Search results for "Markov"

Learning From Errors: Detecting Cross-Technology Interference in WiFi Networks

2018

In this paper, we show that inter-technology interference can be recognized using commodity WiFi devices by monitoring the statistics of receiver errors. Indeed, while for WiFi standard frames the error probability varies during the frame reception in different frame fields (PHY, MAC headers, and payloads) protected with heterogeneous coding, errors may appear randomly at any point during the time the demodulator is trying to receive an exogenous interfering signal. We thus detect and identify cross-technology interference on off-the-shelf WiFi cards by monitoring the sequence of receiver errors (bad PLCP, bad FCS, invalid headers, etc.) and propose two methods to recognize the source of in…

Importance sampling type estimators based on approximate marginal Markov chain Monte Carlo

2020

We consider importance sampling (IS) type weighted estimators based on Markov chain Monte Carlo (MCMC) targeting an approximate marginal of the target distribution. In the context of Bayesian latent variable models, the MCMC typically operates on the hyperparameters, and the subsequent weighting may be based on IS or sequential Monte Carlo (SMC), but allows for multilevel techniques as well. The IS approach provides a natural alternative to delayed acceptance (DA) pseudo-marginal/particle MCMC, and has many advantages over DA, including a straightforward parallelisation and additional flexibility in MCMC implementation. We detail minimal conditions which ensure strong consistency of the sug…

Yliopistotutkintojen määrän ennustaminen Bayes-mallilla

2017

Tämän tutkielman tarkoituksena on kehittää prediktiivinen malli, jolla ennustetaan Jyväskylän yliopiston matemaattis-luonnontieteellisessä tiedekunnassa lähivuosina suoritettavien luonnontieteiden kandidaatin ja filosofian maisterin tutkintojen lukumääriä. Mallin estimointiin käytettävä aineisto koostuu kolmesta osasta: vuosina 1996–2004 tiedekunnassa aloittaneet opiskelijat, vuosina 2005–2015 tiedekunnassa alemmasta korkeakoulututkinnosta aloittaneet opiskelijat ja vuosina 2005–2016 tiedekunnassa ylemmästä korkeakoulututkinnosta aloittaneet opiskelijat. Jokaiselle aineiston osalle sovitetaan omat toisistaan riippumattomat osamallit. Tutkintoennusteet saadaan ennustamalla aineistoon kuuluvi…

Ideal and physical barrier problems for non-linear systems driven by normal and Poissonian white noise via path integral method

2016

Abstract In this paper, the probability density evolution of Markov processes is analyzed for a class of barrier problems specified in terms of certain boundary conditions. The standard case of computing the probability density of the response is associated with natural boundary conditions, and the first passage problem is associated with absorbing boundaries. In contrast, herein we consider the more general case of partially reflecting boundaries and the effect of these boundaries on the probability density of the response. In fact, both standard cases can be considered special cases of the general problem. We provide solutions by means of the path integral method for half- and single-degr…

On the convergence of unconstrained adaptive Markov chain Monte Carlo algorithms

2010

k-out-of-n systems: an exact formula for the stationary availability and multi-objective configuration design based on mathematical programming and T…

2018

[EN] Reliability and availability analyses are recognized as essential for guiding decision makers in the implementation of actions addressed to improve the technical and economical performance of complex systems. For industrial systems with reparable components, the most interesting parameter used to drive maintenance is the stationary availability. In this regard, the present paper proposes an exact formula for computing the system stationary availability of a k-out-of-n system. Such a formula is proved to be in agreement with the fundamental theorem of Markov chains. Then, a multi-objective mathematical model is formulated for choosing the optimal system configuration design. The Pareto …

Poisson convergence on continuous time branching random walks and multistage carcinogenesis.

1982

A theorem for Poisson convergence on realizations of two-dimensional Branching Random Walks with an underlying continuous time Markov Branching Process is proved. This result can be used to gain an approximation for the number of cells having sustained a certain deficiency after a long time in multistage carcinogenesis.

On the use of adaptive spatial weight matrices from disease mapping multivariate analyses

2020

Conditional autoregressive distributions are commonly used to model spatial dependence between nearby geographic units in disease mapping studies. These distributions induce spatial dependence by means of a spatial weights matrix that quantifies the strength of dependence between any two neighboring spatial units. The most common procedure for defining that spatial weights matrix is using an adjacency criterion. In that case, all pairs of spatial units with adjacent borders are given the same weight (typically 1) and the remaining non-adjacent units are assigned a weight of 0. However, assuming all spatial neighbors in a model to be equally influential could be possibly a too rigid or inapp…

Forecasting correlated time series with exponential smoothing models

2011

Abstract This paper presents the Bayesian analysis of a general multivariate exponential smoothing model that allows us to forecast time series jointly, subject to correlated random disturbances. The general multivariate model, which can be formulated as a seemingly unrelated regression model, includes the previously studied homogeneous multivariate Holt-Winters’ model as a special case when all of the univariate series share a common structure. MCMC simulation techniques are required in order to approach the non-analytically tractable posterior distribution of the model parameters. The predictive distribution is then estimated using Monte Carlo integration. A Bayesian model selection crite…

Improving the Performance Metric of Wireless Sensor Networks with Clustering Markov Chain Model and Multilevel Fusion

2013

Published version of an article in the journal: Mathematical Problems in Engineering. Also available from the publisher at: http://dx.doi.org/10.1155/2013/783543 Open access The paper proposes a performance metric evaluation for a distributed detection wireless sensor network with respect to IEEE 802.15.4 standard. A distributed detection scheme is considered with presence of the fusion node and organized sensors into the clustering and non-clustering networks. Sensors are distributed in clusters uniformly and nonuniformly and network has multilevel fusion centers. Fusion centers act as heads of clusters for decision making based on majority-like received signal strength (RSS) with comparis…