Simulating the formation of keratin filament networks by a piecewise-deterministic Markov process.
Beil, Michael; Lück, Sebastian; Fleischer, Frank; Portet, Stéphanie; Arendt, Wolfgang; Schmidt, Volker
2009-02-21
Keratin intermediate filament networks are part of the cytoskeleton in epithelial cells. They were found to regulate viscoelastic properties and motility of cancer cells. Due to unique biochemical properties of keratin polymers, the knowledge of the mechanisms controlling keratin network formation is incomplete. A combination of deterministic and stochastic modeling techniques can be a valuable source of information since they can describe known mechanisms of network evolution while reflecting the uncertainty with respect to a variety of molecular events. We applied the concept of piecewise-deterministic Markov processes to the modeling of keratin network formation with high spatiotemporal resolution. The deterministic component describes the diffusion-driven evolution of a pool of soluble keratin filament precursors fueling various network formation processes. Instants of network formation events are determined by a stochastic point process on the time axis. A probability distribution controlled by model parameters exercises control over the frequency of different mechanisms of network formation to be triggered. Locations of the network formation events are assigned dependent on the spatial distribution of the soluble pool of filament precursors. Based on this modeling approach, simulation studies revealed that the architecture of keratin networks mostly depends on the balance between filament elongation and branching processes. The spatial distribution of network mesh size, which strongly influences the mechanical characteristics of filament networks, is modulated by lateral annealing processes. This mechanism which is a specific feature of intermediate filament networks appears to be a major and fast regulator of cell mechanics.
International Nuclear Information System (INIS)
Costa, O. L. V.; Dufour, F.
2011-01-01
This paper deals with the expected discounted continuous control of piecewise deterministic Markov processes (PDMP’s) using a singular perturbation approach for dealing with rapidly oscillating parameters. The state space of the PDMP is written as the product of a finite set and a subset of the Euclidean space ℝ n . The discrete part of the state, called the regime, characterizes the mode of operation of the physical system under consideration, and is supposed to have a fast (associated to a small parameter ε>0) and a slow behavior. By using a similar approach as developed in Yin and Zhang (Continuous-Time Markov Chains and Applications: A Singular Perturbation Approach, Applications of Mathematics, vol. 37, Springer, New York, 1998, Chaps. 1 and 3) the idea in this paper is to reduce the number of regimes by considering an averaged model in which the regimes within the same class are aggregated through the quasi-stationary distribution so that the different states in this class are replaced by a single one. The main goal is to show that the value function of the control problem for the system driven by the perturbed Markov chain converges to the value function of this limit control problem as ε goes to zero. This convergence is obtained by, roughly speaking, showing that the infimum and supremum limits of the value functions satisfy two optimality inequalities as ε goes to zero. This enables us to show the result by invoking a uniqueness argument, without needing any kind of Lipschitz continuity condition.
Ding, Shaojie; Qian, Min; Qian, Hong; Zhang, Xuejuan
2016-12-01
The stochastic Hodgkin-Huxley model is one of the best-known examples of piecewise deterministic Markov processes (PDMPs), in which the electrical potential across a cell membrane, V(t), is coupled with a mesoscopic Markov jump process representing the stochastic opening and closing of ion channels embedded in the membrane. The rates of the channel kinetics, in turn, are voltage-dependent. Due to this interdependence, an accurate and efficient sampling of the time evolution of the hybrid stochastic systems has been challenging. The current exact simulation methods require solving a voltage-dependent hitting time problem for multiple path-dependent intensity functions with random thresholds. This paper proposes a simulation algorithm that approximates an alternative representation of the exact solution by fitting the log-survival function of the inter-jump dwell time, H(t), with a piecewise linear one. The latter uses interpolation points that are chosen according to the time evolution of the H(t), as the numerical solution to the coupled ordinary differential equations of V(t) and H(t). This computational method can be applied to all PDMPs. Pathwise convergence of the approximated sample trajectories to the exact solution is proven, and error estimates are provided. Comparison with a previous algorithm that is based on piecewise constant approximation is also presented.
Energy Technology Data Exchange (ETDEWEB)
Goreac, Dan, E-mail: Dan.Goreac@u-pem.fr; Kobylanski, Magdalena, E-mail: Magdalena.Kobylanski@u-pem.fr; Martinez, Miguel, E-mail: Miguel.Martinez@u-pem.fr [Université Paris-Est, LAMA (UMR 8050), UPEMLV, UPEC, CNRS (France)
2016-10-15
We study optimal control problems in infinite horizon whxen the dynamics belong to a specific class of piecewise deterministic Markov processes constrained to star-shaped networks (corresponding to a toy traffic model). We adapt the results in Soner (SIAM J Control Optim 24(6):1110–1122, 1986) to prove the regularity of the value function and the dynamic programming principle. Extending the networks and Krylov’s “shaking the coefficients” method, we prove that the value function can be seen as the solution to a linearized optimization problem set on a convenient set of probability measures. The approach relies entirely on viscosity arguments. As a by-product, the dual formulation guarantees that the value function is the pointwise supremum over regular subsolutions of the associated Hamilton–Jacobi integrodifferential system. This ensures that the value function satisfies Perron’s preconization for the (unique) candidate to viscosity solution.
International Nuclear Information System (INIS)
Goreac, Dan; Kobylanski, Magdalena; Martinez, Miguel
2016-01-01
We study optimal control problems in infinite horizon whxen the dynamics belong to a specific class of piecewise deterministic Markov processes constrained to star-shaped networks (corresponding to a toy traffic model). We adapt the results in Soner (SIAM J Control Optim 24(6):1110–1122, 1986) to prove the regularity of the value function and the dynamic programming principle. Extending the networks and Krylov’s “shaking the coefficients” method, we prove that the value function can be seen as the solution to a linearized optimization problem set on a convenient set of probability measures. The approach relies entirely on viscosity arguments. As a by-product, the dual formulation guarantees that the value function is the pointwise supremum over regular subsolutions of the associated Hamilton–Jacobi integrodifferential system. This ensures that the value function satisfies Perron’s preconization for the (unique) candidate to viscosity solution.
Piecewise deterministic processes in biological models
Rudnicki, Ryszard
2017-01-01
This book presents a concise introduction to piecewise deterministic Markov processes (PDMPs), with particular emphasis on their applications to biological models. Further, it presents examples of biological phenomena, such as gene activity and population growth, where different types of PDMPs appear: continuous time Markov chains, deterministic processes with jumps, processes with switching dynamics, and point processes. Subsequent chapters present the necessary tools from the theory of stochastic processes and semigroups of linear operators, as well as theoretical results concerning the long-time behaviour of stochastic semigroups induced by PDMPs and their applications to biological models. As such, the book offers a valuable resource for mathematicians and biologists alike. The first group will find new biological models that lead to interesting and often new mathematical questions, while the second can observe how to include seemingly disparate biological processes into a unified mathematical theory, and...
Nonlinear Markov processes: Deterministic case
International Nuclear Information System (INIS)
Frank, T.D.
2008-01-01
Deterministic Markov processes that exhibit nonlinear transition mechanisms for probability densities are studied. In this context, the following issues are addressed: Markov property, conditional probability densities, propagation of probability densities, multistability in terms of multiple stationary distributions, stability analysis of stationary distributions, and basin of attraction of stationary distribution
Safety Verification of Piecewise-Deterministic Markov Processes
DEFF Research Database (Denmark)
Wisniewski, Rafael; Sloth, Christoffer; Bujorianu, Manuela
2016-01-01
the moment method, we can translate the infinite-dimensional optimisation problem searching for the largest set of p-safe states to a finite dimensional polynomial optimisation problem. We have implemented this technique on top of GloptiPoly and show how to apply it to a numerical example....
Automated Controller Synthesis for non-Deterministic Piecewise-Affine Hybrid Systems
DEFF Research Database (Denmark)
Grunnet, Jacob Deleuran
formations. This thesis uses a hybrid systems model of a satellite formation with possible actuator faults as a motivating example for developing an automated control synthesis method for non-deterministic piecewise-affine hybrid systems (PAHS). The method does not only open an avenue for further research...... in fault tolerant satellite formation control, but can be used to synthesise controllers for a wide range of systems where external events can alter the system dynamics. The synthesis method relies on abstracting the hybrid system into a discrete game, finding a winning strategy for the game meeting...... game and linear optimisation solvers for controller refinement. To illustrate the efficacy of the method a reoccurring satellite formation example including actuator faults has been used. The end result is the application of PAHSCTRL on the example showing synthesis and simulation of a fault tolerant...
Transport properties of a piecewise linear transformation and deterministic Levy flights
International Nuclear Information System (INIS)
Miyaguchi, Tomoshige
2006-01-01
The transport properties of a 1-dimensional piecewise linear dynamical system are investigated through the spectrum of its Frobenius-Perron operator. For a class of initial densities, eigenvalues and eigenfunctions of the Frobenius-Perron operator are obtained explicitly. It is also found that in the long length wave limit, this system exhibits normal diffusion and super diffusion called Levy flight. The diffusion constant and stable index are derived from the eigenvalues. (author)
A high-fidelity weather time series generator using the Markov Chain process on a piecewise level
Hersvik, K.; Endrerud, O.-E. V.
2017-12-01
A method is developed for generating a set of unique weather time-series based on an existing weather series. The method allows statistically valid weather variations to take place within repeated simulations of offshore operations. The numerous generated time series need to share the same statistical qualities as the original time series. Statistical qualities here refer mainly to the distribution of weather windows available for work, including durations and frequencies of such weather windows, and seasonal characteristics. The method is based on the Markov chain process. The core new development lies in how the Markov Process is used, specifically by joining small pieces of random length time series together rather than joining individual weather states, each from a single time step, which is a common solution found in the literature. This new Markov model shows favorable characteristics with respect to the requirements set forth and all aspects of the validation performed.
Kapetanakis, Venediktos; Matthews, Fiona E; van den Hout, Ardo
2013-02-20
This paper presents a parametric method of fitting semi-Markov models with piecewise-constant hazards in the presence of left, right and interval censoring. We investigate transition intensities in a three-state illness-death model with no recovery. We relax the Markov assumption by adjusting the intensity for the transition from state 2 (illness) to state 3 (death) for the time spent in state 2 through a time-varying covariate. This involves the exact time of the transition from state 1 (healthy) to state 2. When the data are subject to left or interval censoring, this time is unknown. In the estimation of the likelihood, we take into account interval censoring by integrating out all possible times for the transition from state 1 to state 2. For left censoring, we use an Expectation-Maximisation inspired algorithm. A simulation study reflects the performance of the method. The proposed combination of statistical procedures provides great flexibility. We illustrate the method in an application by using data on stroke onset for the older population from the UK Medical Research Council Cognitive Function and Ageing Study. Copyright © 2012 John Wiley & Sons, Ltd.
Reviving Markov processes and applications
International Nuclear Information System (INIS)
Cai, H.
1988-01-01
In this dissertation we study a procedure which restarts a Markov process when the process is killed by some arbitrary multiplicative functional. The regenerative nature of this revival procedure is characterized through a Markov renewal equation. An interesting duality between the revival procedure and the classical killing operation is found. Under the condition that the multiplicative functional possesses an intensity, the generators of the revival process can be written down explicitly. An intimate connection is also found between the perturbation of the sample path of a Markov process and the perturbation of a generator (in Kato's sense). The applications of the theory include the study of the processes like piecewise-deterministic Markov process, virtual waiting time process and the first entrance decomposition (taboo probability)
Monotone piecewise bicubic interpolation
International Nuclear Information System (INIS)
Carlson, R.E.; Fritsch, F.N.
1985-01-01
In a 1980 paper the authors developed a univariate piecewise cubic interpolation algorithm which produces a monotone interpolant to monotone data. This paper is an extension of those results to monotone script C 1 piecewise bicubic interpolation to data on a rectangular mesh. Such an interpolant is determined by the first partial derivatives and first mixed partial (twist) at the mesh points. Necessary and sufficient conditions on these derivatives are derived such that the resulting bicubic polynomial is monotone on a single rectangular element. These conditions are then simplified to a set of sufficient conditions for monotonicity. The latter are translated to a system of linear inequalities, which form the basis for a monotone piecewise bicubic interpolation algorithm. 4 references, 6 figures, 2 tables
Piecewise flat gravitational waves
van de Meent, M.
