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Passive filtering is a common strategy used to reduce airborne disease transmission and particulate contaminants in buildings and individual covers. The engineering of high-performance filters with relatively low flow resistance but high…

Collaborative filtering is one of the most used approaches for providing recommendations in various online environments. Even though collaborative recommendation methods have been widely utilized due to their simplicity and ease of use,…

Information Retrieval · Computer Science 2018-04-25 Nikolaos Polatidis , Christos K. Georgiadis

We propose a systematic design of protograph-based quasi-cyclic (QC) low-density parity-check (LDPC) codes with low error floor. We first characterize the trapping sets of such codes and demonstrate that the QC structure of the code…

Information Theory · Computer Science 2019-06-18 Bashirreza Karimi , Amir. H Banihashemi

Cell-free massive MIMO systems consist of many distributed access points with simple components that jointly serve the users. In millimeter wave bands, only a limited set of predetermined beams can be supported. In a network that…

Information Theory · Computer Science 2021-07-05 Cenk M. Yetis , Emil Björnson , Pontus Giselsson

In this work, we propose a class of spline-like wavelet filterbanks for graph signals. These filterbanks possess the properties of critical sampling and perfect reconstruction. Besides, the analysis filters are localized in the graph domain…

Signal Processing · Electrical Eng. & Systems 2024-10-28 Junxia You , Lihua Yang

In this paper, we study the scheduling problem for downlink transmission in a multi-channel (e.g., OFDM-based) wireless network. We focus on a single cell, with the aim of developing a unifying framework for designing low-complexity…

Networking and Internet Architecture · Computer Science 2013-11-19 Bo Ji , Gagan R. Gupta , Xiaojun Lin , Ness B. Shroff

A composite likelihood is a combination of low-dimensional likelihood objects useful in applications where the data have complex structure. Although composite likelihood construction is a crucial aspect influencing both computing and…

Methodology · Statistics 2022-04-26 Zhendong Huang , Davide Ferrari

Real bipartite networks combine degree-constrained random mixing with structured, locality-like rules. We introduce a statistical filter that benchmarks node-level bipartite clustering against degree-preserving randomizations to classify…

Physics and Society · Physics 2025-09-27 Lucía S. Ramírez , Roya Aliakbarisani , M. Ángeles Serrano , Marián Boguñá

This paper proposes a blind detection problem for low pass graph signals. Without assuming knowledge of the exact graph topology, we aim to detect if a set of graph signal observations are generated from a low pass graph filter. Our problem…

Signal Processing · Electrical Eng. & Systems 2024-06-24 Chenyue Zhang , Yiran He , Hoi-To Wai

It is often difficult to correctly implement a Boolean controller for a complex system, especially when concurrency is involved. Yet, it may be easy to formally specify a controller. For instance, for a pipelined processor it suffices to…

Logic in Computer Science · Computer Science 2013-08-23 Georg Hofferek , Ashutosh Gupta , Bettina Könighofer , Jie-Hong Roland Jiang , Roderick Bloem

This paper proposes a class of $M$-channel spectral graph filter banks with a symmetric structure, that is, the transform has sampling operations and spectral graph filters on both the analysis and synthesis sides. The filter banks achieve…

Signal Processing · Electrical Eng. & Systems 2019-05-01 Akie Sakiyama , Kana Watanabe , Yuichi Tanaka

Citizens' assemblies need to represent subpopulations according to their proportions in the general population. These large committees are often constructed in an online fashion by contacting people, asking for the demographic features of…

Artificial Intelligence · Computer Science 2021-12-06 Virginie Do , Jamal Atif , Jérôme Lang , Nicolas Usunier

Networks (or graphs) are used to model the dyadic relations between entities in a complex system. In cases where there exists multiple relations between the entities, the complex system can be represented as a multilayer network, where the…

Social and Information Networks · Computer Science 2019-10-04 Abhishek Santra , Sanjukta Bhowmick , Sharma Chakravarthy

Modeling an unknown dynamical system is crucial in order to predict the future behavior of the system. A standard approach is training recurrent models on measurement data. While these models typically provide exact short-term predictions,…

Machine Learning · Computer Science 2023-03-02 Katharina Ensinger , Sebastian Ziesche , Barbara Rakitsch , Michael Tiemann , Sebastian Trimpe

A multiparameter filtration, or a multifiltration, may in many cases be seen as the collection of sublevel sets of a vector function, which we call a multifiltering function. The main objective of this paper is to obtain a better…

Geometric Topology · Mathematics 2026-01-01 Guillaume Brouillette

In this paper, a new filter model called set-membership Kalman filter for nonlinear state estimation problems was designed, where both random and unknown but bounded uncertainties were considered simultaneously in the discrete-time system.…

Optimization and Control · Mathematics 2018-02-09 Ligang Sun , Hamza Alkhatib , Boris Kargoll , Vladik Kreinovich , Ingo Neumann

A stepped-impedance low-pass filter with integrated hollow waveguide absorbers is presented. The filter combines low insertion loss in the passband with strong attenuation at high frequencies, making it well suited for superconducting…

Quantum Physics · Physics 2026-01-08 Linus Andersson , Benjamin Olsson , Simone Gasparinetti , Robert Rehammar

Fibres shed from our clothes during a washing machine cycle constitute around 35% of the primary microplastics in our oceans. Current conventional dead-end washing machine filters clog relatively quickly and require frequent cleaning. We…

Fluid Dynamics · Physics 2026-04-13 T. Fastnedge , C. J. W. Breward , I. M. Griffiths

Many multi-object estimation problems require additional estimation of model or sensor parameters that are either common to all objects or related to unknown characterisation of one or more sensors. Important examples of these include…

Statistics Theory · Mathematics 2017-05-16 Isabel Schlangen , Daniel E. Clark , Emmanuel D. Delande

Recommender systems often rely on graph-based filters, such as normalized item-item adjacency matrices and low-pass filters. While effective, the centralized computation of these components raises concerns about privacy, security, and the…

Information Retrieval · Computer Science 2025-01-29 Julien Nicolas , César Sabater , Mohamed Maouche , Sonia Ben Mokhtar , Mark Coates