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This paper is concerned with the asymptotic optimality of spectral coarse spaces for two-level iterative methods. Spectral coarse spaces, namely coarse spaces obtained as the span of the slowest modes of the used one-level smoother, are…

Numerical Analysis · Mathematics 2021-03-18 Gabriele Ciaramella , Tommaso Vanzan

In this paper, we propose a new algorithm for the estimation of multiple time delays (TDs). Since a TD is a fundamental spatial cue for sensor array signal processing techniques, many methods for estimating it have been studied. Most of…

Signal Processing · Electrical Eng. & Systems 2022-03-24 Kouei Yamaoka , Yukoh Wakabayashi , Nobutaka Ono

In this paper, we address the problem of target detection in the presence of coherent (or fully correlated) signals, which can be due to multipath propagation effects or electronic attacks by smart jammers. To this end, we formulate the…

Signal Processing · Electrical Eng. & Systems 2021-02-24 Sudan Han , Linjie Yan , Yuxuan Zhang , Pia Addabbo , Chengpeng Hao , Danilo Orlando

Binary sequences with optimal autocorrelation and large linear complexity have important applications in cryptography and communications. Very recently, a class of binary sequences of period $4p$ with optimal autocorrelation was proposed…

Information Theory · Computer Science 2018-01-03 Cuiling Fan

This research is motivated by the need for effective classification in ice-breaking dynamic simulations, aimed at determining the conditions under which an underwater vehicle will break through the ice. This simulation is extremely…

Methodology · Statistics 2025-06-05 Tian Bai , Dianpeng Wang , Kuangqi Chen , Xu He

Datasets from the fields of bioinformatics, chemometrics, and face recognition are typically characterized by small samples of high-dimensional data. Among the many variants of linear discriminant analysis that have been proposed in order…

Machine Learning · Statistics 2020-04-20 Lama B. Niyazi , Abla Kammoun , Hayssam Dahrouj , Mohamed-Slim Alouini , Tareq Y. Al-Naffouri

Decision making under uncertainty is challenging as the data-generating process (DGP) is often unknown. Bayesian inference proceeds by estimating the DGP through posterior beliefs on the model's parameters. However, minimising the expected…

Machine Learning · Computer Science 2025-06-13 Charita Dellaporta , Patrick O'Hara , Theodoros Damoulas

Shearlet systems have been introduced as directional representation systems, which provide optimally sparse approximations of a certain model class of functions governed by anisotropic features while allowing faithful numerical realizations…

Functional Analysis · Mathematics 2014-11-11 Gitta Kutyniok , Wang-Q Lim

Despite recent advancements in Self-Supervised Learning (SSL) for time series analysis, a noticeable gap persists between the anticipated achievements and actual performance. While these methods have demonstrated formidable generalization…

Machine Learning · Computer Science 2024-07-25 Adrian Atienza , Jakob Bardram , Sadasivan Puthusserypady

Industry 4.0 aims to optimize the manufacturing environment by leveraging new technological advances, such as new sensing capabilities and artificial intelligence. The DRAEM technique has shown state-of-the-art performance for unsupervised…

Computer Vision and Pattern Recognition · Computer Science 2022-12-20 Jože M. Rožanec , Patrik Zajec , Spyros Theodoropoulos , Erik Koehorst , Blaž Fortuna , Dunja Mladenić

Distributed integrated sensing and communication (D-ISAC) enables multiple spatially distributed nodes to cooperatively perform sensing and communication. However, achieving coherent cooperation across distributed nodes is challenging due…

Systems and Control · Electrical Eng. & Systems 2026-04-06 Seonghoon Yoo , Seulhyun Kwon , Kawon Han , Elaheh Ataeebojd , Mehdi Rasti , Joonhyuk Kang

In this paper, we synthesize two aperiodic-sampled deep neural network (DNN) control schemes, based on the closed-loop tracking stability guarantees. By means of the integral quadratic constraint coping with the input-output behaviour of…

Systems and Control · Electrical Eng. & Systems 2025-06-24 Renjie Ma , Zhijian Hu , Rongni Yang , Ligang Wu

Sequential recommender systems (SRSs) aim to predict the subsequent items which may interest users via comprehensively modeling users' complex preference embedded in the sequence of user-item interactions. However, most of existing SRSs…

Information Retrieval · Computer Science 2024-10-31 Chengkai Huang , Shoujin Wang , Xianzhi Wang , Lina Yao

Deep generative models (DGMs) for graphs achieve impressively high expressive power thanks to very efficient and scalable neural networks. However, these networks contain non-linearities that prevent analytical computation of many standard…

Machine Learning · Computer Science 2025-08-12 Martin Rektoris , Milan Papež , Václav Šmídl , Tomáš Pevný

Symbol-pair code is a new coding framework which is proposed to correct errors in the symbol-pair read channel. In particular, maximum distance separable (MDS) symbol-pair codes are a kind of symbol-pair codes with the best possible…

Information Theory · Computer Science 2016-08-10 Shuxing Li , Gennian Ge

In this paper, the introduction of interference cancellation in full-duplex joint radar and communication receivers is analysed. More specifically, a focus is made on scenarios in which the receiver simultaneously receives radar echoes from…

Signal Processing · Electrical Eng. & Systems 2024-10-02 François De Saint Moulin , Claude Oestges , Luc Vandendorpe

There is significant recent interest in designing new modulation schemes for doubly-selective channels with large delay and Doppler spreads, where legacy modulation schemes based on time-frequency signal representations underperform.…

Signal Processing · Electrical Eng. & Systems 2026-02-10 Nishant Mehrotra , Sandesh Rao Mattu , Robert Calderbank

The problem of joint detection and lossless source coding is considered. We derive asymptotically optimal decision rules for deciding whether or not a sequence of observations has emerged from a desired information source, and to compress…

Information Theory · Computer Science 2016-11-17 Neri Merhav

The complete complementary code (CCC) is a sequence family with ideal correlation sums which was proposed by Suehiro and Hatori. Numerous literatures show its applications to direct-spread code-division multiple access (DS-CDMA) systems for…

Information Theory · Computer Science 2010-03-16 Chenggao Han , Naoki Suehiro , Takeshi Hashimoto

We construct two families of deterministic sensing matrices where the columns are obtained by exponentiating codewords in the quaternary Delsarte-Goethals code $DG(m,r)$. This method of construction results in sensing matrices with low…

Information Theory · Computer Science 2010-04-29 Robert Calderbank , Sina Jafarpour
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