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As phasor measurement units (PMUs) become more widely used in transmission power systems, a fast state estimation (SE) algorithm that can take advantage of their high sample rates is needed. To accomplish this, we present a method that uses…

Machine Learning · Computer Science 2026-03-09 Ognjen Kundacina , Mirsad Cosovic , Dragisa Miskovic , Dejan Vukobratovic

This paper considers a low-complexity Gaussian Message Passing (GMP) scheme for a coded massive Multiple-Input Multiple-Output (MIMO) systems with Non-Orthogonal Multiple Access (massive MIMO-NOMA), in which a base station with $N_s$…

Information Theory · Computer Science 2018-10-26 Lei Liu , Chau Yuen , Yong Liang Guan , Ying Li , Chongwen Huang

Estimation of a vector from quantized linear measurements is a common problem for which simple linear techniques are suboptimal -- sometimes greatly so. This paper develops generalized approximate message passing (GAMP) algorithms for…

Information Theory · Computer Science 2015-03-24 Ulugbek Kamilov , Vivek K. Goyal , Sundeep Rangan

In a recent article (Proc. Natl. Acad. Sci., 110(36), 14557-14562), El Karoui et al. study the distribution of robust regression estimators in the regime in which the number of parameters p is of the same order as the number of samples n.…

Statistics Theory · Mathematics 2013-11-18 David Donoho , Andrea Montanari

This paper presents an information-theoretic approach to address the phasor measurement unit (PMU) placement problem in electric power systems. Different from the conventional 'topological observability' based approaches, this paper…

Optimization and Control · Mathematics 2012-01-16 Qiao Li , Tao Cui , Yang Weng , Rohit Negi , Franz Franchetti , Marija D. Ilic

We consider the estimation of an i.i.d.\ random vector observed through a linear transform followed by a componentwise, probabilistic (possibly nonlinear) measurement channel. A novel algorithm, called generalized approximate message…

Information Theory · Computer Science 2012-08-15 Sundeep Rangan

In this paper, a novel linear algorithm is proposed for state estimation including bad data detection of power systems that are monitored both by conventional and synchrophasor measurements. Both types of data are treated simultaneously and…

Systems and Control · Electrical Eng. & Systems 2020-01-30 Aleksandar Jovicic , Gabriela Hug

Real-time transmission line outage detection is difficult because of partial phasor measurement unit (PMU) deployment and varying outage signal strength. Existing detection approaches focus on monitoring PMU-measured nodal algebraic states,…

Systems and Control · Electrical Eng. & Systems 2021-10-28 Xiaozhou Yang , Nan Chen , Chao Zhai

Phasor Measurement Units (PMUs) convert high-speed waveform data into low-speed phasor data, which are fundamental to wide-area monitoring and control in power systems, with oscillation detection and localization among their most prominent…

Signal Processing · Electrical Eng. & Systems 2026-01-23 Bowen Ou , Bin Wang , Slava Maslennikov , Hanchao Liu , Jim Follum

We propose simple protocols for performing quantum noise spectroscopy based on the method of transfer tensor maps (TTM), [Phys. Rev. Lett. 112, 110401 (2014)]. The TTM approach is a systematic way to deduce the memory kernel of a…

Quantum Physics · Physics 2019-05-29 Yu-Qin Chen , Kai-Li Ma , Yi-Cong Zheng , Jonathan Allcock , Shengyu Zhang , Chang-Yu Hsieh

The impact of Phasor Measurement Units (PMUs) for providing situational awareness to transmission system operators has been widely documented. Micro-PMUs ($\mu$PMUs) are an emerging sensing technology that can provide similar benefits to…

Systems and Control · Computer Science 2016-10-05 Mahdi Jamei , Anna Scaglione , Ciaran Roberts , Emma Stewart , Sean Peisert , Chuck McParland , Alex McEachern

Sparsity-based tensor recovery methods have shown great potential in suppressing seismic data noise. These methods exploit tensor sparsity measures capturing the low-dimensional structures inherent in seismic data tensors to remove noise by…

Computer Vision and Pattern Recognition · Computer Science 2025-02-21 Sirui Pan , Zhiyuan Zha , Shigang Wang , Yue Li , Zipei Fan , Gang Yan , Binh T. Nguyen , Bihan Wen , Ce Zhu

This paper extends the idea of the Thevenin equivalent into unbalanced 3{\phi} circuits and proposes a 3{\phi} long-term voltage stability indicator (VSI), that can identify critical loads in a system. Furthermore, in order to identify…

Optimization and Control · Mathematics 2020-01-23 Amarsagar Reddy Ramapuram Matavalam , Ankit Singhal , Venkataramana Ajjarapu

We consider the task of estimating a low-rank matrix from non-linear and noisy observations. We prove a strong universality result showing that Bayes-optimal performances are characterized by an equivalent Gaussian model with an effective…

Machine Learning · Statistics 2024-03-08 Pierre Mergny , Justin Ko , Florent Krzakala , Lenka Zdeborová

We address the problem of signal denoising via transform-domain shrinkage based on a novel $\textit{risk}$ criterion called the minimum probability of error (MPE), which measures the probability that the estimated parameter lies outside an…

Applications · Statistics 2020-02-19 Jishnu Sadasivan , Subhadip Mukherjee , Chandra Sekhar Seelamantula

The generalized approximate message passing (GAMP) algorithm under the Bayesian setting shows advantage in recovering under-sampled sparse signals from corrupted observations. Compared to conventional convex optimization methods, it has a…

Information Theory · Computer Science 2017-01-12 Shuai Huang , Trac D. Tran

Compressed sensing is a signal processing technique in which data is acquired directly in a compressed form. There are two modeling approaches that can be considered: the worst-case (Hamming) approach and a statistical mechanism, in which…

Information Theory · Computer Science 2016-01-20 Wasim Huleihel , Neri Merhav

Additive asynchronous and cyclostationary impulsive noise limits communication performance in OFDM powerline communication (PLC) systems. Conventional OFDM receivers assume additive white Gaussian noise and hence experience degradation in…

Machine Learning · Statistics 2016-11-18 Jing Lin , Marcel Nassar , Brian L. Evans

An abstraction for multisensor communication termed the Gaussian Multiplex Channel is presented and analyzed. In this model, the sensor outputs can be added together in any combination through a network of switches, and the combinations can…

Signal Processing · Electrical Eng. & Systems 2024-12-20 Daniel R. Fuhrmann , Muhammad Fahad

Generalized Vector Approximate Message Passing (GVAMP) is an efficient iterative algorithm for approximately minimum-mean-squared-error estimation of a random vector $\mathbf{x}\sim p_{\mathbf{x}}(\mathbf{x})$ from generalized linear…

Information Theory · Computer Science 2018-06-27 Christopher A. Metzler , Philip Schniter , Richard G. Baraniuk
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