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In this paper, the bit error performance of a family of likelihood ascent search (LAS) multiuser detectors is analyzed. An upper bound on the BER of any LAS detector is obtained by bounding the fixed point region with the worst initial…

Information Theory · Computer Science 2016-11-15 Yi Sun

Automated experiments in scanning transmission electron microscopy (STEM) require rapid image segmentation to optimize data representation for human interpretation, decision-making, site-selective spectroscopies, and atomic manipulation.…

Materials Science · Physics 2024-09-23 Kamyar Barakati , Utkarsh Pratiush , Austin C. Houston , Gerd Duscher , Sergei V. Kalinin

Model error covariances play a central role in the performance of data assimilation methods applied to nonlinear state-space models. However, these covariances are largely unknown in most of the applications. A misspecification of the model…

Computation · Statistics 2019-11-06 María Magdalena Lucini , Peter Jan van Leeuwen , Manuel Pulido

Recent developments in system identification have brought attention to regularized kernel-based methods. This type of approach has been proven to compare favorably with classic parametric methods. However, current formulations are not…

Systems and Control · Computer Science 2016-11-25 Giulio Bottegal , Aleksandr Y. Aravkin , Håkan Hjalmarsson , Gianluigi Pillonetto

Simultaneous multiuser beamforming in multiantenna downlink channels can entail dirty paper (DP) precoding (optimal and high complexity) or linear precoding (suboptimal and low complexity) approaches. The system performance is typically…

Information Theory · Computer Science 2013-07-22 Serdar Ozyurt , Murat Torlak

Expectation Propagation (EP) is a widely used iterative message-passing algorithm that decomposes a global inference problem into multiple local ones. It approximates marginal distributions as ``beliefs'' using intermediate functions called…

Machine Learning · Statistics 2026-04-07 Zilu Zhao , Jichao Chen , Dirk Slock

In this paper we consider the estimation of unknown parameters in Bayesian inverse problems. In most cases of practical interest, there are several barriers to performing such estimation, This includes a numerical approximation of a…

Methodology · Statistics 2025-02-07 Neil K. Chada , Ajay Jasra , Mohamed Maama , Raul Tempone

Transmission electron microscopes (TEMs) enable atomic-scale imaging but suffer from aberrations caused by lens imperfections and environmental conditions, reducing image quality. These aberrations can be compensated by adjusting…

Systems and Control · Electrical Eng. & Systems 2026-04-20 Jilles S. van Hulst , Erik M. Franken , Bart J. Janssen , W. P. M. H. Heemels , Duarte J. Antunes

Non-data-aided (NDA) parameter estimation is considered for binary-phase-shift-keying transmission in an additive white Gaussian noise channel. Cramer-Rao lower bounds (CRLBs) for signal amplitude, noise variance, channel reliability…

Information Theory · Computer Science 2007-07-13 Fredrik Brannstrom , Lars K. Rasmussen

In this paper, we propose a new combined message passing algorithm which allows belief propagation (BP) and mean filed (MF) applied on a same factor node, so that MF can be applied to hard constraint factors. Based on the proposed message…

Information Theory · Computer Science 2017-01-24 Chuanzong Zhang , Zhengdao Yuan , Zhongyong Wang , Qinghua Guo

The kernel-based regularization method has two core issues: kernel design and hyperparameter estimation. In this paper, we focus on the second issue and study the properties of several hyperparameter estimators including the empirical Bayes…

Systems and Control · Computer Science 2017-07-04 Biqiang Mu , Tianshi Chen , Lennart Ljung

Small area estimators that ignore the sampling design lack design consistency when the sampling mechanism is complex and may be severely biased under informative designs. Existing procedures that account for the survey weights under…

Methodology · Statistics 2026-03-12 William Acero , Domingo Morales , Isabel Molina

In this paper, we consider a partial deconvolution kernel estimator for nonparametric regression when some covariates are measured with error while others are observed without error. We focus on a general and realistic setting in which the…

Statistics Theory · Mathematics 2026-01-29 Baba Thiam

Estimating the score, i.e., the gradient of log density function, from a set of samples generated by an unknown distribution is a fundamental task in inference and learning of probabilistic models that involve flexible yet intractable…

Machine Learning · Statistics 2020-07-01 Yuhao Zhou , Jiaxin Shi , Jun Zhu

This paper introduces a data-adaptive non-parametric approach for the estimation of time-varying spectral densities from nonstationary time series. Time-varying spectral densities are commonly estimated by local kernel smoothing. The…

Computation · Statistics 2020-07-21 Anne van Delft , Michael Eichler

Overcoming the conventional trade-off between throughput and bit error rate (BER) performance, versus computational complexity is a long-term challenge for uplink Multiple-Input Multiple-Output (MIMO) detection in base station design for…

Networking and Internet Architecture · Computer Science 2021-03-22 Minsung Kim , Salvatore Mandrà , Davide Venturelli , Kyle Jamieson

The rapid development of the mobile communications requires ever higher spectral efficiency. The non-orthogonal multiple access (NOMA) has emerged as a promising technology to further increase the access efficiency of wireless networks.…

Information Theory · Computer Science 2017-10-25 Weijie Yuan , Nan Wu , Qinghua Guo , Yonghui Li , Chengwen Xing , Jingming Kuang

The traditional kernel density estimator of an unknown density is by construction completely nonparametric, in the sense that it has no preferences and will work reasonably well for all shapes. The present paper develops a class of…

Methodology · Statistics 2026-05-05 Nils Lid Hjort , Ingrid Kristine Glad

This paper proposes a novel non-orthogonal affine frequency division multiplexing (nAFDM) waveform for reliable high-mobility communications with enhanced spectral efficiency (SE). The key idea is to introduce a bandwidth compression factor…

Information Theory · Computer Science 2026-02-17 Qin Yi , Zilong Liu , Leila Musavian , Zeping Sui

We present a generic approximation of the packet error rate (PER) function of uncoded schemes in the AWGN channel using extreme value theory (EVT). The PER function can assume both the exponential and the Gaussian Q-function bit error rate…

Information Theory · Computer Science 2016-10-19 Aamir Mahmood , Riku Jäntti
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