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We consider the robust filtering problem for a state-space model with outliers in correlated measurements. We propose a new robust filtering framework to further improve the robustness of conventional robust filters. Specifically, the…

Applications · Statistics 2020-11-30 Hongwei Wang , Yuanyuan Liu , Wei Zhang , Junyi Zuo

Integrated sensing and communication is a key feature in next-generation wireless networks, enabling joint data transmission and environmental radar sensing on shared spectrum. In multi-user scenarios, simultaneous transmissions cause…

Signal Processing · Electrical Eng. & Systems 2026-01-30 Laurits Randers , Martin Voigt Vejling , Petar Popovski

Traditional fault diagnosis methods struggle to handle fault data, with complex data characteristics such as high dimensions and large noise. Deep learning is a promising solution, which typically works well only when labeled fault data are…

Machine Learning · Computer Science 2025-03-13 Dandan Zhao , Hongpeng Yin , Jintang Bian , Han Zhou

Anomaly detection aims at identifying data points that show systematic deviations from the majority of data in an unlabeled dataset. A common assumption is that clean training data (free of anomalies) is available, which is often violated…

Machine Learning · Computer Science 2022-07-20 Chen Qiu , Aodong Li , Marius Kloft , Maja Rudolph , Stephan Mandt

Detecting a small number of outliers from a set of data observations is always challenging. This problem is more difficult in the setting of multiple network samples, where computing the anomalous degree of a network sample is generally not…

Artificial Intelligence · Computer Science 2016-10-04 Xuan-Hong Dang , Arlei Silva , Ambuj Singh , Ananthram Swami , Prithwish Basu

Massive Multiple Input Multiple Output (MIMO) offers superior capacity for future networks. In the quest for energy efficient implementation of these large array-based trans-mission systems, the power consumption of the Power…

Information Theory · Computer Science 2021-11-30 Laura Monteyne , Gilles Callebaut , Björn Sihlbom , Liesbet Van der Perre

The statistical properties of nonlinear phase noise, often called the Gordon-Mollenauer effect, is studied analytically when the number of fiber spans is very large. The joint characteristic functions of the nonlinear phase noise with…

Optics · Physics 2007-05-23 Keang-Po Ho

A simple procedure for the design of recursive digital filters with an infinite impulse response (IIR) and non-recursive digital filters with a finite impulse response (FIR) is described. The fixed-lag smoothing filters are designed to…

Signal Processing · Electrical Eng. & Systems 2025-07-22 Hugh Lachlan Kennedy

Image sequences filtering have recently become a very important technical problem especially with the advent of new technology in multimedia and video systems applications. Often image sequences are corrupted by some amount of noise…

Computer Vision and Pattern Recognition · Computer Science 2013-04-18 Soumaya Hichri , Faouzi Benzarti , Hamid Amiri

Functional magnetic resonance imaging (fMRI) data contain high levels of noise and artifacts. To avoid contamination of downstream analyses, fMRI-based studies must identify and remove these noise sources prior to statistical analysis. One…

Methodology · Statistics 2023-05-03 Fatma Parlak , Damon D. Pham , Amanda F. Mejia

Nonlinearities can be introduced into communication systems by the physical components such as the power amplifier, or during signal propagation through a nonlinear channel. These nonlinearities can be compensated by a nonlinear equalizer…

Signal Processing · Electrical Eng. & Systems 2019-05-15 Etsushi Yamazaki , Nariman Farsad , Andrea Goldsmith

Periodic disturbances composed of harmonics typically occur during periodic operations, impairing performance of mechanical and electrical systems. To improve the performance, control of periodic-disturbance suppression has been studied,…

Systems and Control · Electrical Eng. & Systems 2025-06-13 Hisayoshi Muramatsu

High-dimensional data poses unique challenges in outlier detection process. Most of the existing algorithms fail to properly address the issues stemming from a large number of features. In particular, outlier detection algorithms perform…

Machine Learning · Computer Science 2020-09-22 Firuz Kamalov , Ho Hon Leung

Motivated by the looming "capacity crunch" in fiber-optic networks, information transmission over such systems is revisited. Among numerous distortions, inter-channel interference in multiuser wavelength-division multiplexing (WDM) is…

Information Theory · Computer Science 2014-10-09 Mansoor I. Yousefi , Frank R. Kschischang

The development of new phased array systems in radio astronomy, as the low frequency array (LOFAR) and the square kilometre array (SKA), formed of a large number of small and flexible elementary antennas, has led to significant challenges.…

In modern wireless networks, interference is no longer negligible since each cell becomes smaller to support high throughput. The reduced size of each cell forces to install many cells, and consequently causes to increase inter-cell…

Information Theory · Computer Science 2012-09-19 Hyukjoon Kwon , Jungwon Lee , Inyup Kang

Out-of-system (OoS) interference is a potential limitation for distributed networks that operate in unlicensed spectrum or in a spectrum sharing scenario. The OoS interference differs from the in-system interference in that OoS signals and…

Information Theory · Computer Science 2024-05-08 Zakir Hussain Shaik , Erik G. Larsson

Camera motion deblurring is an important low-level vision task for achieving better imaging quality. When a scene has outliers such as saturated pixels, the captured blurred image becomes more difficult to restore. In this paper, we propose…

Image and Video Processing · Electrical Eng. & Systems 2021-04-28 Meng Chang , Chenwei Yang , Huajun Feng , Zhihai Xu , Qi Li

We propose thresholding as an approach to deal with class imbalance. We define the concept of thresholding as a process of determining a decision boundary in the presence of a tunable parameter. The threshold is the maximum value of this…

Machine Learning · Computer Science 2016-07-12 Charmgil Hong , Rumi Ghosh , Soundar Srinivasan

Massive multiple-input multiple-output (mMIMO) technology is considered a key enabler for the 5G and future wireless networks. In most wireless communication systems, mMIMO is employed together with orthogonal frequency-division…

Networking and Internet Architecture · Computer Science 2023-07-03 Marcin Wachowiak , Pawel Kryszkiewicz