2011-01-01
We examine the continuum limit of the piecewise flat locally finite gravity model introduced by ’t Hooft. In the linear weak field limit, we find the energy–momentum tensor and metric perturbation of an arbitrary configuration of defects. The energy–momentum turns out to be restricted to satisfy
Exact piecewise flat gravitational waves
van de Meent, M.
2011-01-01
We generalize our previous linear result (van de Meent 2011 Class. Quantum Grav 28 075005) in obtaining gravitational waves from our piecewise flat model for gravity in 3+1 dimensions to exact piecewise flat configurations describing exact planar gravitational waves. We show explicitly how to
Slope Estimation in Noisy Piecewise Linear Functions.
Ingle, Atul; Bucklew, James; Sethares, William; Varghese, Tomy
2015-03-01
This paper discusses the development of a slope estimation algorithm called MAPSlope for piecewise linear data that is corrupted by Gaussian noise. The number and locations of slope change points (also known as breakpoints) are assumed to be unknown a priori though it is assumed that the possible range of slope values lies within known bounds. A stochastic hidden Markov model that is general enough to encompass real world sources of piecewise linear data is used to model the transitions between slope values and the problem of slope estimation is addressed using a Bayesian maximum a posteriori approach. The set of possible slope values is discretized, enabling the design of a dynamic programming algorithm for posterior density maximization. Numerical simulations are used to justify choice of a reasonable number of quantization levels and also to analyze mean squared error performance of the proposed algorithm. An alternating maximization algorithm is proposed for estimation of unknown model parameters and a convergence result for the method is provided. Finally, results using data from political science, finance and medical imaging applications are presented to demonstrate the practical utility of this procedure.
Maximizing Entropy over Markov Processes
DEFF Research Database (Denmark)
Biondi, Fabrizio; Legay, Axel; Nielsen, Bo Friis
2013-01-01
The channel capacity of a deterministic system with confidential data is an upper bound on the amount of bits of data an attacker can learn from the system. We encode all possible attacks to a system using a probabilistic specification, an Interval Markov Chain. Then the channel capacity...... as a reward function, a polynomial algorithm to verify the existence of an system maximizing entropy among those respecting a specification, a procedure for the maximization of reward functions over Interval Markov Chains and its application to synthesize an implementation maximizing entropy. We show how...... to use Interval Markov Chains to model abstractions of deterministic systems with confidential data, and use the above results to compute their channel capacity. These results are a foundation for ongoing work on computing channel capacity for abstractions of programs derived from code....
Maximizing entropy over Markov processes
DEFF Research Database (Denmark)
Biondi, Fabrizio; Legay, Axel; Nielsen, Bo Friis
2014-01-01
The channel capacity of a deterministic system with confidential data is an upper bound on the amount of bits of data an attacker can learn from the system. We encode all possible attacks to a system using a probabilistic specification, an Interval Markov Chain. Then the channel capacity...... as a reward function, a polynomial algorithm to verify the existence of a system maximizing entropy among those respecting a specification, a procedure for the maximization of reward functions over Interval Markov Chains and its application to synthesize an implementation maximizing entropy. We show how...... to use Interval Markov Chains to model abstractions of deterministic systems with confidential data, and use the above results to compute their channel capacity. These results are a foundation for ongoing work on computing channel capacity for abstractions of programs derived from code. © 2014 Elsevier...
Kirkwood, James R
2015-01-01
Review of ProbabilityShort HistoryReview of Basic Probability DefinitionsSome Common Probability DistributionsProperties of a Probability DistributionProperties of the Expected ValueExpected Value of a Random Variable with Common DistributionsGenerating FunctionsMoment Generating FunctionsExercisesDiscrete-Time, Finite-State Markov ChainsIntroductionNotationTransition MatricesDirected Graphs: Examples of Markov ChainsRandom Walk with Reflecting BoundariesGamblerâ€™s RuinEhrenfest ModelCentral Problem of Markov ChainsCondition to Ensure a Unique Equilibrium StateFinding the Equilibrium StateTransient and Recurrent StatesIndicator FunctionsPerron-Frobenius TheoremAbsorbing Markov ChainsMean First Passage TimeMean Recurrence Time and the Equilibrium StateFundamental Matrix for Regular Markov ChainsDividing a Markov Chain into Equivalence ClassesPeriodic Markov ChainsReducible Markov ChainsSummaryExercisesDiscrete-Time, Infinite-State Markov ChainsRenewal ProcessesDelayed Renewal ProcessesEquilibrium State f...
Markov Chains and Markov Processes
Ogunbayo, Segun
2016-01-01
Markov chain, which was named after Andrew Markov is a mathematical system that transfers a state to another state. Many real world systems contain uncertainty. This study helps us to understand the basic idea of a Markov chain and how is been useful in our daily lives. For some times there had been suspense on distinct predictions and future existences. Also in different games there had been different expectations or results involved. That is the reason why we need Markov chains to predict o...
Spaces of Piecewise Linear Manifolds
DEFF Research Database (Denmark)
Gomez Lopez, Mauricio Esteban
Abstract In this thesis we introduce Δ-set ψPLd(RN) which we regard as the piecewise linear analogue of the space ψd(RN) of smooth d-dimensional submanifoldsin RN introduced by Galatius in [4]. Using ψPLd(RN) we define a bi-Δ-set Cd(RN)•,• ( whose geometric realization BCPLd(RN) = llCd(RN)•,•ll ......Abstract In this thesis we introduce Δ-set ψPLd(RN) which we regard as the piecewise linear analogue of the space ψd(RN) of smooth d-dimensional submanifoldsin RN introduced by Galatius in [4]. Using ψPLd(RN) we define a bi-Δ-set Cd(RN)•,• ( whose geometric realization BCPLd(RN) = ll...... BCPLd (RN) ≅ ΩN–1lψPLd (RN)•l when N — d ≥ 3. The proof of the main theorem relies on properties of ψPLd (RN) • which arise from the fact that this Δ-set can be obtained from a more general contravariant functor PL op → Sets defined on the category of finite dimensional polyhedraand piecewise linear...... maps, and on a fiberwise transversality result for piecewise linear submersions whose fibers are contained in R × (-1,1)N-1 ⊆ RN . For the proof of this transversality result we use a theorem of Hudson on extensions of piecewise linear isotopies which is why we need to include the condition N — d ≥ 3...
Stable piecewise polynomial vector fields
Directory of Open Access Journals (Sweden)
Claudio Pessoa
2012-09-01
Full Text Available Let $N={y>0}$ and $S={y<0}$ be the semi-planes of $mathbb{R}^2$ having as common boundary the line $D={y=0}$. Let $X$ and $Y$ be polynomial vector fields defined in $N$ and $S$, respectively, leading to a discontinuous piecewise polynomial vector field $Z=(X,Y$. This work pursues the stability and the transition analysis of solutions of $Z$ between $N$ and $S$, started by Filippov (1988 and Kozlova (1984 and reformulated by Sotomayor-Teixeira (1995 in terms of the regularization method. This method consists in analyzing a one parameter family of continuous vector fields $Z_{epsilon}$, defined by averaging $X$ and $Y$. This family approaches $Z$ when the parameter goes to zero. The results of Sotomayor-Teixeira and Sotomayor-Machado (2002 providing conditions on $(X,Y$ for the regularized vector fields to be structurally stable on planar compact connected regions are extended to discontinuous piecewise polynomial vector fields on $mathbb{R}^2$. Pertinent genericity results for vector fields satisfying the above stability conditions are also extended to the present case. A procedure for the study of discontinuous piecewise vector fields at infinity through a compactification is proposed here.
Fracture Mechanical Markov Chain Crack Growth Model
DEFF Research Database (Denmark)
Gansted, L.; Brincker, Rune; Hansen, Lars Pilegaard
1991-01-01
propagation process can be described by a discrete space Markov theory. The model is applicable to deterministic as well as to random loading. Once the model parameters for a given material have been determined, the results can be used for any structure as soon as the geometrical function is known....
Control and estimation of piecewise affine systems
Xu, Jun
2014-01-01
As a powerful tool to study nonlinear systems and hybrid systems, piecewise affine (PWA) systems have been widely applied to mechanical systems. Control and Estimation of Piecewise Affine Systems presents several research findings relating to the control and estimation of PWA systems in one unified view. Chapters in this title discuss stability results of PWA systems, using piecewise quadratic Lyapunov functions and piecewise homogeneous polynomial Lyapunov functions. Explicit necessary and sufficient conditions for the controllability and reachability of a class of PWA systems are
Quantized, piecewise linear filter network
DEFF Research Database (Denmark)
Sørensen, John Aasted
1993-01-01
A quantization based piecewise linear filter network is defined. A method for the training of this network based on local approximation in the input space is devised. The training is carried out by repeatedly alternating between vector quantization of the training set into quantization classes...... and equalization of the quantization classes linear filter mean square training errors. The equalization of the mean square training errors is carried out by adapting the boundaries between neighbor quantization classes such that the differences in mean square training errors are reduced...
Stability Analysis of Periodic Orbits in a Class of Duffing-Like Piecewise Linear Vibrators
El Aroudi, A.
2014-09-01
In this paper, we study the dynamical behavior of a Duffing-like piecewise linear (PWL) springmass-damper system for vibration-based energy harvesting applications. First, we present a continuous time single degree of freedom PWL dynamical model of the system. From this PWL model, numerical simulations are carried out by computing frequency response and bifurcation diagram under a deterministic harmonic excitation for different sets of system parameter values. Stability analysis is performed using Floquet theory combined with Fillipov method.
Stability Analysis of Periodic Orbits in a Class of Duffing-Like Piecewise Linear Vibrators
El Aroudi, A.; Benadero, L.; Ouakad, H.; Younis, Mohammad I.
2014-01-01
In this paper, we study the dynamical behavior of a Duffing-like piecewise linear (PWL) springmass-damper system for vibration-based energy harvesting applications. First, we present a continuous time single degree of freedom PWL dynamical model of the system. From this PWL model, numerical simulations are carried out by computing frequency response and bifurcation diagram under a deterministic harmonic excitation for different sets of system parameter values. Stability analysis is performed using Floquet theory combined with Fillipov method.
Pseudo-random number generator based on asymptotic deterministic randomness
Wang, Kai; Pei, Wenjiang; Xia, Haishan; Cheung, Yiu-ming
2008-06-01
A novel approach to generate the pseudorandom-bit sequence from the asymptotic deterministic randomness system is proposed in this Letter. We study the characteristic of multi-value correspondence of the asymptotic deterministic randomness constructed by the piecewise linear map and the noninvertible nonlinearity transform, and then give the discretized systems in the finite digitized state space. The statistic characteristics of the asymptotic deterministic randomness are investigated numerically, such as stationary probability density function and random-like behavior. Furthermore, we analyze the dynamics of the symbolic sequence. Both theoretical and experimental results show that the symbolic sequence of the asymptotic deterministic randomness possesses very good cryptographic properties, which improve the security of chaos based PRBGs and increase the resistance against entropy attacks and symbolic dynamics attacks.
Pseudo-random number generator based on asymptotic deterministic randomness
International Nuclear Information System (INIS)
Wang Kai; Pei Wenjiang; Xia Haishan; Cheung Yiuming
2008-01-01
A novel approach to generate the pseudorandom-bit sequence from the asymptotic deterministic randomness system is proposed in this Letter. We study the characteristic of multi-value correspondence of the asymptotic deterministic randomness constructed by the piecewise linear map and the noninvertible nonlinearity transform, and then give the discretized systems in the finite digitized state space. The statistic characteristics of the asymptotic deterministic randomness are investigated numerically, such as stationary probability density function and random-like behavior. Furthermore, we analyze the dynamics of the symbolic sequence. Both theoretical and experimental results show that the symbolic sequence of the asymptotic deterministic randomness possesses very good cryptographic properties, which improve the security of chaos based PRBGs and increase the resistance against entropy attacks and symbolic dynamics attacks
DEFF Research Database (Denmark)
Gravesen, Jens
2005-01-01
t is shown that a closed polygon with an odd number of vertices is the median of exactly one piecewise planar cylinder and one piecewise planar Möbius band, intersecting each other orthogonally. A closed polygon with an even number of vertices is in the generic case neither the median...
