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We study empirical Bayes (EB) predictive density estimation in linear mixed models (LMMs) with large number of units, which induce a high dimensional random effects space. Focusing on Kullback Leibler (KL) risk minimization, we develop a…

Methodology · Statistics 2026-03-31 Abir Sarkar , Gourab Mukherjee , Keisuke Yano

We address the optimal transmit power allocation problem (from the sensor nodes (SNs) to the fusion center (FC)) for the decentralized detection of an unknown deterministic spatially uncorrelated signal which is being observed by a…

Systems and Control · Computer Science 2015-06-04 Edmond Nurellari , Des McLernon , Mounir Ghogho , Syed Ali Raza Zaidi

The security of quantum cryptography is guaranteed by the no-cloning theorem, which implies that an eavesdropper copying transmitted qubits in unknown states causes their disturbance. Nevertheless, in real cryptographic systems some level…

Quantum Physics · Physics 2013-05-06 Karol Bartkiewicz , Karel Lemr , Antonín Černoch , Jan Soubusta , Adam Miranowicz

This paper investigates the problem of linear spatial collaboration for distributed estimation in wireless sensor networks. In this context, the sensors share their local noisy (and potentially spatially correlated) observations with each…

Information Theory · Computer Science 2016-11-17 Mohammad Fanaei , Matthew C. Valenti , Abbas Jamalipour , Natalia A. Schmid

We consider a multi-stage distributed detection scenario, where $n$ sensors and a fusion center (FC) are deployed to accomplish a binary hypothesis test. At each time stage, local sensors generate binary messages, assumed to be spatially…

Signal Processing · Electrical Eng. & Systems 2023-01-04 Guangyang Zeng , Xiaoqiang Ren , Junfeng Wu

In optical wireless scattering communication, received signal in each symbol interval is captured by a photomultiplier tube (PMT) and then sampled through very short but finite interval sampling. The resulting samples form a signal vector…

Information Theory · Computer Science 2016-12-14 Difan Zou , Chen Gong , Zhengyuan Xu

In this paper, we aim to design and analyze distributed Bayesian estimation algorithms for sensor networks. The challenges we address are to (i) derive a distributed provably-correct algorithm in the functional space of probability…

Machine Learning · Computer Science 2025-03-25 Parth Paritosh , Nikolay Atanasov , Sonia Martinez

We propose and experimentally demonstrate a scheme to render the detection apparatus of a Quantum Key Distribution system immune to the main classes of hacking attacks in which the eavesdropper explores the back-door opened by the…

Distributed detection primarily centers around two approaches: Unquantized Distributed Detection (UDD), where each sensor reports its complete observation to the fusion center (FC), and quantized-and-Coded DD (CDD), where each sensor first…

Information Theory · Computer Science 2023-11-07 Lei Cao , Ramanarayanan Viswanathan

We propose a near-optimum receiver for the discrimination of binary phase-shift-keyed coherent states employing photon-number-resolving detectors. The receiver exploits a discrimination strategy based on both the so-called homodyne-like and…

Quantum Physics · Physics 2023-03-10 Michele N. Notarnicola , Matteo G. A. Paris , Stefano Olivares

This paper considers unmanned aerial vehicle (UAV)-carried intelligent reflecting surface (IRS) for secure data collection in wireless sensor networks. An eavesdropper (Eve) lurks within the vicinity of the main receiver (Bob) while several…

Information Theory · Computer Science 2021-01-19 Christantus O. Nnamani , Muhammad R. A. Khandaker , Mathini Sellathurai

The imperfections of a receiver's detector affect the performance of two-way continuous-variable quantum key distribution protocols and are difficult to adjust in practical situations. We propose a method to improve the performance of…

Quantum Physics · Physics 2014-02-24 Yi-Chen Zhang , Zhengyu Li , Christian Weedbrook , Song Yu , Wanyi Gu , Maozhu Sun , Xiang Peng , Hong Guo

Estimating the Kullback-Leibler (KL) divergence between random variables is a fundamental problem in statistical analysis. For continuous random variables, traditional information-theoretic estimators scale poorly with dimension and/or…

Machine Learning · Computer Science 2025-10-08 Mikil Foss , Andrew Lamperski

This paper develops a systematic approach to realising linear detectors with an optimised sensitivity, allowing for the detection of extremely weak signals. First, general constraints are derived on a specific class of input-output transfer…

Quantum Physics · Physics 2023-01-09 Joe Bentley , Hendra Nurdin , Yanbei Chen , Xiang Li , Haixing Miao

We consider the design of systems for sequential decentralized detection, a problem that entails several interdependent choices: the choice of a stopping rule (specifying the sample size), a global decision function (a choice between two…

Statistics Theory · Mathematics 2016-11-17 XuanLong Nguyen , Martin J. Wainwright , Michael I. Jordan

This work investigates Distributed Detection (DD) in Wireless Sensor Networks (WSNs), where spatially distributed sensors transmit binary decisions over a shared flat-fading channel. To enhance fusion efficiency, a reconfigurable…

Signal Processing · Electrical Eng. & Systems 2026-01-29 Domenico Ciuonzo , Alessio Zappone , Marco Di Renzo , Ciro D'Elia

We consider a decentralized detection problem in a power-constrained wireless sensor networks (WSNs), in which a number of sensor nodes collaborate to detect the presence of a deterministic vector signal. The signal to be detected is…

Information Retrieval · Computer Science 2015-10-28 Jun Fang , Hongbin Li , Zhi Chen , Shaoqian Li

We consider the Bennett-Brassard cryptographic scheme, which uses two conjugate quantum bases. An eavesdropper who attempts to obtain information on qubits sent in one of the bases causes a disturbance to qubits sent in the other basis. We…

Quantum Physics · Physics 2007-05-23 Christopher A. Fuchs , Nicolas Gisin , Robert B. Griffiths , Chi-Sheng Niu , Asher Peres

This paper considers the problem of localising a stationary signal source using a team of mobile agents which only take binary measurements. Background false detection rates and missed detection probabilities are incorporated into the…

Signal Processing · Electrical Eng. & Systems 2018-09-13 Daniel D. Selvaratnam , Iman Shames , Jonathan H. Manton , Branko Ristic

This paper proposes two linear projection methods for supervised dimension reduction using only the first and second-order statistics. The methods, each catering to a different parameter regime, are derived under the general Gaussian model…

Information Theory · Computer Science 2024-08-13 Biao Chen , Joshua Kortje