 2021-10-27 Joshua Feinberg , Roman Riser

We introduce a new method for sparse principal component analysis, based on the aggregation of eigenvector information from carefully-selected axis-aligned random projections of the sample covariance matrix. Unlike most alternative…

Methodology · Statistics 2019-05-07 Milana Gataric , Tengyao Wang , Richard J. Samworth

Blind gain and phase calibration (BGPC) is a structured bilinear inverse problem, which arises in many applications, including inverse rendering in computational relighting (albedo estimation with unknown lighting), blind phase and gain…

Information Theory · Computer Science 2016-11-03 Yanjun Li , Kiryung Lee , Yoram Bresler

Online blind source separation is essential for both speech communication and human-machine interaction. Among existing approaches, overdetermined independent vector analysis (OverIVA) delivers strong performance by exploiting the…

Audio and Speech Processing · Electrical Eng. & Systems 2026-01-21 Kang Chen , Xianrui Wang , Yichen Yang , Andreas Brendel , Gongping Huang , Zbyněk Koldovský , Jingdong Chen , Jacob Benesty , Shoji Makino

6D pose estimation aims at determining the object pose that best explains the camera observation. The unique solution for non-ambiguous objects can turn into a multi-modal pose distribution for symmetrical objects or when occlusions of…

Computer Vision and Pattern Recognition · Computer Science 2026-01-09 Boris Meden , Asma Brazi , Fabrice Mayran de Chamisso , Steve Bourgeois , Vincent Lepetit

This paper is concerned with the interplay between statistical asymmetry and spectral methods. Suppose we are interested in estimating a rank-1 and symmetric matrix $\mathbf{M}^{\star}\in \mathbb{R}^{n\times n}$, yet only a randomly…

Statistics Theory · Mathematics 2023-01-10 Yuxin Chen , Chen Cheng , Jianqing Fan

We present a technique for the blind separation of components in CMB data. The method uses a spectral EM algorithm which recovers simultaneously component templates, their emission law as a function of wavelength, and noise levels. We test…

In this paper we introduce a new and simple method to estimate the symbol rate for single carrier systems of unknown modulation. The introduced technique detects the symbol rate from a continuous range of symbol rates, i.e. it does not…

Signal Processing · Electrical Eng. & Systems 2020-04-27 Mahmoud Elgenedy , Ayman Elezabi

We consider Bayesian optimization of an expensive-to-evaluate black-box objective function, where we also have access to cheaper approximations of the objective. In general, such approximations arise in applications such as reinforcement…

Machine Learning · Statistics 2016-11-16 Matthias Poloczek , Jialei Wang , Peter I. Frazier
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