Deterministic Graphical Games Revisited
DEFF Research Database (Denmark)
Andersson, Daniel; Hansen, Kristoffer Arnsfelt; Miltersen, Peter Bro
2008-01-01
We revisit the deterministic graphical games of Washburn. A deterministic graphical game can be described as a simple stochastic game (a notion due to Anne Condon), except that we allow arbitrary real payoffs but disallow moves of chance. We study the complexity of solving deterministic graphical...... games and obtain an almost-linear time comparison-based algorithm for computing an equilibrium of such a game. The existence of a linear time comparison-based algorithm remains an open problem....
Markov processes an introduction for physical scientists
Gillespie, Daniel T
1991-01-01
Markov process theory is basically an extension of ordinary calculus to accommodate functions whos time evolutions are not entirely deterministic. It is a subject that is becoming increasingly important for many fields of science. This book develops the single-variable theory of both continuous and jump Markov processes in a way that should appeal especially to physicists and chemists at the senior and graduate level.Key Features* A self-contained, prgamatic exposition of the needed elements of random variable theory* Logically integrated derviations of the Chapman-Kolmogorov e
Piecewise Loglinear Estimation of Efficient Production Surfaces
Rajiv D. Banker; Ajay Maindiratta
1986-01-01
Linear programming formulations for piecewise loglinear estimation of efficient production surfaces are derived from a set of basic properties postulated for the underlying production possibility sets. Unlike the piecewise linear model of Banker, Charnes, and Cooper (Banker R. D., A. Charnes, W. W. Cooper. 1984. Models for the estimation of technical and scale inefficiencies in data envelopment analysis. Management Sci. 30 (September) 1078--1092.), this approach permits the identification of ...
Markov processes and controlled Markov chains
Filar, Jerzy; Chen, Anyue
2002-01-01
The general theory of stochastic processes and the more specialized theory of Markov processes evolved enormously in the second half of the last century. In parallel, the theory of controlled Markov chains (or Markov decision processes) was being pioneered by control engineers and operations researchers. Researchers in Markov processes and controlled Markov chains have been, for a long time, aware of the synergies between these two subject areas. However, this may be the first volume dedicated to highlighting these synergies and, almost certainly, it is the first volume that emphasizes the contributions of the vibrant and growing Chinese school of probability. The chapters that appear in this book reflect both the maturity and the vitality of modern day Markov processes and controlled Markov chains. They also will provide an opportunity to trace the connections that have emerged between the work done by members of the Chinese school of probability and the work done by the European, US, Central and South Ameri...
Dynamic optimization deterministic and stochastic models
Hinderer, Karl; Stieglitz, Michael
2016-01-01
This book explores discrete-time dynamic optimization and provides a detailed introduction to both deterministic and stochastic models. Covering problems with finite and infinite horizon, as well as Markov renewal programs, Bayesian control models and partially observable processes, the book focuses on the precise modelling of applications in a variety of areas, including operations research, computer science, mathematics, statistics, engineering, economics and finance. Dynamic Optimization is a carefully presented textbook which starts with discrete-time deterministic dynamic optimization problems, providing readers with the tools for sequential decision-making, before proceeding to the more complicated stochastic models. The authors present complete and simple proofs and illustrate the main results with numerous examples and exercises (without solutions). With relevant material covered in four appendices, this book is completely self-contained.
Pseudo-deterministic Algorithms
Goldwasser , Shafi
2012-01-01
International audience; In this talk we describe a new type of probabilistic algorithm which we call Bellagio Algorithms: a randomized algorithm which is guaranteed to run in expected polynomial time, and to produce a correct and unique solution with high probability. These algorithms are pseudo-deterministic: they can not be distinguished from deterministic algorithms in polynomial time by a probabilistic polynomial time observer with black box access to the algorithm. We show a necessary an...
FDTD Method for Piecewise Homogeneous Dielectric Media
Directory of Open Access Journals (Sweden)
Zh. O. Dombrovskaya
2016-01-01
Full Text Available In this paper, we consider a numerical solution of Maxwell’s curl equations for piecewise uniform dielectric medium by the example of a one-dimensional problem. For obtaining the second order accuracy, the electric field grid node is placed into the permittivity discontinuity point of the medium. If the dielectric permittivity is large, the problem becomes singularly perturbed and a contrast structure appears. We propose a piecewise quasi-uniform mesh which resolves all characteristic solution parts of the problem (regular part, boundary layer and transition zone placed between them in detail. The features of the mesh are discussed.
Fast-slow asymptotics for a Markov chain model of fast sodium current
Starý, Tomáš; Biktashev, Vadim N.
2017-09-01
We explore the feasibility of using fast-slow asymptotics to eliminate the computational stiffness of discrete-state, continuous-time deterministic Markov chain models of ionic channels underlying cardiac excitability. We focus on a Markov chain model of fast sodium current, and investigate its asymptotic behaviour with respect to small parameters identified in different ways.
Stability Analysis of Periodic Orbits in a Class of Duffing-Like Piecewise Linear Vibrators
Directory of Open Access Journals (Sweden)
El Aroudi A.
2014-01-01
Full Text Available In this paper, we study the dynamical behavior of a Duffing-like piecewise linear (PWL springmass-damper system for vibration-based energy harvesting applications. First, we present a continuous time single degree of freedom PWL dynamical model of the system. From this PWL model, numerical simulations are carried out by computing frequency response and bifurcation diagram under a deterministic harmonic excitation for different sets of system parameter values. Stability analysis is performed using Floquet theory combined with Fillipov method.
Markov stochasticity coordinates
International Nuclear Information System (INIS)
Eliazar, Iddo
2017-01-01
Markov dynamics constitute one of the most fundamental models of random motion between the states of a system of interest. Markov dynamics have diverse applications in many fields of science and engineering, and are particularly applicable in the context of random motion in networks. In this paper we present a two-dimensional gauging method of the randomness of Markov dynamics. The method–termed Markov Stochasticity Coordinates–is established, discussed, and exemplified. Also, the method is tweaked to quantify the stochasticity of the first-passage-times of Markov dynamics, and the socioeconomic equality and mobility in human societies.
Abdulla, Parosh Aziz; Henda, Noomene Ben; Mayr, Richard
2007-01-01
We consider qualitative and quantitative verification problems for infinite-state Markov chains. We call a Markov chain decisive w.r.t. a given set of target states F if it almost certainly eventually reaches either F or a state from which F can no longer be reached. While all finite Markov chains are trivially decisive (for every set F), this also holds for many classes of infinite Markov chains. Infinite Markov chains which contain a finite attractor are decisive w.r.t. every set F. In part...
Markov stochasticity coordinates
Energy Technology Data Exchange (ETDEWEB)
Eliazar, Iddo, E-mail: iddo.eliazar@intel.com
2017-01-15
Markov dynamics constitute one of the most fundamental models of random motion between the states of a system of interest. Markov dynamics have diverse applications in many fields of science and engineering, and are particularly applicable in the context of random motion in networks. In this paper we present a two-dimensional gauging method of the randomness of Markov dynamics. The method–termed Markov Stochasticity Coordinates–is established, discussed, and exemplified. Also, the method is tweaked to quantify the stochasticity of the first-passage-times of Markov dynamics, and the socioeconomic equality and mobility in human societies.
Modeling nonhomogeneous Markov processes via time transformation.
Hubbard, R A; Inoue, L Y T; Fann, J R
2008-09-01
Longitudinal studies are a powerful tool for characterizing the course of chronic disease. These studies are usually carried out with subjects observed at periodic visits giving rise to panel data. Under this observation scheme the exact times of disease state transitions and sequence of disease states visited are unknown and Markov process models are often used to describe disease progression. Most applications of Markov process models rely on the assumption of time homogeneity, that is, that the transition rates are constant over time. This assumption is not satisfied when transition rates depend on time from the process origin. However, limited statistical tools are available for dealing with nonhomogeneity. We propose models in which the time scale of a nonhomogeneous Markov process is transformed to an operational time scale on which the process is homogeneous. We develop a method for jointly estimating the time transformation and the transition intensity matrix for the time transformed homogeneous process. We assess maximum likelihood estimation using the Fisher scoring algorithm via simulation studies and compare performance of our method to homogeneous and piecewise homogeneous models. We apply our methodology to a study of delirium progression in a cohort of stem cell transplantation recipients and show that our method identifies temporal trends in delirium incidence and recovery.
Weak-noise limit of a piecewise-smooth stochastic differential equation.
Chen, Yaming; Baule, Adrian; Touchette, Hugo; Just, Wolfram
2013-11-01
We investigate the validity and accuracy of weak-noise (saddle-point or instanton) approximations for piecewise-smooth stochastic differential equations (SDEs), taking as an illustrative example a piecewise-constant SDE, which serves as a simple model of Brownian motion with solid friction. For this model, we show that the weak-noise approximation of the path integral correctly reproduces the known propagator of the SDE at lowest order in the noise power, as well as the main features of the exact propagator with higher-order corrections, provided the singularity of the path integral associated with the nonsmooth SDE is treated with some heuristics. We also show that, as in the case of smooth SDEs, the deterministic paths of the noiseless system correctly describe the behavior of the nonsmooth SDE in the low-noise limit. Finally, we consider a smooth regularization of the piecewise-constant SDE and study to what extent this regularization can rectify some of the problems encountered when dealing with discontinuous drifts and singularities in SDEs.
Deterministic Compressed Sensing
2011-11-01
39 4.3 Digital Communications . . . . . . . . . . . . . . . . . . . . . . . . . 40 4.4 Group Testing ...deterministic de - sign matrices. All bounds ignore the O() constants. . . . . . . . . . . 131 xvi List of Algorithms 1 Iterative Hard Thresholding Algorithm...sensing is information theoretically possible using any (2k, )-RIP sensing matrix . The following celebrated results of Candès, Romberg and Tao [54
Deterministic uncertainty analysis
International Nuclear Information System (INIS)
Worley, B.A.
1987-01-01
Uncertainties of computer results are of primary interest in applications such as high-level waste (HLW) repository performance assessment in which experimental validation is not possible or practical. This work presents an alternate deterministic approach for calculating uncertainties that has the potential to significantly reduce the number of computer runs required for conventional statistical analysis. 7 refs., 1 fig
International Nuclear Information System (INIS)
1990-01-01
In the present report, data on RBE values for effects in tissues of experimental animals and man are analysed to assess whether for specific tissues the present dose limits or annual limits of intake based on Q values, are adequate to prevent deterministic effects. (author)
Nonlinear Modeling by Assembling Piecewise Linear Models
Yao, Weigang; Liou, Meng-Sing
2013-01-01
To preserve nonlinearity of a full order system over a parameters range of interest, we propose a simple modeling approach by assembling a set of piecewise local solutions, including the first-order Taylor series terms expanded about some sampling states. The work by Rewienski and White inspired our use of piecewise linear local solutions. The assembly of these local approximations is accomplished by assigning nonlinear weights, through radial basis functions in this study. The efficacy of the proposed procedure is validated for a two-dimensional airfoil moving at different Mach numbers and pitching motions, under which the flow exhibits prominent nonlinear behaviors. All results confirm that our nonlinear model is accurate and stable for predicting not only aerodynamic forces but also detailed flowfields. Moreover, the model is robustness-accurate for inputs considerably different from the base trajectory in form and magnitude. This modeling preserves nonlinearity of the problems considered in a rather simple and accurate manner.
On boolean combinations forming piecewise testable languages
Czech Academy of Sciences Publication Activity Database
Masopust, Tomáš; Thomazo, M.
