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CANDECOMP/PARAFAC (CP) decomposition is the mostly used model to formulate the received tensor signal in a massive MIMO system, as the receiver generally sums the components from different paths or users. To achieve accurate and low-latency…

Signal Processing · Electrical Eng. & Systems 2024-11-21 Xiao Gong , Wei Chen , Bo Ai , Geert Leus

In this paper, we introduce a sequential variational mode decomposition method to separate non-stationary mixed signals successively. This method is inspired by the variational method, and can precisely recover the original components one…

Signal Processing · Electrical Eng. & Systems 2021-03-11 Wei Chen

We propose an effective and robust algorithm for identifying partial differential equations (PDEs) with space-time varying coefficients from a single trajectory of noisy observations. Identifying unknown differential equations from noisy…

Numerical Analysis · Mathematics 2023-04-13 Yuchen He , Sung-Ha Kang , Wenjing Liao , Hao Liu , Yingjie Liu

A common problem to signal processing are biases introduced by correlated noise. When quantifying time delays between two signals, mixed noise introduces a bias towards zero delay in conventional delay estimates based on the cross- or…

Signal Processing · Electrical Eng. & Systems 2025-06-02 Tin Jurhar , Franziska Pellegrini , Ana I. Nuñes del Toro , Tilman Stephani , Guido Nolte , Stefan Haufe

The problem of sparse approximation and the closely related compressed sensing have received tremendous attention in the past decade. Primarily studied from the viewpoint of applied harmonic analysis and signal processing, there have been…

Information Theory · Computer Science 2018-10-23 Ali Çivril

Temporal graph signals are multivariate time series with individual components associated with nodes of a fixed graph structure. Data of this kind arises in many domains including activity of social network users, sensor network readings…

Machine Learning · Computer Science 2021-06-28 Maxwell McNeil , Lin Zhang , Petko Bogdanov

This paper proposes a grouped pattern (GP) for sensing signals and a corresponding multi-periodogram algorithm for range estimation in integrated sensing and communications (ISAC) systems. GP partitions subcarriers into groups with an…

Information Theory · Computer Science 2026-04-27 Yi Geng , Pan Cao

Compressed sensing has a wide range of applications that include error correction, imaging, radar and many more. Given a sparse signal in a high dimensional space, one wishes to reconstruct that signal accurately and efficiently from a…

Numerical Analysis · Mathematics 2009-05-28 Deanna Needell

There are a variety of industrial products that possess periodic textures or surfaces, such as carbon fiber textiles and display panels. Traditional image-based quality inspection methods for these products require identifying the periodic…

Computer Vision and Pattern Recognition · Computer Science 2024-09-10 Peng Ye , Chengyu Tao , Juan Du

We investigate the phase separation mechanism of bosonic binary mixtures in spatially-fragmented traps, evidencing the emergence of phases featuring a different degree of mixing. The analysis is initially carried out by means of a…

Quantum Gases · Physics 2019-04-19 Vittorio Penna , Andrea Richaud

We consider the demixing problem of two (or more) structured high-dimensional vectors from a limited number of nonlinear observations where this nonlinearity is due to either a periodic or an aperiodic function. We study certain families of…

Machine Learning · Statistics 2017-08-11 Mohammadreza Soltani , Chinmay Hegde

If digital video data is transmitted over unreliable channels such as the internet or wireless terminals, the risk of severe image distortion due to transmission errors is ubiquitous. To cope with this, error concealment can be applied on…

Image and Video Processing · Electrical Eng. & Systems 2022-07-11 Jürgen Seiler , André Kaup

In this paper, a cooperative spectrum sensing scheme based on compressive sensing is proposed. In this scheme, secondary users (SUs) are organized in clusters. In each cluster, SUs forward their compressed signals to the cluster head. Then,…

Information Theory · Computer Science 2019-12-12 Fatima Salahdine , Elias Ghribi , Naima Kaabouch

Koopman mode decomposition and tensor component analysis (also known as CANDECOMP/PARAFAC or canonical polyadic decomposition) are two popular approaches of decomposing high dimensional data sets into low dimensional modes that capture the…

Numerical Analysis · Mathematics 2021-05-19 William T. Redman

In federated learning, communication cost is often a critical bottleneck to scale up distributed optimization algorithms to collaboratively learn a model from millions of devices with potentially unreliable or limited communication and…

Machine Learning · Computer Science 2020-11-24 Farzin Haddadpour , Mohammad Mahdi Kamani , Aryan Mokhtari , Mehrdad Mahdavi

In this paper, we develop a systematic framework for the time-sequential compression of dynamic probabilistic occupancy grids. Our approach leverages ideas from signal compression theory to formulate an optimization problem that searches…

Robotics · Computer Science 2025-04-16 Daniel T. Larsson , Dipankar Maity

This paper studies the secrecy rate maximization problem of a secure wireless communication system, in the presence of multiple eavesdroppers. The security of the communication link is enhanced through cooperative jamming, with the help of…

Information Theory · Computer Science 2017-01-13 Kanapathippillai Cumanan , George C. Alexandropoulos , Zhgiuo Ding , George K. Karagiannidis

We investigate the fading cognitive multiple access wiretap channel (CMAC-WT), in which two secondary-user transmitters (STs) send secure messages to a secondary-user receiver (SR) in the presence of an eavesdropper (ED) and subject to…

Signal Processing · Electrical Eng. & Systems 2020-03-31 Juening Jin , Chengshan Xiao , Meixia Tao , Wen Chen

In this paper we propose a novel data-level algorithm for handling data imbalance in the classification task, Synthetic Majority Undersampling Technique (SMUTE). SMUTE leverages the concept of interpolation of nearby instances, previously…

Machine Learning · Computer Science 2021-04-20 Michał Koziarski

Multiple-input multiple-output (MIMO) is a key ingredient of next-generation wireless communications. Recently, various MIMO signal detectors based on deep learning techniques and quantum(-inspired) algorithms have been proposed to improve…

Information Theory · Computer Science 2023-07-25 Satoshi Takabe