相关论文: Hidden Markov model tracking of continuous gravita…

Data sets comprised of sequences of curves sampled at high frequencies in time are increasingly common in practice, but they can exhibit complicated dependence structures that cannot be modelled using common methods of Functional Data…

Hidden Markov models (HMMs) are probabilistic methods in which observations are seen as realizations of a latent Markov process with discrete states that switch over time. Moving beyond standard statistical tests, HMMs offer a statistical…

With the symbolic framework of Probability Bracket Notation (PBN), the Markov Sequence Projector (MSP) is introduced to expand the evolution formula of Homogeneous Markov Chains (HMCs). The well-known weather example, a Visible Markov Model…

We describe a new pipeline used to analyze the data from the fifth science run (S5) of the LIGO detectors to search for continuous gravitational waves from isolated spinning neutron stars. The method employed is based on the Hough…

Suppose that we are given a time series where consecutive samples are believed to come from a probabilistic source, that the source changes from time to time and that the total number of sources is fixed. Our objective is to estimate the…

The canonical signal model in continuous gravitational wave searches is deterministic, and stable over the long integration times needed to separate a putative signal from the noise, e.g. with a matched filter. However, there exist…

Electric arc welding (EAW) exhibits strongly non stationary and temporally evolving behavior, making reliable assessment of arc stability difficult using conventional frame based approaches. In this study, arc dynamics are modeled as a…

Within the next decade gravitational-wave (GW) observations by Advanced LIGO in the United States, Advanced Virgo and GEO HF in Europe, and possibly other ground-based instruments will provide unprecedented opportunities to look directly…

Gravitational waves modulate the apparent frequencies of other periodic signals. Low-frequency gravitational waves could therefore be detected by observing frequency modulations in signals from higher-frequency sources, e.g., those from…

Periodic (almost monochromatic) gravitational waves emitted by rotating, asymmetric neutron stars are intriguing potential signals in the sensitivity band of Advanced LIGO and Advanced Virgo detectors. These signals are related to elastic…

Continuous gravitational waves from spinning deformed neutron stars have not been detected yet, and are one of the most promising signals for future detection. All-sky searches for continuous gravitational waves from unknown neutron stars…

This paper presents a new and flexible prognostics framework based on a higher order hidden semi-Markov model (HOHSMM) for systems or components with unobservable health states and complex transition dynamics. The HOHSMM extends the basic…

Seven years after the first direct detection of gravitational waves, from the collision of two black holes, the field of gravitational wave astronomy is firmly established. A first detection of continuous gravitational waves from…

The paper investigates the problems of quickest change detection in Markov models and hidden Markov models (HMMs). Sequential observations are taken from a (hidden) Markov model. At some unknown time, an event occurs in the system and…

As deep neural networks continue to revolutionize various application domains, there is increasing interest in making these powerful models more understandable and interpretable, and narrowing down the causes of good and bad predictions. We…

Sco X-1, the brightest low mass X-ray binary, is likely to be a source for gravitational wave emission. In one mechanism, emission of a gravitational wave arrests the increase in spin frequency due to the accretion torque in a low mass…

Continuous gravitational waves, i.e., persistent and nearly-monochromatic signals emitted by asymmetric spinning neutron stars, remain elusive. Searches for these signals from unknown binary systems are the most computationally challenging,…

The Hidden Markov Model (HMM) can predict the future value of a time series based on its current and previous values, making it a powerful algorithm for handling various types of time series. Numerous studies have explored the improvement…

We develop the analytic and numerical tools for data analysis of the gravitational-wave signals from spinning neutron stars for ground-based laser interferometric detectors. We study in detail the statistical properties of the optimum…

In this paper, we consider the filtering and smoothing recursions in nonparametric finite state space hidden Markov models (HMMs) when the parameters of the model are unknown and replaced by estimators. We provide an explicit and time…