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Realizing capacity demands of future wireless communications requires improved spectral efficiency in the sub-6-GHz frequency bands. This paper proposes a novel eight-element multiple-input multiple-output (MIMO) antenna that can be tuned…

Signal Processing · Electrical Eng. & Systems 2018-08-24 Jari-Matti Hannula , Tapio O. Saarinen , Anu Lehtovuori , Jari Holopainen , Ville Viikari

Network models provide a powerful and flexible framework for analyzing a wide range of structured data sources. In many situations of interest, however, multiple networks can be constructed to capture different aspects of an underlying…

Social and Information Networks · Computer Science 2021-11-03 Madeline Navarro , Genevera I. Allen , Michael Weylandt

The use of the THz frequency domain in future network generations offers an unparalleled level of capacity, which can enhance innovative applications in wireless communication, analytics, and imaging. Communication technologies rely on…

Beam-Hopping (BH) and precoding are two trending technologies for the satellite community. While BH enables flexibility to adapt the offered capacity to the heterogeneous demand, precoding aims at boosting the spectral efficiency. In this…

Information Theory · Computer Science 2019-05-06 Mirza Golam Kibria , Eva Lagunas , Nicola Maturo , Danilo Spano , Symeon Chatzinotas

Clustering performs an essential role in many real world applications, such as market research, pattern recognition, data analysis, and image processing. However, due to the high dimensionality of the input feature values, the data being…

Machine Learning · Computer Science 2021-02-16 Si Lu , Ruisi Li

The problem of constrained clustering has attracted significant attention in the past decades. In this paper, we study the balanced $k$-center, $k$-median, and $k$-means clustering problems where the size of each cluster is constrained by…

Computational Geometry · Computer Science 2018-09-11 Hu Ding

Broad searches for continuous gravitational wave signals rely on hierarchies of follow-up stages for candidates above a given significance threshold. An important step to simplify these follow-ups and reduce the computational cost is to…

General Relativity and Quantum Cosmology · Physics 2021-03-24 Banafsheh Beheshtipour , Maria Alessandra Papa

This paper constitutes the novel hypergraph convolutional neural networkbased clustering technique. This technique is employed to solve the clustering problem for the Citeseer dataset and the Cora dataset. Each dataset contains the feature…

Machine Learning · Computer Science 2022-09-07 Loc H. Tran , Nguyen Trinh , Linh H. Tran

The role of saturation for cluster formation in finite systems such as atomic nuclei is analyzed by considering three length-scale ratios, and performing deformation-constrained self-consistent mean-field calculations. The effect of…

Nuclear Theory · Physics 2015-06-18 Jean-Paul Ebran , Elias Khan , Tamara Niksic , Dario Vretenar

We consider the scenario of deep clustering, in which the available prior knowledge is limited. In this scenario, few existing state-of-the-art deep clustering methods can perform well for both non-complex topology and complex topology…

Machine Learning · Statistics 2023-03-07 Yuhui Zhang , Yuichiro Wada , Hiroki Waida , Kaito Goto , Yusaku Hino , Takafumi Kanamori

For many next-generation high intensity proton accelerator applications including the Spallation Neutron Source (SNS), superconducting (SC) RF provides the technology of choice for the linac. In designing the superconducting cavity, several…

Accelerator Physics · Physics 2007-05-23 Sang-ho Kim , Marc Doleans , Yoon Kang

AI-enabled precision medicine promises a transformational improvement in healthcare outcomes by enabling data-driven personalized diagnosis, prognosis, and treatment. However, the well-known "curse of dimensionality" and the clustered…

Machine Learning · Computer Science 2023-05-19 Amanda M. Buch , Conor Liston , Logan Grosenick

Spectral clustering is a fundamental technique in the field of data mining and information processing. Most existing spectral clustering algorithms integrate dimensionality reduction into the clustering process assisted by manifold learning…

Machine Learning · Computer Science 2014-11-25 Xiaojun Chang , Feiping Nie , Zhigang Ma , Yi Yang , Xiaofang Zhou

We propose a linear clustering process on a network consisting of two opposite forces: attraction and repulsion between adjacent nodes. Each node is mapped to a position on a one-dimensional line. The attraction and repulsion forces move…

Social and Information Networks · Computer Science 2022-09-26 Ivan Jokić , Piet Van Mieghem

In this paper, we introduce Adaptive Cluster Lasso(ACL) method for variable selection in high dimensional sparse regression models with strongly correlated variables. To handle correlated variables, the concept of clustering or grouping…

Machine Learning · Statistics 2016-03-14 Niharika Gauraha , Swapan K. Parui

Clustering, as an unsupervised technique, plays a pivotal role in various data analysis applications. Among clustering algorithms, Spectral Clustering on Euclidean Spaces has been extensively studied. However, with the rapid evolution of…

Machine Learning · Computer Science 2024-12-09 Sagar Ghosh , Swagatam Das

A high power microwave system based on power combining and pulse compression of conventional klystrons is introduced in this paper. This system mainly consists of pulse modulator, power combiner, driving source of klystrons and pulse…

Accelerator Physics · Physics 2015-12-14 Zheng-Feng Xiong , Huai-Bi Chen , Cheng Cheng , Hui Ning , Chuan-Xiang Tang

In particle accelerators, transverse-longitudinal coupling (TLC) dynamics can be invoked for efficient bunch compression or high harmonic generation when one of the transverse eigenemittance is small. In this sense, complete or partial…

Accelerator Physics · Physics 2023-11-21 Xiujie Deng

Latent class models are widely used for identifying unobserved subgroups from multivariate categorical data in social sciences, with binary data as a particularly popular example. However, accurately recovering individual latent class…

Methodology · Statistics 2026-02-25 Zhongyuan Lyu , Yuqi Gu

In Robust Control and Data Driven Robust Control design methodologies, multiple plant transfer functions or a family of transfer functions are considered and a common controller is designed such that all the plants that fall into this…

Systems and Control · Electrical Eng. & Systems 2023-11-20 Nikhil Potu Surya Prakash , Joohwan Seo , Jongeun Choi , Roberto Horowitz