2017-01-01
Roč. 682, June 19 (2017), s. 165-179 ISSN 0304-3975 Institutional support: RVO:67985840 Keywords : automata * language s * k-piecewise testability Subject RIV: BA - General Mathematics OBOR OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8) Impact factor: 0.698, year: 2016 http://www.sciencedirect.com/science/article/pii/S030439751730066X
Decomposed Implicit Models of Piecewise - Linear Networks
Directory of Open Access Journals (Sweden)
J. Brzobohaty
1992-05-01
Full Text Available The general matrix form of the implicit description of a piecewise-linear (PWL network and the symbolic block diagram of the corresponding circuit model are proposed. Their decomposed forms enable us to determine quite separately the existence of the individual breakpoints of the resultant PWL characteristic and their coordinates using independent network parameters. For the two-diode and three-diode cases all the attainable types of the PWL characteristic are introduced.
Deterministic and stochastic CTMC models from Zika disease transmission
Zevika, Mona; Soewono, Edy
2018-03-01
Zika infection is one of the most important mosquito-borne diseases in the world. Zika virus (ZIKV) is transmitted by many Aedes-type mosquitoes including Aedes aegypti. Pregnant women with the Zika virus are at risk of having a fetus or infant with a congenital defect and suffering from microcephaly. Here, we formulate a Zika disease transmission model using two approaches, a deterministic model and a continuous-time Markov chain stochastic model. The basic reproduction ratio is constructed from a deterministic model. Meanwhile, the CTMC stochastic model yields an estimate of the probability of extinction and outbreaks of Zika disease. Dynamical simulations and analysis of the disease transmission are shown for the deterministic and stochastic models.
Deterministic behavioural models for concurrency
DEFF Research Database (Denmark)
Sassone, Vladimiro; Nielsen, Mogens; Winskel, Glynn
1993-01-01
This paper offers three candidates for a deterministic, noninterleaving, behaviour model which generalizes Hoare traces to the noninterleaving situation. The three models are all proved equivalent in the rather strong sense of being equivalent as categories. The models are: deterministic labelled...... event structures, generalized trace languages in which the independence relation is context-dependent, and deterministic languages of pomsets....
Grabski
2014-01-01
Semi-Markov Processes: Applications in System Reliability and Maintenance is a modern view of discrete state space and continuous time semi-Markov processes and their applications in reliability and maintenance. The book explains how to construct semi-Markov models and discusses the different reliability parameters and characteristics that can be obtained from those models. The book is a useful resource for mathematicians, engineering practitioners, and PhD and MSc students who want to understand the basic concepts and results of semi-Markov process theory. Clearly defines the properties and
Learning Markov Decision Processes for Model Checking
DEFF Research Database (Denmark)
Mao, Hua; Chen, Yingke; Jaeger, Manfred
2012-01-01
. The proposed learning algorithm is adapted from algorithms for learning deterministic probabilistic finite automata, and extended to include both probabilistic and nondeterministic transitions. The algorithm is empirically analyzed and evaluated by learning system models of slot machines. The evaluation......Constructing an accurate system model for formal model verification can be both resource demanding and time-consuming. To alleviate this shortcoming, algorithms have been proposed for automatically learning system models based on observed system behaviors. In this paper we extend the algorithm...... on learning probabilistic automata to reactive systems, where the observed system behavior is in the form of alternating sequences of inputs and outputs. We propose an algorithm for automatically learning a deterministic labeled Markov decision process model from the observed behavior of a reactive system...
DEFF Research Database (Denmark)
Justesen, Jørn
2005-01-01
A simple construction of two-dimensional (2-D) fields is presented. Rows and columns are outcomes of the same Markov chain. The entropy can be calculated explicitly.......A simple construction of two-dimensional (2-D) fields is presented. Rows and columns are outcomes of the same Markov chain. The entropy can be calculated explicitly....
Deterministic Graphical Games Revisited
DEFF Research Database (Denmark)
Andersson, Klas Olof Daniel; Hansen, Kristoffer Arnsfelt; Miltersen, Peter Bro
2012-01-01
Starting from Zermelo’s classical formal treatment of chess, we trace through history the analysis of two-player win/lose/draw games with perfect information and potentially infinite play. Such chess-like games have appeared in many different research communities, and methods for solving them......, such as retrograde analysis, have been rediscovered independently. We then revisit Washburn’s deterministic graphical games (DGGs), a natural generalization of chess-like games to arbitrary zero-sum payoffs. We study the complexity of solving DGGs and obtain an almost-linear time comparison-based algorithm...
Diffusion piecewise homogenization via flux discontinuity factors
International Nuclear Information System (INIS)
Sanchez, Richard; Zmijarevic, Igor
2011-01-01
We analyze the calculation of flux discontinuity factors (FDFs) for use with piecewise subdomain assembly homogenization. These coefficients depend on the numerical mesh used to compute the diffusion problem. When the mesh has a single degree of freedom on subdomain interfaces the solution is unique and can be computed independently per subdomain. For all other cases we have implemented an iterative calculation for the FDFs. Our numerical results show that there is no solution to this nonlinear problem but that the iterative algorithm converges towards FDFs values that reproduce subdomains reaction rates with a relatively high precision. In our test we have included both the GET and black-box FDFs. (author)
Bayesian regression of piecewise homogeneous Poisson processes
Directory of Open Access Journals (Sweden)
Diego Sevilla
2015-12-01
Full Text Available In this paper, a Bayesian method for piecewise regression is adapted to handle counting processes data distributed as Poisson. A numerical code in Mathematica is developed and tested analyzing simulated data. The resulting method is valuable for detecting breaking points in the count rate of time series for Poisson processes. Received: 2 November 2015, Accepted: 27 November 2015; Edited by: R. Dickman; Reviewed by: M. Hutter, Australian National University, Canberra, Australia.; DOI: http://dx.doi.org/10.4279/PIP.070018 Cite as: D J R Sevilla, Papers in Physics 7, 070018 (2015
A Memristor Model with Piecewise Window Function
Directory of Open Access Journals (Sweden)
J. Yu
2013-12-01
Full Text Available In this paper, we present a memristor model with piecewise window function, which is continuously differentiable and consists of three nonlinear pieces. By introducing two parameters, the shape of this window function can be flexibly adjusted to model different types of memristors. Using this model, one can easily obtain an expression of memristance depending on charge, from which the numerical value of memristance can be readily calculated for any given charge, and eliminate the error occurring in the simulation of some existing window function models.
Bound constrained quadratic programming via piecewise
DEFF Research Database (Denmark)
Madsen, Kaj; Nielsen, Hans Bruun; Pinar, M. C.
1999-01-01
of a symmetric, positive definite matrix, and is solved by Newton iteration with line search. The paper describes the algorithm and its implementation including estimation of lambda/sub 1/ , how to get a good starting point for the iteration, and up- and downdating of Cholesky factorization. Results of extensive......We consider the strictly convex quadratic programming problem with bounded variables. A dual problem is derived using Lagrange duality. The dual problem is the minimization of an unconstrained, piecewise quadratic function. It involves a lower bound of lambda/sub 1/ , the smallest eigenvalue...
Diffusion piecewise homogenization via flux discontinuity ratios
International Nuclear Information System (INIS)
Sanchez, Richard; Dante, Giorgio; Zmijarevic, Igor
2013-01-01
We analyze piecewise homogenization with flux-weighted cross sections and preservation of averaged currents at the boundary of the homogenized domain. Introduction of a set of flux discontinuity ratios (FDR) that preserve reference interface currents leads to preservation of averaged region reaction rates and fluxes. We consider the class of numerical discretizations with one degree of freedom per volume and per surface and prove that when the homogenization and computing meshes are equal there is a unique solution for the FDRs which exactly preserve interface currents. For diffusion sub-meshing we introduce a Jacobian-Free Newton-Krylov method and for all cases considered obtain an 'exact' numerical solution (eight digits for the interface currents). The homogenization is completed by extending the familiar full assembly homogenization via flux discontinuity factors to the sides of regions laying on the boundary of the piecewise homogenized domain. Finally, for the familiar nodal discretization we numerically find that the FDRs obtained with no sub-mesh (nearly at no cost) can be effectively used for whole-core diffusion calculations with sub-mesh. This is not the case, however, for cell-centered finite differences. (authors)
Analysis and design of Markov jump systems with complex transition probabilities
Zhang, Lixian; Shi, Peng; Zhu, Yanzheng
2016-01-01
The book addresses the control issues such as stability analysis, control synthesis and filter design of Markov jump systems with the above three types of TPs, and thus is mainly divided into three parts. Part I studies the Markov jump systems with partially unknown TPs. Different methodologies with different conservatism for the basic stability and stabilization problems are developed and compared. Then the problems of state estimation, the control of systems with time-varying delays, the case involved with both partially unknown TPs and uncertain TPs in a composite way are also tackled. Part II deals with the Markov jump systems with piecewise homogeneous TPs. Methodologies that can effectively handle control problems in the scenario are developed, including the one coping with the asynchronous switching phenomenon between the currently activated system mode and the controller/filter to be designed. Part III focuses on the Markov jump systems with memory TPs. The concept of σ-mean square stability is propo...
NONLINEAR PLANT PIECEWISE-CONTINUOUS MODEL MATRIX PARAMETERS ESTIMATION
Directory of Open Access Journals (Sweden)
Roman L. Leibov
2017-09-01
Full Text Available This paper presents a nonlinear plant piecewise-continuous model matrix parameters estimation technique using nonlinear model time responses and random search method. One of piecewise-continuous model application areas is defined. The results of proposed approach application for aircraft turbofan engine piecewisecontinuous model formation are presented
Using piecewise sinusoidal basis functions to blanket multiple wire segments
CSIR Research Space (South Africa)
Lysko, AA
2009-06-01
Full Text Available This paper discusses application of the piecewise sinusoidal (PWS) basis function (BF) over a chain of several wire segments, for example as a multiple domain basis function. The usage of PWS BF is compared to results based on the piecewise linear...
Online identification of continuous bimodal and trimodal piecewise affine systems
Le, Q.T.; van den Boom, A.J.J.; Baldi, S.; Rantzer, Anders; Bagterp Jørgensen, John; Stoustrup, Jakob
2016-01-01
This paper investigates the identification of continuous piecewise affine systems in state space form with jointly unknown partition and subsystem matrices. The partition of the system is generated by the so-called centers. By representing continuous piecewise affine systems in the max-form and
janssen, Anja; Segers, Johan
2013-01-01
The extremes of a univariate Markov chain with regularly varying stationary marginal distribution and asymptotically linear behavior are known to exhibit a multiplicative random walk structure called the tail chain. In this paper we extend this fact to Markov chains with multivariate regularly varying marginal distributions in Rd. We analyze both the forward and the backward tail process and show that they mutually determine each other through a kind of adjoint relation. In ...
Casimir energy for a piecewise uniform string
International Nuclear Information System (INIS)
Brevik, I.; Nielsen, H.B.
1989-07-01
The Casimir energy for the transverse oscillations of a piecewise uniform closed string is calculated. The string consists of two parts I and II, endowed in general with different tensions and mass densities, although adjusted in such a way that the velocity of sound always equals the velocity of light. The dispersion equation is worked out under general conditions, and the frequency spectrum is determined in special cases. When the ratio L II /L I between the string lengths is an integer, it is in principle possible to determine the frequency spectrum through solving algebraic equations of increasingly high degree. The Casimir energy relative to the uniform string is in general found to be negative, although in the special case L I =L II the energy is equal to zero. Delicate points in the regularization procedure are discussed; they point toward an anomaly in the theory. (orig.)
