Copula-based CUSUM charts for monitoring infectious disease using Markovian Poisson processes
The manuscript addresses the copula-based CUSUM charting scheme to monitor infectious
disease. To facilitate the disease surveillance, the Poisson distribution is often used to …
disease. To facilitate the disease surveillance, the Poisson distribution is often used to …
Multiple change points detection in low rank and sparse high dimensional vector autoregressive models
Identifying change/break points in multivariate time series represents a canonical problem in
signal processing, due to numerous applications related to anomaly detection problems …
signal processing, due to numerous applications related to anomaly detection problems …
Bayesian nonparametric hidden Markov model for agile radar pulse sequences streaming analysis
Multi-function radars are sophisticated types of sensors with the capabilities of complex agile
inter-pulse modulation implementation and dynamic work mode scheduling. The …
inter-pulse modulation implementation and dynamic work mode scheduling. The …
Asymptotic Bayesian theory of quickest change detection for hidden Markov models
CD Fuh, AG Tartakovsky - IEEE Transactions on Information …, 2018 - ieeexplore.ieee.org
In the 1960s, Shiryaev developed a Bayesian theory of change-point detection in the iid
case, which was generalized in the early 2000s by Tartakovsky and Veeravalli and recently …
case, which was generalized in the early 2000s by Tartakovsky and Veeravalli and recently …
Scalable sum-shrinkage schemes for distributed monitoring large-scale data streams
In this article, we investigate the problem of monitoring independent large-scale data
streams where an undesired event may occur at some unknown time and affect only a few …
streams where an undesired event may occur at some unknown time and affect only a few …
Sequential algorithms for moving anomaly detection in networks
The problem of quickest moving anomaly detection in networks is studied. Initially, the
observations are generated according to a prechange distribution. At some unknown but …
observations are generated according to a prechange distribution. At some unknown but …
Fundamental limits for learning hidden Markov model parameters
K Abraham, E Gassiat, Z Naulet - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
We study the frontier between learnable and unlearnable hidden Markov models (HMMs).
HMMs are flexible tools for clustering dependent data coming from unknown populations …
HMMs are flexible tools for clustering dependent data coming from unknown populations …
Misspecified and asymptotically minimax robust quickest change detection
We investigate the quickest detection of an unknown change in the distribution of a
stochastic process generating independent and identically distributed observations. We …
stochastic process generating independent and identically distributed observations. We …
Moving point target detection based on higher order statistics in very low SNR
W Niu, W Zheng, Z Yang, Y Wu… - IEEE Geoscience and …, 2017 - ieeexplore.ieee.org
This letter presents an approach for the detection of moving point targets on high-frame-rate
image sequences with low spatial resolution and low SNR based on higher order statistical …
image sequences with low spatial resolution and low SNR based on higher order statistical …
Data-driven quickest change detection in hidden Markov models
The problem of quickest change detection in hidden Markov models (HMMs) is investigated.
A sequence of samples are generated from a HMM, and at some unknown time, the …
A sequence of samples are generated from a HMM, and at some unknown time, the …