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Attention mechanisms have achieved significant empirical success in multiple fields, but their underlying optimization objectives remain unclear yet. Moreover, the quadratic complexity of self-attention has become increasingly prohibitive.…

Machine Learning · Computer Science 2025-11-06 Qishuai Wen , Zhiyuan Huang , Chun-Guang Li

The traditional compressed sensing approach is naturally offline, in that it amounts to sparsely sampling and reconstructing a given dataset. Recently, an online algorithm for performing compressed sensing on streaming data was proposed:…

Optimization and Control · Mathematics 2016-05-10 Pantelis Sopasakis , Nikolaos Freris , Panagiotis Patrinos

Broadband channel is often characterized by a sparse multipath channel where dominant multipath taps are widely separated in time, thereby resulting in a large delay spread. Traditionally, accurate channel estimation is done by sampling…

Information Theory · Computer Science 2012-07-31 Guan Gui , Aihua Kuang , Ling Wang

In this paper, we propose improved estimation method for logistic regression based on subsamples taken according the optimal subsampling probabilities developed in Wang et al. 2018 Both asymptotic results and numerical results show that the…

Methodology · Statistics 2021-06-24 HaiYing Wang

A novel linear blind adaptive receiver based on joint iterative optimization (JIO) and the constrained constant modulus (CCM) design criterion is proposed for interference suppression in direct-sequence ultra-wideband (DS-UWB) systems. The…

Information Theory · Computer Science 2013-05-15 Sheng Li , Rodrigo C. de Lamare

For wideband spectrum sensing, compressive sensing has been proposed as a solution to speed up the high dimensional signals sensing and reduce the computational complexity. Compressive sensing consists of acquiring the essential information…

Signal Processing · Electrical Eng. & Systems 2018-02-13 Fatima Salahdine , Naima Kaabouch , Hassan El Ghazi

In this work, we examine sampling problems with non-smooth potentials. We propose a novel Markov chain Monte Carlo algorithm for sampling from non-smooth potentials. We provide a non-asymptotical analysis of our algorithm and establish a…

Machine Learning · Computer Science 2022-02-11 Jiaming Liang , Yongxin Chen

In this paper, to synchronize Ultra Wideband (UWB) systems in ad-hoc multi-user environments, we propose a new timing acquisition approach for achieving a good performance despite the difficulties to get there. Synchronization constraints…

Networking and Internet Architecture · Computer Science 2012-09-13 Moez Hizem , Ridha Bouallegue

1-bit compressive sensing aims to recover sparse signals from quantized 1-bit measurements. Designing efficient approaches that could handle noisy 1-bit measurements is important in a variety of applications. In this paper we use the…

Information Theory · Computer Science 2022-04-28 Shuai Huang , Trac D. Tran

Capacity is one of the most important performance metrics for wireless communication networks. It describes the maximum rate at which the information can be transmitted of a wireless communication system. To support the growing demand for…

Signal Processing · Electrical Eng. & Systems 2022-09-05 Dandan Jiang , Han Hao , Lu Yang , Rui Wang

Recent results from compressive sampling (CS) have demonstrated that accurate reconstruction of sparse signals often requires far fewer samples than suggested by the classical Nyquist--Shannon sampling theorem. Typically, signal…

Fluid Dynamics · Physics 2014-04-24 Gudmundur F. Adalsteinsson , Nicholas K. -R. Kevlahan

In two-way time-of-arrival (TOA) systems, a user device (UD) obtains its position by round-trip communications to a number of anchor nodes (ANs) at known locations. The objective function of the maximum likelihood (ML) method for two-way…

Signal Processing · Electrical Eng. & Systems 2021-03-18 Sihao Zhao , Xiao-Ping Zhang , Xiaowei Cui , Mingquan Lu

Quantum waveform estimation, in which quantum sensors sample entire time series, promises to revolutionize the sensing of weak and stochastic signals, such as the biomagnetic impulses emitted by firing neurons. For long duration signals…

This paper presents a novel power spectral density estimation technique for band-limited, wide-sense stationary signals from sub-Nyquist sampled data. The technique employs multi-coset sampling and incorporates the advantages of compressed…

Information Theory · Computer Science 2012-05-18 Michael A. Lexa , Mike E. Davies , John S. Thompson

Broadband wireless channel is a time dispersive and becomes strongly frequency selective. In most cases, the channel is composed of a few dominant coefficients and a large part of coefficients is approximately zero or zero. To exploit the…

Information Theory · Computer Science 2010-05-14 Guan Gui , Wei Peng , Qun Wan , Fumiyuki Adachi

We develop an ultrawideband (UWB) inverse scattering technique for reconstructing continuous random media based on Bayesian compressive sensing. In addition to providing maximum a posteriori estimates of the unknown weights, Bayesian…

Data Analysis, Statistics and Probability · Physics 2014-11-27 A. E. Fouda , F. L. Teixeira

Consider the task of estimating a 3-order $n \times n \times n$ tensor from noisy observations of randomly chosen entries in the sparse regime. We introduce a similarity based collaborative filtering algorithm for estimating a tensor from…

Machine Learning · Computer Science 2023-01-18 Devavrat Shah , Christina Lee Yu

Ultra-wideband (UWB) time difference of arrival (TDOA)-based localization has recently emerged as a promising indoor positioning solution. However, in cluttered environments, both the UWB radio positions and the obstacle-induced…

Robotics · Computer Science 2022-04-12 Wenda Zhao , Abhishek Goudar , Angela P. Schoellig

Using low-frequency (UHF to L-band) ultra-wideband (UWB) synthetic aperture radar (SAR) technology for detecting buried and obscured targets, e.g. bomb or mine, has been successfully demonstrated recently. Despite promising recent progress,…

Signal Processing · Electrical Eng. & Systems 2018-10-09 Tiep Vu , Lam Nguyen , Vishal Monga

Compressed sensing is a signal processing method that acquires data directly in a compressed form. This allows one to make less measurements than what was considered necessary to record a signal, enabling faster or more precise measurement…

Statistical Mechanics · Physics 2012-08-20 Florent Krzakala , Marc Mézard , François Sausset , Yifan Sun , Lenka Zdeborová