Markov chain modelling of pitting corrosion in underground pipelines
Energy Technology Data Exchange (ETDEWEB)
Caleyo, F. [Departamento de Ingenieri' a Metalurgica, ESIQIE, IPN, UPALM Edif. 7, Zacatenco, Mexico D. F. 07738 (Mexico)], E-mail: fcaleyo@gmail.com; Velazquez, J.C. [Departamento de Ingenieri' a Metalurgica, ESIQIE, IPN, UPALM Edif. 7, Zacatenco, Mexico D. F. 07738 (Mexico); Valor, A. [Facultad de Fisica, Universidad de La Habana, San Lazaro y L, Vedado, 10400 La Habana (Cuba); Hallen, J.M. [Departamento de Ingenieri' a Metalurgica, ESIQIE, IPN, UPALM Edif. 7, Zacatenco, Mexico D. F. 07738 (Mexico)
2009-09-15
A continuous-time, non-homogenous linear growth (pure birth) Markov process has been used to model external pitting corrosion in underground pipelines. The closed form solution of Kolmogorov's forward equations for this type of Markov process is used to describe the transition probability function in a discrete pit depth space. The identification of the transition probability function can be achieved by correlating the stochastic pit depth mean with the deterministic mean obtained experimentally. Monte-Carlo simulations previously reported have been used to predict the time evolution of the mean value of the pit depth distribution for different soil textural classes. The simulated distributions have been used to create an empirical Markov chain-based stochastic model for predicting the evolution of pitting corrosion depth and rate distributions from the observed properties of the soil. The proposed model has also been applied to pitting corrosion data from pipeline repeated in-line inspections and laboratory immersion experiments.
Markov chain modelling of pitting corrosion in underground pipelines
International Nuclear Information System (INIS)
Caleyo, F.; Velazquez, J.C.; Valor, A.; Hallen, J.M.
2009-01-01
A continuous-time, non-homogenous linear growth (pure birth) Markov process has been used to model external pitting corrosion in underground pipelines. The closed form solution of Kolmogorov's forward equations for this type of Markov process is used to describe the transition probability function in a discrete pit depth space. The identification of the transition probability function can be achieved by correlating the stochastic pit depth mean with the deterministic mean obtained experimentally. Monte-Carlo simulations previously reported have been used to predict the time evolution of the mean value of the pit depth distribution for different soil textural classes. The simulated distributions have been used to create an empirical Markov chain-based stochastic model for predicting the evolution of pitting corrosion depth and rate distributions from the observed properties of the soil. The proposed model has also been applied to pitting corrosion data from pipeline repeated in-line inspections and laboratory immersion experiments.
Deterministic uncertainty analysis
International Nuclear Information System (INIS)
Worley, B.A.
1987-12-01
This paper presents a deterministic uncertainty analysis (DUA) method for calculating uncertainties that has the potential to significantly reduce the number of computer runs compared to conventional statistical analysis. The method is based upon the availability of derivative and sensitivity data such as that calculated using the well known direct or adjoint sensitivity analysis techniques. Formation of response surfaces using derivative data and the propagation of input probability distributions are discussed relative to their role in the DUA method. A sample problem that models the flow of water through a borehole is used as a basis to compare the cumulative distribution function of the flow rate as calculated by the standard statistical methods and the DUA method. Propogation of uncertainties by the DUA method is compared for ten cases in which the number of reference model runs was varied from one to ten. The DUA method gives a more accurate representation of the true cumulative distribution of the flow rate based upon as few as two model executions compared to fifty model executions using a statistical approach. 16 refs., 4 figs., 5 tabs
The topological entropy of iterated piecewise affine maps is uncomputable
Directory of Open Access Journals (Sweden)
Pascal Koiran
2001-12-01
Full Text Available We show that it is impossible to compute (or even to approximate the topological entropy of a continuous piecewise affine function in dimension four. The same result holds for saturated linear functions in unbounded dimension. We ask whether the topological entropy of a piecewise affine function is always a computable real number, and conversely whether every non-negative computable real number can be obtained as the topological entropy of a piecewise affine function. It seems that these two questions are also open for cellular automata.
El Yazid Boudaren, Mohamed; Monfrini, Emmanuel; Pieczynski, Wojciech; Aïssani, Amar
2014-11-01
Hidden Markov chains have been shown to be inadequate for data modeling under some complex conditions. In this work, we address the problem of statistical modeling of phenomena involving two heterogeneous system states. Such phenomena may arise in biology or communications, among other fields. Namely, we consider that a sequence of meaningful words is to be searched within a whole observation that also contains arbitrary one-by-one symbols. Moreover, a word may be interrupted at some site to be carried on later. Applying plain hidden Markov chains to such data, while ignoring their specificity, yields unsatisfactory results. The Phasic triplet Markov chain, proposed in this paper, overcomes this difficulty by means of an auxiliary underlying process in accordance with the triplet Markov chains theory. Related Bayesian restoration techniques and parameters estimation procedures according to the new model are then described. Finally, to assess the performance of the proposed model against the conventional hidden Markov chain model, experiments are conducted on synthetic and real data.
Elements of automata theory and the theory of Markov chains. [Self-organizing control systems
Energy Technology Data Exchange (ETDEWEB)
Lind, M
1975-03-01
Selected topics from automata theory and the theory of Markov chains are treated. In particular, finite-memory automata are discussed in detail, and the results are used to formulate an automation model of a class of continuous systems. Stochastic automata are introduced as a natural generalization of the deterministic automaton. Markov chains are shown to be closely related to stochastic automata. Results from Markov chain theory are thereby directly applicable to analysis of stochastic automata. This report provides the theoretical foundation for the investigation in Riso Report No. 315 of a class of self-organizing control systems. (25 figures) (auth)
Height-Deterministic Pushdown Automata
DEFF Research Database (Denmark)
Nowotka, Dirk; Srba, Jiri
2007-01-01
We define the notion of height-deterministic pushdown automata, a model where for any given input string the stack heights during any (nondeterministic) computation on the input are a priori fixed. Different subclasses of height-deterministic pushdown automata, strictly containing the class...... of regular languages and still closed under boolean language operations, are considered. Several of such language classes have been described in the literature. Here, we suggest a natural and intuitive model that subsumes all the formalisms proposed so far by employing height-deterministic pushdown automata...
Hartfiel, Darald J
1998-01-01
In this study extending classical Markov chain theory to handle fluctuating transition matrices, the author develops a theory of Markov set-chains and provides numerous examples showing how that theory can be applied. Chapters are concluded with a discussion of related research. Readers who can benefit from this monograph are those interested in, or involved with, systems whose data is imprecise or that fluctuate with time. A background equivalent to a course in linear algebra and one in probability theory should be sufficient.
Piecewise linear regression splines with hyperbolic covariates
International Nuclear Information System (INIS)
Cologne, John B.; Sposto, Richard
1992-09-01
Consider the problem of fitting a curve to data that exhibit a multiphase linear response with smooth transitions between phases. We propose substituting hyperbolas as covariates in piecewise linear regression splines to obtain curves that are smoothly joined. The method provides an intuitive and easy way to extend the two-phase linear hyperbolic response model of Griffiths and Miller and Watts and Bacon to accommodate more than two linear segments. The resulting regression spline with hyperbolic covariates may be fit by nonlinear regression methods to estimate the degree of curvature between adjoining linear segments. The added complexity of fitting nonlinear, as opposed to linear, regression models is not great. The extra effort is particularly worthwhile when investigators are unwilling to assume that the slope of the response changes abruptly at the join points. We can also estimate the join points (the values of the abscissas where the linear segments would intersect if extrapolated) if their number and approximate locations may be presumed known. An example using data on changing age at menarche in a cohort of Japanese women illustrates the use of the method for exploratory data analysis. (author)
Deterministic methods in radiation transport
International Nuclear Information System (INIS)
Rice, A.F.; Roussin, R.W.
1992-06-01
The Seminar on Deterministic Methods in Radiation Transport was held February 4--5, 1992, in Oak Ridge, Tennessee. Eleven presentations were made and the full papers are published in this report, along with three that were submitted but not given orally. These papers represent a good overview of the state of the art in the deterministic solution of radiation transport problems for a variety of applications of current interest to the Radiation Shielding Information Center user community
Confluence reduction for Markov automata
Timmer, Mark; Katoen, Joost P.; van de Pol, Jaco; Stoelinga, Mariëlle Ida Antoinette
2016-01-01
Markov automata are a novel formalism for specifying systems exhibiting nondeterminism, probabilistic choices and Markovian rates. As expected, the state space explosion threatens the analysability of these models. We therefore introduce confluence reduction for Markov automata, a powerful reduction
Color and Contrast Enhancement by Controlled Piecewise Affine Histogram Equalization
Directory of Open Access Journals (Sweden)
Jose-Luis Lisani
2012-10-01
Full Text Available This paper presents a simple contrast enhancement algorithm based on histogram equalization (HE. The proposed algorithm performs a piecewise affine transform of the intensity levels of a digital image such that the new cumulative distribution function will be approximately uniform (as with HE, but where the stretching of the range is locally controlled to avoid brutal noise enhancement. We call this algorithm Piecewise Affine Equalization (PAE. Several experiments show that, in general, the new algorithm improves HE results.
Process Algebra and Markov Chains
Brinksma, Hendrik; Hermanns, H.; Brinksma, Hendrik; Hermanns, H.; Katoen, Joost P.
This paper surveys and relates the basic concepts of process algebra and the modelling of continuous time Markov chains. It provides basic introductions to both fields, where we also study the Markov chains from an algebraic perspective, viz. that of Markov chain algebra. We then proceed to study
Process algebra and Markov chains
Brinksma, E.; Hermanns, H.; Brinksma, E.; Hermanns, H.; Katoen, J.P.
2001-01-01
This paper surveys and relates the basic concepts of process algebra and the modelling of continuous time Markov chains. It provides basic introductions to both fields, where we also study the Markov chains from an algebraic perspective, viz. that of Markov chain algebra. We then proceed to study
Markov Chain Models for the Stochastic Modeling of Pitting Corrosion
Directory of Open Access Journals (Sweden)
A. Valor
2013-01-01
Full Text Available The stochastic nature of pitting corrosion of metallic structures has been widely recognized. It is assumed that this kind of deterioration retains no memory of the past, so only the current state of the damage influences its future development. This characteristic allows pitting corrosion to be categorized as a Markov process. In this paper, two different models of pitting corrosion, developed using Markov chains, are presented. Firstly, a continuous-time, nonhomogeneous linear growth (pure birth Markov process is used to model external pitting corrosion in underground pipelines. A closed-form solution of the system of Kolmogorov's forward equations is used to describe the transition probability function in a discrete pit depth space. The transition probability function is identified by correlating the stochastic pit depth mean with the empirical deterministic mean. In the second model, the distribution of maximum pit depths in a pitting experiment is successfully modeled after the combination of two stochastic processes: pit initiation and pit growth. Pit generation is modeled as a nonhomogeneous Poisson process, in which induction time is simulated as the realization of a Weibull process. Pit growth is simulated using a nonhomogeneous Markov process. An analytical solution of Kolmogorov's system of equations is also found for the transition probabilities from the first Markov state. Extreme value statistics is employed to find the distribution of maximum pit depths.
Indian Academy of Sciences (India)
be obtained as a limiting value of a sample path of a suitable ... makes a mathematical model of chance and deals with the problem by .... Is the Markov chain aperiodic? It is! Here is how you can see it. Suppose that after you do the cut, you hold the top half in your right hand, and the bottom half in your left. Then there.
Composable Markov Building Blocks
Evers, S.; Fokkinga, M.M.; Apers, Peter M.G.; Prade, H.; Subrahmanian, V.S.
2007-01-01
In situations where disjunct parts of the same process are described by their own first-order Markov models and only one model applies at a time (activity in one model coincides with non-activity in the other models), these models can be joined together into one. Under certain conditions, nearly all
Composable Markov Building Blocks
Evers, S.; Fokkinga, M.M.; Apers, Peter M.G.
2007-01-01
In situations where disjunct parts of the same process are described by their own first-order Markov models, these models can be joined together under the constraint that there can only be one activity at a time, i.e. the activities of one model coincide with non-activity in the other models. Under
Solan, Eilon; Vieille, Nicolas
2015-01-01
We study irreducible time-homogenous Markov chains with finite state space in discrete time. We obtain results on the sensitivity of the stationary distribution and other statistical quantities with respect to perturbations of the transition matrix. We define a new closeness relation between transition matrices, and use graph-theoretic techniques, in contrast with the matrix analysis techniques previously used.
