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A method for constructing sets of sequences with zero-correlation zone (ZCZ sequences) and sequence sets with low cross correlation is proposed. The method is to use families of short sequences and complete orthogonal sequence sets to…

Information Theory · Computer Science 2007-07-13 Xiangyong Zeng , Lei Hu , Qingchong Liu

This work aims at the development of signal processing algorithms that can explore the potential of a PICOSEC-MicroMegas detector and offers the ability for online, precise timing. The PICOSEC-MicroMegas detector is a novel gaseous detector…

Instrumentation and Detectors · Physics 2021-12-30 Alexandra Kallitsopoulou

Interpolation is responsible for digital signal resampling and can significantly degrade the original signal quality if not done properly. For many years, optimal interpolation algorithms were sought within constrained classes of…

Computer Vision and Pattern Recognition · Computer Science 2011-04-23 Oleg S. Pianykh

Cross-correlation is a popular signal processing technique used in numerous location tracking systems for obtaining reliable range information. However, its efficient design and practical implementation has not yet been achieved on mote…

Other Computer Science · Computer Science 2016-06-14 Prasant Misra , Wen Hu , Mingrui Yang , Marco Duarte , Sanjay Jha

Intelligent metasurfaces are one of the favorite technologies for integrating sixth-generation (6G) networks, especially the reconfigurable intelligent surface (RIS) that has been extensively researched in various applications. In this…

Signal Processing · Electrical Eng. & Systems 2024-01-09 Herman L. dos Santos , Martin Voigt Vejling , Taufik Abrão , Petar Popovski

A novel time calibration method for waveform sampling application specific integrated circuits (ASICs) based on switched capacitor arrays (SCAs) is proposed in this paper. Precision timing extraction using SCA ASICs has been proved to be a…

Instrumentation and Detectors · Physics 2019-07-10 Boyu Cheng , Lei Zhao , Jiajun Qin , Han Chen , Yuxiang Guo , Shubin Liu , Qi An

Supervised learning with irregularly sampled time series have been a challenge to Machine Learning methods due to the obstacle of dealing with irregular time intervals. Some papers introduced recently recurrent neural network models that…

Machine Learning · Computer Science 2020-03-23 Rafael T. Sousa , Lucas A. Pereira , Anderson S. Soares

Continual self-supervised learning (CSSL) methods have gained increasing attention in remote sensing (RS) due to their capability to learn new tasks sequentially from continuous streams of unlabeled data. Existing CSSL methods, while…

Computer Vision and Pattern Recognition · Computer Science 2025-05-19 Lars Möllenbrok , Behnood Rasti , Begüm Demir

Spatial sampling is traditionally studied in a static setting where static sensors scattered around space take measurements of the spatial field at their locations. In this paper we study the emerging paradigm of sampling and reconstructing…

Multimedia · Computer Science 2015-06-12 Jayakrishnan Unnikrishnan , Martin Vetterli

The Gillespie algorithm provides statistically exact methods for simulating stochastic dynamics modelled as interacting sequences of discrete events including systems of biochemical reactions or earthquake occurrences, networks of queuing…

Physics and Society · Physics 2020-02-20 Naoki Masuda , Luis E. C. Rocha

Efficient sampling of many-dimensional and multimodal density functions is a task of great interest in many research fields. We describe an algorithm that allows parallelizing inherently serial Markov chain Monte Carlo (MCMC) sampling by…

Computation · Statistics 2020-08-10 Vasyl Hafych , Philipp Eller , Oliver Schulz , Allen Caldwell

We investigate and report an experimental confirmation of zero-lag synchronization (ZLS) in a system of three coupled time-delayed piecewise linear electronic circuits via dynamical relaying with different coupling configurations, namely…

Chaotic Dynamics · Physics 2015-06-12 R. Suresh , K. Srinivasan , D. V. Senthilkumar , I. Raja Mohamed , K. Murali , M. Lakshmanan , J. Kurths

In this paper, we consider (random) sampling of signals concentrated on a bounded Corkscrew domain $\Omega$ of a metric measure space, and reconstructing concentrated signals approximately from their (un)corrupted sampling data taken on a…

Information Theory · Computer Science 2020-06-18 Yaxu Li , Qiyu Sun , Jun Xian

We study the problem of finding efficient sampling policies in an edge-based feedback system, where sensor samples are offloaded to a back-end server that processes them and generates feedback to a user. Sampling the system at maximum…

Information Theory · Computer Science 2023-02-07 Vishnu Narayanan Moothedath , Jaya Prakash Champati , James Gross

We present a simple yet novel time series imputation technique with the goal of constructing an irregular time series that is uniform across every sample in a data set. Specifically, we fix a grid defined by the midpoints of non-overlapping…

Machine Learning · Computer Science 2022-01-19 Andrew Baumgartner , Sevda Molani , Qi Wei , Jennifer Hadlock

Shapelets that discriminate time series using local features (subsequences) are promising for time series clustering. Existing time series clustering methods may fail to capture representative shapelets because they discover shapelets from…

Machine Learning · Computer Science 2023-11-16 Borui Cai , Guangyan Huang , Shuiqiao Yang , Yong Xiang , Chi-Hung Chi

Wireless control systems (WCSs) often have to operate in dynamic environments where the network traffic load may vary unpredictably over time. The sampling in sensors is conventionally time triggered with fixed periods. In this context,…

Networking and Internet Architecture · Computer Science 2008-12-18 Feng Xia , Wenhong Zhao

In this note we study the problem of sampling and reconstructing signals which are assumed to lie on or close to one of several subspaces of a Hilbert space. Importantly, we here consider a very general setting in which we allow infinitely…

Information Theory · Computer Science 2009-12-02 Thomas Blumensath

The time series captured by a single scalp electrode (plus the reference electrode) of refractory epileptic patients is used to forecast seizures susceptibility. The time series is preprocessed, segmented, and each segment transformed into…

Machine Learning · Computer Science 2022-06-30 Tiago Leal , Antonio Dourado , Fabio Lopes , Cesar Teixeira

This paper is concerned with high-order numerical methods for hyperbolic systems of balance laws. Such methods are typically based on high-order piecewise polynomial reconstructions (interpolations) of the computed discrete quantities.…

Numerical Analysis · Mathematics 2025-07-28 Shaoshuai Chu , Alexander Kurganov , Mingye Na , Bao Shan Wang , Ruixiao Xin
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