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Exponential error bounds achievable by universal coding and decoding are derived for frame-asynchronous discrete memoryless %asynchronous multiple access channels with two senders, via the method of subtypes, a refinement of the method of…

Information Theory · Computer Science 2020-02-04 Lóránt Farkas , Tamás Kói

Discrete sampling theorem is formulated that refers to discrete signals specified by a finite number of their samples and band-limited in a domain of a certain orthogonal transform. Conditions of the recoverability of such signals from…

Optics · Physics 2009-02-24 L. Yaroslavsky

In light of the ever-increasing demand for new spectral bands and the underutilization of those already allocated, the concept of Cognitive Radio (CR) has emerged. Opportunistic users could exploit temporarily vacant bands after detecting…

Information Theory · Computer Science 2015-06-17 Deborah Cohen , Yonina C. Eldar

In this article, we propose a design method of selfinterference cancelers for wireless relay stations taking account of the baseband signal subspace. The problem is first formulated as a sampled-data $H^{\infty}$ control problem with a…

Systems and Control · Computer Science 2015-03-27 Hampei Sasahara , Masaaki Nagahara , Kazunori Hayashi , Yutaka Yamamoto

The ubiquitous time-delay estimation (TDE) problem becomes nontrivial when sensors are non-co-located and communication between them is limited. Building on the recently proposed "extremum encoding" compression-estimation scheme, we address…

Signal Processing · Electrical Eng. & Systems 2024-12-25 Amir Weiss , Yuval Kochman , Gregory W. Wornell

This work considers distributed sensing and transmission of sporadic random samples. Lower bounds are derived for the reconstruction error of a single normally or uniformly-distributed finite-dimensional vector imperfectly measured by a…

Information Theory · Computer Science 2015-11-20 Ayşe Ünsal , Raymond Knopp

We consider the problem of frequency estimation for a single bosonic field evolving under a squeezing Hamiltonian and continuously monitored via homodyne detection. In particular, we exploit reinforcement learning techniques to devise…

Quantum Physics · Physics 2022-04-19 Alessio Fallani , Matteo A. C. Rossi , Dario Tamascelli , Marco G. Genoni

We investigate the problem of a monostatic pulse-Doppler radar transceiver trying to detect targets, sparsely populated in the radar's unambiguous time-frequency region. Several past works employ compressed sensing (CS) algorithms to this…

Information Theory · Computer Science 2013-09-24 Omer Bar-Ilan , Yonina C. Eldar

Frequency estimation of multiple sinusoids is significant in both theory and application. In some application scenarios, only sub-Nyquist samples are available to estimate the frequencies. A conventional approach is to sample the signals at…

Information Theory · Computer Science 2017-03-21 Shan Huang , Haijian Zhang , Hong Sun , Lei Yu , Liwen Chen

This paper addresses a fundamental and important question in control: under what conditions does there fail to exist a robust control policy that keeps the state of a constrained linear system within a target set, despite bounded…

Systems and Control · Electrical Eng. & Systems 2025-07-08 Paul Trodden , José M. Maestre , Hideaki Ishii

Optimal sampled-data control of a nonlinear system is considered with the stable-manifold approach and extensive use of numerical techniques. The idea is to notice the Hamiltonian system associated with the considered optimal control…

Systems and Control · Electrical Eng. & Systems 2021-12-30 Yasuaki Oishi , Noboru Sakamoto

This paper proposes an output feedback controller capable of ensuring steady-state offset-free tracking for ramp and sinusoidal reference signals while ensuring local stability and state and input constraints fulfillment. The proposed…

Optimization and Control · Mathematics 2024-03-18 Geovana Franca dos Santos , Eugenio B. Castelan , Walter Lucia

We present a robust data-driven control scheme for an unknown linear system model with bounded process and measurement noise. Instead of depending on a system model in traditional predictive control, a controller utilizing data-driven…

Systems and Control · Electrical Eng. & Systems 2022-07-14 Amr Alanwar , Yvonne Stürz , Karl Henrik Johansson

We study the stabilization of networked control systems with asynchronous sensors and controllers. Offsets between the sensor and controller clocks are unknown and modeled as parametric uncertainty. First we consider multi-input linear…

Systems and Control · Computer Science 2017-03-02 Masashi Wakaiki , Kunihisa Okano , Joao P. Hespanha

Zero-Shot Super-Resolution Spatiotemporal Forecasting requires a deep learning model to be trained on low-resolution data and deployed for inference on high-resolution. Existing studies consider maintaining similar error across different…

Computer Vision and Pattern Recognition · Computer Science 2026-02-10 Wenshuo Wang , Fan Zhang

This paper addresses the challenge of efficiently capturing a high proportion of true signals for subsequent data analyses when sample sizes are relatively limited with respect to data dimension. We propose the signal missing rate as a new…

Methodology · Statistics 2018-08-30 X. Jessie Jeng , Teng Zhang , Jung-Ying Tzeng

This paper introduces a control strategy to simultaneously achieve asymptotic stabilization and transient frequency regulation of power networks. The control command is generated by iteratively solving an open-loop control cost minimization…

Systems and Control · Electrical Eng. & Systems 2019-11-13 Yifu Zhang , Jorge Cortes

We introduce general results on well-posedness and output regulation of regular linear systems with nonautonomous controllers. We present a generalization of the internal model principle for time-dependent controllers with asymptotically…

Optimization and Control · Mathematics 2022-04-12 Lassi Paunonen , Sepideh Afshar

A common goal in the control of a large network is to minimize the number of driver nodes or control inputs. Yet, the physical determination of control signals and the properties of the resulting control trajectories remain widely…

Disordered Systems and Neural Networks · Physics 2013-05-28 Jie Sun , Adilson E. Motter

We present a general control-theoretic framework for constructing and analyzing random decoupling schemes, applicable to quantum dynamical control of arbitrary finite-dimensional composite systems. The basic idea is to design the control…

Quantum Physics · Physics 2009-11-11 Lorenza Viola , Emanuel Knill