Indian Academy of Sciences (India)
Home; Journals; Resonance – Journal of Science Education; Volume 7; Issue 3. Markov Chain Monte Carlo - Examples. Arnab Chakraborty. General Article Volume 7 Issue 3 March 2002 pp 25-34. Fulltext. Click here to view fulltext PDF. Permanent link: https://www.ias.ac.in/article/fulltext/reso/007/03/0025-0034. Keywords.
Partially Hidden Markov Models
DEFF Research Database (Denmark)
Forchhammer, Søren Otto; Rissanen, Jorma
1996-01-01
Partially Hidden Markov Models (PHMM) are introduced. They differ from the ordinary HMM's in that both the transition probabilities of the hidden states and the output probabilities are conditioned on past observations. As an illustration they are applied to black and white image compression where...
Deterministic and stochastic models for middle east respiratory syndrome (MERS)
Suryani, Dessy Rizki; Zevika, Mona; Nuraini, Nuning
2018-03-01
World Health Organization (WHO) data stated that since September 2012, there were 1,733 cases of Middle East Respiratory Syndrome (MERS) with 628 death cases that occurred in 27 countries. MERS was first identified in Saudi Arabia in 2012 and the largest cases of MERS outside Saudi Arabia occurred in South Korea in 2015. MERS is a disease that attacks the respiratory system caused by infection of MERS-CoV. MERS-CoV transmission occurs directly through direct contact between infected individual with non-infected individual or indirectly through contaminated object by the free virus. Suspected, MERS can spread quickly because of the free virus in environment. Mathematical modeling is used to illustrate the transmission of MERS disease using deterministic model and stochastic model. Deterministic model is used to investigate the temporal dynamic from the system to analyze the steady state condition. Stochastic model approach using Continuous Time Markov Chain (CTMC) is used to predict the future states by using random variables. From the models that were built, the threshold value for deterministic models and stochastic models obtained in the same form and the probability of disease extinction can be computed by stochastic model. Simulations for both models using several of different parameters are shown, and the probability of disease extinction will be compared with several initial conditions.
Deterministic indexing for packed strings
DEFF Research Database (Denmark)
Bille, Philip; Gørtz, Inge Li; Skjoldjensen, Frederik Rye
2017-01-01
Given a string S of length n, the classic string indexing problem is to preprocess S into a compact data structure that supports efficient subsequent pattern queries. In the deterministic variant the goal is to solve the string indexing problem without any randomization (at preprocessing time...... or query time). In the packed variant the strings are stored with several character in a single word, giving us the opportunity to read multiple characters simultaneously. Our main result is a new string index in the deterministic and packed setting. Given a packed string S of length n over an alphabet σ...
Generalized Markov branching models
Li, Junping
2005-01-01
In this thesis, we first considered a modified Markov branching process incorporating both state-independent immigration and resurrection. After establishing the criteria for regularity and uniqueness, explicit expressions for the extinction probability and mean extinction time are presented. The criteria for recurrence and ergodicity are also established. In addition, an explicit expression for the equilibrium distribution is presented.\\ud \\ud We then moved on to investigate the basic proper...
Ragain, Stephen; Ugander, Johan
2016-01-01
As datasets capturing human choices grow in richness and scale---particularly in online domains---there is an increasing need for choice models that escape traditional choice-theoretic axioms such as regularity, stochastic transitivity, and Luce's choice axiom. In this work we introduce the Pairwise Choice Markov Chain (PCMC) model of discrete choice, an inferentially tractable model that does not assume any of the above axioms while still satisfying the foundational axiom of uniform expansio...
Distinguishing Hidden Markov Chains
Kiefer, Stefan; Sistla, A. Prasad
2015-01-01
Hidden Markov Chains (HMCs) are commonly used mathematical models of probabilistic systems. They are employed in various fields such as speech recognition, signal processing, and biological sequence analysis. We consider the problem of distinguishing two given HMCs based on an observation sequence that one of the HMCs generates. More precisely, given two HMCs and an observation sequence, a distinguishing algorithm is expected to identify the HMC that generates the observation sequence. Two HM...
Fannes, Mark; Wouters, Jeroen
2012-01-01
We study a quantum process that can be considered as a quantum analogue for the classical Markov process. We specifically construct a version of these processes for free Fermions. For such free Fermionic processes we calculate the entropy density. This can be done either directly using Szeg\\"o's theorem for asymptotic densities of functions of Toeplitz matrices, or through an extension of said theorem to rates of functions, which we present in this article.
Pemodelan Markov Switching Autoregressive
Ariyani, Fiqria Devi; Warsito, Budi; Yasin, Hasbi
2014-01-01
Transition from depreciation to appreciation of exchange rate is one of regime switching that ignored by classic time series model, such as ARIMA, ARCH, or GARCH. Therefore, economic variables are modeled by Markov Switching Autoregressive (MSAR) which consider the regime switching. MLE is not applicable to parameters estimation because regime is an unobservable variable. So that filtering and smoothing process are applied to see the regime probabilities of observation. Using this model, tran...
Approximate quantum Markov chains
Sutter, David
2018-01-01
This book is an introduction to quantum Markov chains and explains how this concept is connected to the question of how well a lost quantum mechanical system can be recovered from a correlated subsystem. To achieve this goal, we strengthen the data-processing inequality such that it reveals a statement about the reconstruction of lost information. The main difficulty in order to understand the behavior of quantum Markov chains arises from the fact that quantum mechanical operators do not commute in general. As a result we start by explaining two techniques of how to deal with non-commuting matrices: the spectral pinching method and complex interpolation theory. Once the reader is familiar with these techniques a novel inequality is presented that extends the celebrated Golden-Thompson inequality to arbitrarily many matrices. This inequality is the key ingredient in understanding approximate quantum Markov chains and it answers a question from matrix analysis that was open since 1973, i.e., if Lieb's triple ma...
Directory of Open Access Journals (Sweden)
Mokaedi V. Lekgari
2014-01-01
Full Text Available We investigate random-time state-dependent Foster-Lyapunov analysis on subgeometric rate ergodicity of continuous-time Markov chains (CTMCs. We are mainly concerned with making use of the available results on deterministic state-dependent drift conditions for CTMCs and on random-time state-dependent drift conditions for discrete-time Markov chains and transferring them to CTMCs.
A relation between non-Markov and Markov processes
International Nuclear Information System (INIS)
Hara, H.
1980-01-01
With the aid of a transformation technique, it is shown that some memory effects in the non-Markov processes can be eliminated. In other words, some non-Markov processes are rewritten in a form obtained by the random walk process; the Markov process. To this end, two model processes which have some memory or correlation in the random walk process are introduced. An explanation of the memory in the processes is given. (orig.)
Transiently chaotic neural networks with piecewise linear output functions
Energy Technology Data Exchange (ETDEWEB)
Chen, S.-S. [Department of Mathematics, National Taiwan Normal University, Taipei, Taiwan (China); Shih, C.-W. [Department of Applied Mathematics, National Chiao Tung University, 1001 Ta-Hsueh Road, Hsinchu, Taiwan (China)], E-mail: cwshih@math.nctu.edu.tw
2009-01-30
Admitting both transient chaotic phase and convergent phase, the transiently chaotic neural network (TCNN) provides superior performance than the classical networks in solving combinatorial optimization problems. We derive concrete parameter conditions for these two essential dynamic phases of the TCNN with piecewise linear output function. The confirmation for chaotic dynamics of the system results from a successful application of the Marotto theorem which was recently clarified. Numerical simulation on applying the TCNN with piecewise linear output function is carried out to find the optimal solution of a travelling salesman problem. It is demonstrated that the performance is even better than the previous TCNN model with logistic output function.
Iterates of piecewise monotone mappings on an interval
Preston, Chris
1988-01-01
Piecewise monotone mappings on an interval provide simple examples of discrete dynamical systems whose behaviour can be very complicated. These notes are concerned with the properties of the iterates of such mappings. The material presented can be understood by anyone who has had a basic course in (one-dimensional) real analysis. The account concentrates on the topological (as opposed to the measure theoretical) aspects of the theory of piecewise monotone mappings. As well as offering an elementary introduction to this theory, these notes also contain a more advanced treatment of the problem of classifying such mappings up to topological conjugacy.
Virtual Estimator for Piecewise Linear Systems Based on Observability Analysis
Morales-Morales, Cornelio; Adam-Medina, Manuel; Cervantes, Ilse; Vela-Valdés and, Luis G.; García Beltrán, Carlos Daniel
2013-01-01
This article proposes a virtual sensor for piecewise linear systems based on observability analysis that is in function of a commutation law related with the system's outpu. This virtual sensor is also known as a state estimator. Besides, it presents a detector of active mode when the commutation sequences of each linear subsystem are arbitrary and unknown. For the previous, this article proposes a set of virtual estimators that discern the commutation paths of the system and allow estimating their output. In this work a methodology in order to test the observability for piecewise linear systems with discrete time is proposed. An academic example is presented to show the obtained results. PMID:23447007
Mallak, Saed
1996-01-01
Ankara : Department of Mathematics and Institute of Engineering and Sciences of Bilkent University, 1996. Thesis (Master's) -- Bilkent University, 1996. Includes bibliographical references leaves leaf 29 In thi.s work, we studierl the Ergodicilv of Non-Stationary .Markov chains. We gave several e.xainples with different cases. We proved that given a sec[uence of Markov chains such that the limit of this sec|uence is an Ergodic Markov chain, then the limit of the combination ...
Active Learning of Markov Decision Processes for System Verification
DEFF Research Database (Denmark)
Chen, Yingke; Nielsen, Thomas Dyhre
2012-01-01
deterministic Markov decision processes from data by actively guiding the selection of input actions. The algorithm is empirically analyzed by learning system models of slot machines, and it is demonstrated that the proposed active learning procedure can significantly reduce the amount of data required...... demanding process, and this shortcoming has motivated the development of algorithms for automatically learning system models from observed system behaviors. Recently, algorithms have been proposed for learning Markov decision process representations of reactive systems based on alternating sequences...... of input/output observations. While alleviating the problem of manually constructing a system model, the collection/generation of observed system behaviors can also prove demanding. Consequently we seek to minimize the amount of data required. In this paper we propose an algorithm for learning...
Markov Chain Monte Carlo Methods
Indian Academy of Sciences (India)
Keywords. Markov chain; state space; stationary transition probability; stationary distribution; irreducibility; aperiodicity; stationarity; M-H algorithm; proposal distribution; acceptance probability; image processing; Gibbs sampler.
Markov Jump Processes Approximating a Non-Symmetric Generalized Diffusion
International Nuclear Information System (INIS)
Limić, Nedžad
2011-01-01
Consider a non-symmetric generalized diffusion X(⋅) in ℝ d determined by the differential operator A(x) = -Σ ij ∂ i a ij (x)∂ j + Σ i b i (x)∂ i . In this paper the diffusion process is approximated by Markov jump processes X n (⋅), in homogeneous and isotropic grids G n ⊂ℝ d , which converge in distribution in the Skorokhod space D([0,∞),ℝ d ) to the diffusion X(⋅). The generators of X n (⋅) are constructed explicitly. Due to the homogeneity and isotropy of grids, the proposed method for d≥3 can be applied to processes for which the diffusion tensor {a ij (x)} 11 dd fulfills an additional condition. The proposed construction offers a simple method for simulation of sample paths of non-symmetric generalized diffusion. Simulations are carried out in terms of jump processes X n (⋅). For piece-wise constant functions a ij on ℝ d and piece-wise continuous functions a ij on ℝ 2 the construction and principal algorithm are described enabling an easy implementation into a computer code.
