Search results for "Markov"
showing 10 items of 628 documents
Modeling and Mitigating Errors in Belief Propagation for Distributed Detection
2021
We study the behavior of the belief-propagation (BP) algorithm affected by erroneous data exchange in a wireless sensor network (WSN). The WSN conducts a distributed multidimensional hypothesis test over binary random variables. The joint statistical behavior of the sensor observations is modeled by a Markov random field whose parameters are used to build the BP messages exchanged between the sensing nodes. Through linearization of the BP message-update rule, we analyze the behavior of the resulting erroneous decision variables and derive closed-form relationships that describe the impact of stochastic errors on the performance of the BP algorithm. We then develop a decentralized distribute…
Quantum fluctuations and correlations in equilibrium and nonequilibrium thermodynamics
2014
La simulazione delle portate giornaliere di un corso d’acqua tramite modelli markoviani a stato nascosto
2008
La memoria valuta l’applicabilità dei modelli markoviani a stato nascosto (Hidden state Markov Models) per la simulazione delle portate giornaliere di un corso d’acqua. In questi modelli la variabile osservata è l’emissione di un processo markoviano con un numero discreto di stati, caratterizzato da una matrice di probabilità di transizione, che viene “ricoperto” da una certa funzione densità di probabilità. Il problema della selezione del modello consiste in questo caso nella scelta del numero di stati e del tipo di distribuzione di probabilità di appartenenza ad uno stato. Identificato il modello, la sua calibrazione consiste nella stima delle probabilità di transizione e dei parametri de…
Sentience and the Origins of Consciousness: From Cartesian Duality to Markovian Monism
2020
This essay addresses Cartesian duality and how its implicit dialectic might be repaired using physics and information theory. Our agenda is to describe a key distinction in the physical sciences that may provide a foundation for the distinction between mind and matter, and between sentient and intentional systems. From this perspective, it becomes tenable to talk about the physics of sentience and &lsquo
On Capturing Oil Rents with a National Excise Tax Revisited
2004
In this paper the scope of Bergstrom’s (1982) results is studied. Moreover, his analysis is extended assuming that extraction cost is directly related to accumulated extractions. For the case of a competitive market it is found that the optimal policy is a constant tariff if extraction is costless. However, with depletion effects, the optimal tariff must ultimately be decreasing. For the case of a monopolistic market the results depend crucially on the kind of strategies the importing country governments can play and on whether the monopolist chooses the price or extraction rate. For a price-setting monopolist it is shown that the importing countries cannot use a tariff to capture monopoly …
Statistical analysis of life sequence data
2016
Topological Protection and Control of Quantum Markovianity
2020
This article belongs to the Special Issue Topological Photonics.
Combining Sequence Analysis and Hidden Markov Models in the Analysis of Complex Life Sequence Data
2018
Life course data often consists of multiple parallel sequences, one for each life domain of interest. Multichannel sequence analysis has been used for computing pairwise dissimilarities and finding clusters in this type of multichannel (or multidimensional) sequence data. Describing and visualizing such data is, however, often challenging. We propose an approach for compressing, interpreting, and visualizing the information within multichannel sequences by finding (1) groups of similar trajectories and (2) similar phases within trajectories belonging to the same group. For these tasks we combine multichannel sequence analysis and hidden Markov modelling. We illustrate this approach with an …
Bayesian semiparametric long memory models for discretized event data
2020
We introduce a new class of semiparametric latent variable models for long memory discretized event data. The proposed methodology is motivated by a study of bird vocalizations in the Amazon rain forest; the timings of vocalizations exhibit self-similarity and long range dependence. This rules out Poisson process based models where the rate function itself is not long range dependent. The proposed class of FRActional Probit (FRAP) models is based on thresholding, a latent process. This latent process is modeled by a smooth Gaussian process and a fractional Brownian motion by assuming an additive structure. We develop a Bayesian approach to inference using Markov chain Monte Carlo and show g…