DEFF Research Database (Denmark)
Johansen, Søren; Juselius, Katarina; Frydman, Roman
2010-01-01
This paper discusses the I(2) model with breaks in the deterministic component and illustrates with an analysis of German and US prices, exchange rates, and interest rates in 1975--1999. It provides new results on the likelihood ratio test of overidentifying restrictions on the cointegrating...... relations when they contain piecewise linear trends. One important aim of the paper is to demonstrate that a structured I(2) analysis is useful for a better understanding of the empirical regularities underlying the persistent swings in nominal exchange rates, typical in periods of floating exchange rates....
Volchenkov, Dima; Dawin, Jean René
A system for using dice to compose music randomly is known as the musical dice game. The discrete time MIDI models of 804 pieces of classical music written by 29 composers have been encoded into the transition matrices and studied by Markov chains. Contrary to human languages, entropy dominates over redundancy, in the musical dice games based on the compositions of classical music. The maximum complexity is achieved on the blocks consisting of just a few notes (8 notes, for the musical dice games generated over Bach's compositions). First passage times to notes can be used to resolve tonality and feature a composer.
DEFF Research Database (Denmark)
Kohlenbach, Ulrich Wilhelm
2002-01-01
We show that the so-called weak Markov's principle (WMP) which states that every pseudo-positive real number is positive is underivable in E-HA + AC. Since allows one to formalize (atl eastl arge parts of) Bishop's constructive mathematics, this makes it unlikely that WMP can be proved within...... the framework of Bishop-style mathematics (which has been open for about 20 years). The underivability even holds if the ine.ective schema of full comprehension (in all types) for negated formulas (in particular for -free formulas) is added, which allows one to derive the law of excluded middle...
ANALYSIS OF MARKOV NETWORK WITH INCOMES, POSITIVE AND NEGATIVE MESSAGES
Directory of Open Access Journals (Sweden)
V. V. Naumenko
2014-01-01
Full Text Available Markov queuing network with income in transient regime is considered. It has positive and negative messages, which can be used in forecasting income of information and telecommunication systems and networks affected by viruses. Investigations are carried out in the cases when incomes from transitions between network states are deterministic functions dependent on states, or they are random variables with given mean values. In the last case it is assumed that all network systems operate in a high load mode. An example is given.
Deterministic extraction from weak random sources
Gabizon, Ariel
2011-01-01
In this research monograph, the author constructs deterministic extractors for several types of sources, using a methodology of recycling randomness which enables increasing the output length of deterministic extractors to near optimal length.
Deterministic hydrodynamics: Taking blood apart
Davis, John A.; Inglis, David W.; Morton, Keith J.; Lawrence, David A.; Huang, Lotien R.; Chou, Stephen Y.; Sturm, James C.; Austin, Robert H.
2006-10-01
We show the fractionation of whole blood components and isolation of blood plasma with no dilution by using a continuous-flow deterministic array that separates blood components by their hydrodynamic size, independent of their mass. We use the technology we developed of deterministic arrays which separate white blood cells, red blood cells, and platelets from blood plasma at flow velocities of 1,000 μm/sec and volume rates up to 1 μl/min. We verified by flow cytometry that an array using focused injection removed 100% of the lymphocytes and monocytes from the main red blood cell and platelet stream. Using a second design, we demonstrated the separation of blood plasma from the blood cells (white, red, and platelets) with virtually no dilution of the plasma and no cellular contamination of the plasma. cells | plasma | separation | microfabrication
ICRP (1991) and deterministic effects
International Nuclear Information System (INIS)
Mole, R.H.
1992-01-01
A critical review of ICRP Publication 60 (1991) shows that considerable revisions are needed in both language and thinking about deterministic effects (DE). ICRP (1991) makes a welcome and clear distinction between change, caused by irradiation; damage, some degree of deleterious change, for example to cells, but not necessarily deleterious to the exposed individual; harm, clinically observable deleterious effects expressed in individuals or their descendants; and detriment, a complex concept combining the probability, severity and time of expression of harm (para42). (All added emphases come from the author.) Unfortunately these distinctions are not carried through into the discussion of deterministic effects (DE) and two important terms are left undefined. Presumably effect may refer to change, damage, harm or detriment, according to context. Clinically observable is also undefined although its meaning is crucial to any consideration of DE since DE are defined as causing observable harm (para 20). (Author)
Random skew plane partitions with a piecewise periodic back wall
DEFF Research Database (Denmark)
Boutillier, Cedric; Mkrtchyan, Sevak; Reshetikhin, Nicolai
Random skew plane partitions of large size distributed according to an appropriately scaled Schur process develop limit shapes. In the present work we consider the limit of large random skew plane partitions where the inner boundary approaches a piecewise linear curve with non-lattice slopes. Muc...
Behavioral and macro modeling using piecewise linear techniques
Kruiskamp, M.W.; Leenaerts, D.M.W.; Antao, B.
1998-01-01
In this paper we will demonstrate that most digital, analog as well as behavioral components can be described using piecewise linear approximations of their real behavior. This leads to several advantages from the viewpoint of simulation. We will also give a method to store the resulting linear
Piecewise adiabatic following in non-Hermitian cycling
Gong, Jiangbin; Wang, Qing-hai
2018-05-01
The time evolution of periodically driven non-Hermitian systems is in general nonunitary but can be stable. It is hence of considerable interest to examine the adiabatic following dynamics in periodically driven non-Hermitian systems. We show in this work the possibility of piecewise adiabatic following interrupted by hopping between instantaneous system eigenstates. This phenomenon is first observed in a computational model and then theoretically explained, using an exactly solvable model, in terms of the Stokes phenomenon. In the latter case, the piecewise adiabatic following is shown to be a genuine critical behavior and the precise phase boundary in the parameter space is located. Interestingly, the critical boundary for piecewise adiabatic following is found to be unrelated to the domain for exceptional points. To characterize the adiabatic following dynamics, we also advocate a simple definition of the Aharonov-Anandan (AA) phase for nonunitary cyclic dynamics, which always yields real AA phases. In the slow driving limit, the AA phase reduces to the Berry phase if adiabatic following persists throughout the driving without hopping, but oscillates violently and does not approach any limit in cases of piecewise adiabatic following. This work exposes the rich features of nonunitary dynamics in cases of slow cycling and should stimulate future applications of nonunitary dynamics.
Casimir energy for twisted piecewise uniform bosonic strings
International Nuclear Information System (INIS)
Lu, J.; Huang, B.; Shanghai, Teachers Univ.
1998-01-01
The Casimir energy for the transverse oscillations of piecewise uniform bosonic strings with either untwisted or twisted continuous conditions is discussed. After calculating the analytic values of zeros of the dispersion function under certain conditions, is obtained the Casimir energy for both open and closed bosonic strings composed of two or three segments
Transformations Based on Continuous Piecewise-Affine Velocity Fields
DEFF Research Database (Denmark)
Freifeld, Oren; Hauberg, Søren; Batmanghelich, Kayhan
2017-01-01
We propose novel finite-dimensional spaces of well-behaved transformations. The latter are obtained by (fast and highly-accurate) integration of continuous piecewise-affine velocity fields. The proposed method is simple yet highly expressive, effortlessly handles optional constraints (e.g., volum...
A new chaotic Hopfield network with piecewise linear activation function
International Nuclear Information System (INIS)
Peng-Sheng, Zheng; Wan-Sheng, Tang; Jian-Xiong, Zhang
2010-01-01
This paper presents a new chaotic Hopfield network with a piecewise linear activation function. The dynamic of the network is studied by virtue of the bifurcation diagram, Lyapunov exponents spectrum and power spectrum. Numerical simulations show that the network displays chaotic behaviours for some well selected parameters
A method of piecewise-smooth numerical branching
Czech Academy of Sciences Publication Activity Database
Ligurský, Tomáš; Renard, Y.
2017-01-01
Roč. 97, č. 7 (2017), s. 815-827 ISSN 1521-4001 R&D Projects: GA MŠk LQ1602 Institutional support: RVO:68145535 Keywords : numerical branching * piecewise smooth * steady-state problem * contact problem * Coulomb friction Subject RIV: BA - General Mathematics OBOR OECD: Applied mathematics http://onlinelibrary.wiley.com/doi/10.1002/zamm.201600219/epdf
Combinatorial Vector Fields for Piecewise Affine Control Systems
DEFF Research Database (Denmark)
Wisniewski, Rafal; Larsen, Jesper Abildgaard
2008-01-01
This paper is intended to be a continuation of Habets and van Schuppen (2004) and Habets, Collins and van Schuppen (2006), which address the control problem for piecewise-affine systems on an arbitrary polytope or a family of these. Our work deals with the underlying combinatorics of the underlyi...
On the dynamic analysis of piecewise-linear networks
Heemels, WPMH; Camlibel, MK; Schumacher, JM
Piecewise-linear (PL) modeling is often used to approximate the behavior of nonlinear circuits. One of the possible PL modeling methodologies is based on the linear complementarity problem, and this approach has already been used extensively in the circuits and systems community for static networks.
Computation of piecewise affine terminal cost functions for model predictive control
Brunner, F.D.; Lazar, M.; Allgöwer, F.; Fränzle, Martin; Lygeros, John
2014-01-01
This paper proposes a method for the construction of piecewise affine terminal cost functions for model predictive control (MPC). The terminal cost function is constructed on a predefined partition by solving a linear program for a given piecewise affine system, a stabilizing piecewise affine
International Nuclear Information System (INIS)
Floriani, Elena; Lima, Ricardo; Ourrad, Ouerdia; Spinelli, Lionel
2016-01-01
Highlights: • The flux through a Markov chain of a conserved quantity (mass) is studied. • Mass is supplied by an external source and ends in the absorbing states of the chain. • Meaningful for modeling open systems whose dynamics has a Markov property. • The analytical expression of mass distribution is given for a constant source. • The expression of mass distribution is given for periodic or random sources. - Abstract: In this paper we study the flux through a finite Markov chain of a quantity, that we will call mass, which moves through the states of the chain according to the Markov transition probabilities. Mass is supplied by an external source and accumulates in the absorbing states of the chain. We believe that studying how this conserved quantity evolves through the transient (non-absorbing) states of the chain could be useful for the modelization of open systems whose dynamics has a Markov property.
El Aroudi, Abdelali
2014-05-01
Recently, nonlinearities have been shown to play an important role in increasing the extracted energy of vibration-based energy harvesting systems. In this paper, we study the dynamical behavior of a piecewise linear (PWL) spring-mass-damper system for vibration-based energy harvesting applications. First, we present a continuous time single degree of freedom PWL dynamical model of the system. Different configurations of the PWL model and their corresponding state-space regions are derived. Then, from this PWL model, extensive numerical simulations are carried out by computing time-domain waveforms, state-space trajectories and frequency responses under a deterministic harmonic excitation for different sets of system parameter values. Stability analysis is performed using Floquet theory combined with Filippov method, Poincaré map modeling and finite difference method (FDM). The Floquet multipliers are calculated using these three approaches and a good concordance is obtained among them. The performance of the system in terms of the harvested energy is studied by considering both purely harmonic excitation and a noisy vibrational source. A frequency-domain analysis shows that the harvested energy could be larger at low frequencies as compared to an equivalent linear system, in particular, for relatively low excitation intensities. This could be an advantage for potential use of this system in low frequency ambient vibrational-based energy harvesting applications. © 2014 World Scientific Publishing Company.
Deterministic chaos in entangled eigenstates
Schlegel, K. G.; Förster, S.
2008-05-01
We investigate the problem of deterministic chaos in connection with entangled states using the Bohmian formulation of quantum mechanics. We show for a two particle system in a harmonic oscillator potential, that in a case of entanglement and three energy eigen-values the maximum Lyapunov-parameters of a representative ensemble of trajectories for large times develops to a narrow positive distribution, which indicates nearly complete chaotic dynamics. We also present in short results from two time-dependent systems, the anisotropic and the Rabi oscillator.
Deterministic chaos in entangled eigenstates
Energy Technology Data Exchange (ETDEWEB)
Schlegel, K.G. [Fakultaet fuer Physik, Universitaet Bielefeld, Postfach 100131, D-33501 Bielefeld (Germany)], E-mail: guenter.schlegel@arcor.de; Foerster, S. [Fakultaet fuer Physik, Universitaet Bielefeld, Postfach 100131, D-33501 Bielefeld (Germany)
2008-05-12
We investigate the problem of deterministic chaos in connection with entangled states using the Bohmian formulation of quantum mechanics. We show for a two particle system in a harmonic oscillator potential, that in a case of entanglement and three energy eigen-values the maximum Lyapunov-parameters of a representative ensemble of trajectories for large times develops to a narrow positive distribution, which indicates nearly complete chaotic dynamics. We also present in short results from two time-dependent systems, the anisotropic and the Rabi oscillator.
Deterministic chaos in entangled eigenstates
International Nuclear Information System (INIS)
Schlegel, K.G.; Foerster, S.
2008-01-01
We investigate the problem of deterministic chaos in connection with entangled states using the Bohmian formulation of quantum mechanics. We show for a two particle system in a harmonic oscillator potential, that in a case of entanglement and three energy eigen-values the maximum Lyapunov-parameters of a representative ensemble of trajectories for large times develops to a narrow positive distribution, which indicates nearly complete chaotic dynamics. We also present in short results from two time-dependent systems, the anisotropic and the Rabi oscillator
A deterministic width function model
Directory of Open Access Journals (Sweden)
C. E. Puente
2003-01-01
Full Text Available Use of a deterministic fractal-multifractal (FM geometric method to model width functions of natural river networks, as derived distributions of simple multifractal measures via fractal interpolating functions, is reported. It is first demonstrated that the FM procedure may be used to simulate natural width functions, preserving their most relevant features like their overall shape and texture and their observed power-law scaling on their power spectra. It is then shown, via two natural river networks (Racoon and Brushy creeks in the United States, that the FM approach may also be used to closely approximate existing width functions.
Regeneration and general Markov chains
Directory of Open Access Journals (Sweden)
Vladimir V. Kalashnikov
1994-01-01
Full Text Available Ergodicity, continuity, finite approximations and rare visits of general Markov chains are investigated. The obtained results permit further quantitative analysis of characteristics, such as, rates of convergence, continuity (measured as a distance between perturbed and non-perturbed characteristics, deviations between Markov chains, accuracy of approximations and bounds on the distribution function of the first visit time to a chosen subset, etc. The underlying techniques use the embedding of the general Markov chain into a wide sense regenerative process with the help of splitting construction.
Markov chains theory and applications
Sericola, Bruno
2013-01-01
Markov chains are a fundamental class of stochastic processes. They are widely used to solve problems in a large number of domains such as operational research, computer science, communication networks and manufacturing systems. The success of Markov chains is mainly due to their simplicity of use, the large number of available theoretical results and the quality of algorithms developed for the numerical evaluation of many metrics of interest.The author presents the theory of both discrete-time and continuous-time homogeneous Markov chains. He carefully examines the explosion phenomenon, the
Quadratic Variation by Markov Chains
DEFF Research Database (Denmark)
Hansen, Peter Reinhard; Horel, Guillaume
We introduce a novel estimator of the quadratic variation that is based on the the- ory of Markov chains. The estimator is motivated by some general results concerning filtering contaminated semimartingales. Specifically, we show that filtering can in prin- ciple remove the effects of market...... microstructure noise in a general framework where little is assumed about the noise. For the practical implementation, we adopt the dis- crete Markov chain model that is well suited for the analysis of financial high-frequency prices. The Markov chain framework facilitates simple expressions and elegant analyti...
Hyperchaotic encryption based on multi-scroll piecewise linear Systems
Czech Academy of Sciences Publication Activity Database
García-Martínez, M.; Ontanon-García, L.J.; Campos-Cantón, E.; Čelikovský, Sergej
2015-01-01
Roč. 270, č. 1 (2015), s. 413-424 ISSN 0096-3003 R&D Projects: GA ČR GA13-20433S Institutional support: RVO:67985556 Keywords : Hyperchaotic encryption * Piecewise linear systems * Stream cipher * Pseudo-random bit generator * Chaos theory * Multi-scrollattractors Subject RIV: BC - Control Systems Theory Impact factor: 1.345, year: 2015 http://library.utia.cas.cz/separaty/2015/TR/celikovsky-0446895.pdf
Separability by piecewise testable languages is PTime-complete
Czech Academy of Sciences Publication Activity Database
Masopust, Tomáš
2018-01-01
Roč. 711, February 8 (2018), s. 109-114 ISSN 0304-3975 Institutional support: RVO:67985840 Keywords : separability * piecewise testable languages * complexity Subject RIV: BA - General Mathematics OBOR OECD: Computer science s, information science , bioinformathics (hardware development to be 2.2, social aspect to be 5.8) Impact factor: 0.698, year: 2016 https://www. science direct.com/ science /article/pii/S0304397517308319?via%3Dihub
Lyapunov exponent and topological entropy plateaus in piecewise linear maps
International Nuclear Information System (INIS)
Botella-Soler, V; Oteo, J A; Ros, J; Glendinning, P
2013-01-01
We consider a two-parameter family of piecewise linear maps in which the moduli of the two slopes take different values. We provide numerical evidence of the existence of some parameter regions in which the Lyapunov exponent and the topological entropy remain constant. Analytical proof of this phenomenon is also given for certain cases. Surprisingly however, the systems with that property are not conjugate as we prove by using kneading theory. (paper)
Dynamic logic architecture based on piecewise-linear systems
International Nuclear Information System (INIS)
Peng Haipeng; Liu Fei; Li Lixiang; Yang Yixian; Wang Xue
2010-01-01
This Letter explores piecewise-linear systems to construct dynamic logic architecture. The proposed schemes can discriminate the two input signals and obtain 16 kinds of logic operations by different combinations of parameters and conditions for determining the output. Each logic cell performs more flexibly, that makes it possible to achieve complex logic operations more simply and construct computing architecture with less logic cells. We also analyze the various performances of our schemes under different conditions and the characteristics of these schemes.
Rectification of aerial images using piecewise linear transformation
International Nuclear Information System (INIS)
Liew, L H; Lee, B Y; Wang, Y C; Cheah, W S
2014-01-01
Aerial images are widely used in various activities by providing visual records. This type of remotely sensed image is helpful in generating digital maps, managing ecology, monitoring crop growth and region surveying. Such images could provide insight into areas of interest that have lower altitude, particularly in regions where optical satellite imaging is prevented due to cloudiness. Aerial images captured using a non-metric cameras contain real details of the images as well as unexpected distortions. Distortions would affect the actual length, direction and shape of objects in the images. There are many sources that could cause distortions such as lens, earth curvature, topographic relief and the attitude of the aircraft that is used to carry the camera. These distortions occur differently, collectively and irregularly in the entire image. Image rectification is an essential image pre-processing step to eliminate or at least reduce the effect of distortions. In this paper, a non-parametric approach with piecewise linear transformation is investigated in rectifying distorted aerial images. The non-parametric approach requires a set of corresponding control points obtained from a reference image and a distorted image. The corresponding control points are then applied with piecewise linear transformation as geometric transformation. Piecewise linear transformation divides the image into regions by triangulation. Different linear transformations are employed separately to triangular regions instead of using a single transformation as the rectification model for the entire image. The result of rectification is evaluated using total root mean square error (RMSE). Experiments show that piecewise linear transformation could assist in improving the limitation of using global transformation to rectify images
Piecewise affine control for fast unmanned ground vehicles
Benine Neto , André; Grand , Christophe
2012-01-01
International audience; Unmanned ground vehicles (UGV) may experience skidding when moving at high speeds, and therefore have its safety jeopardized. For this reason the nonlinear dynamics of lateral tire forces must be taken into account into the design of steering controllers for autonomous vehicles. This paper presents the design of a state feedback piecewise affine controller applied to an UGV to coordinate the steering and torque distribution inputs in order to reduce vehicle skidding on...
On the dynamic analysis of piecewise-linear networks
Heemels, W.P.M.H.; Camlibel, M.K.; Schumacher, J.M.
2002-01-01
Piecewise-linear (PL) modeling is often used to approximate the behavior of nonlinear circuits. One of the possible PL modeling methodologies is based on the linear complementarity problem, and this approach has already been used extensively in the circuits and systems community for static networks. In this paper, the object of study will be dynamic electrical circuits that can be recast as linear complementarity systems, i.e., as interconnections of linear time-invariant differential equatio...
Separability by piecewise testable languages is PTime-complete
Czech Academy of Sciences Publication Activity Database
Masopust, Tomáš
2018-01-01
Roč. 711, February 8 (2018), s. 109-114 ISSN 0304-3975 Institutional support: RVO:67985840 Keywords : separability * piecewise testable languages * complexity Subject RIV: BA - General Mathematics OBOR OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8) Impact factor: 0.698, year: 2016 https://www.sciencedirect.com/science/article/pii/S0304397517308319?via%3Dihub
Markov Chain Monte Carlo Methods
Indian Academy of Sciences (India)
Systat Software Asia-Pacific. Ltd., in Bangalore, where the technical work for the development of the statistical software Systat takes ... In Part 4, we discuss some applications of the Markov ... one can construct the joint probability distribution of.
Confluence reduction for Markov automata
Timmer, Mark; van de Pol, Jan Cornelis; Stoelinga, Mariëlle Ida Antoinette
Markov automata are a novel formalism for specifying systems exhibiting nondeterminism, probabilistic choices and Markovian rates. Recently, the process algebra MAPA was introduced to efficiently model such systems. As always, the state space explosion threatens the analysability of the models
Confluence Reduction for Markov Automata
Timmer, Mark; van de Pol, Jan Cornelis; Stoelinga, Mariëlle Ida Antoinette; Braberman, Victor; Fribourg, Laurent
Markov automata are a novel formalism for specifying systems exhibiting nondeterminism, probabilistic choices and Markovian rates. Recently, the process algebra MAPA was introduced to efficiently model such systems. As always, the state space explosion threatens the analysability of the models
Extracting Markov Models of Peptide Conformational Dynamics from Simulation Data.
Schultheis, Verena; Hirschberger, Thomas; Carstens, Heiko; Tavan, Paul
2005-07-01
A high-dimensional time series obtained by simulating a complex and stochastic dynamical system (like a peptide in solution) may code an underlying multiple-state Markov process. We present a computational approach to most plausibly identify and reconstruct this process from the simulated trajectory. Using a mixture of normal distributions we first construct a maximum likelihood estimate of the point density associated with this time series and thus obtain a density-oriented partition of the data space. This discretization allows us to estimate the transfer operator as a matrix of moderate dimension at sufficient statistics. A nonlinear dynamics involving that matrix and, alternatively, a deterministic coarse-graining procedure are employed to construct respective hierarchies of Markov models, from which the model most plausibly mapping the generating stochastic process is selected by consideration of certain observables. Within both procedures the data are classified in terms of prototypical points, the conformations, marking the various Markov states. As a typical example, the approach is applied to analyze the conformational dynamics of a tripeptide in solution. The corresponding high-dimensional time series has been obtained from an extended molecular dynamics simulation.
Integrated Deterministic-Probabilistic Safety Assessment Methodologies
Energy Technology Data Exchange (ETDEWEB)
Kudinov, P.; Vorobyev, Y.; Sanchez-Perea, M.; Queral, C.; Jimenez Varas, G.; Rebollo, M. J.; Mena, L.; Gomez-Magin, J.
2014-02-01
IDPSA (Integrated Deterministic-Probabilistic Safety Assessment) is a family of methods which use tightly coupled probabilistic and deterministic approaches to address respective sources of uncertainties, enabling Risk informed decision making in a consistent manner. The starting point of the IDPSA framework is that safety justification must be based on the coupling of deterministic (consequences) and probabilistic (frequency) considerations to address the mutual interactions between stochastic disturbances (e.g. failures of the equipment, human actions, stochastic physical phenomena) and deterministic response of the plant (i.e. transients). This paper gives a general overview of some IDPSA methods as well as some possible applications to PWR safety analyses. (Author)
Complex motion of elevators in piecewise map model combined with circle map
Nagatani, Takashi
2013-11-01
We study the dynamic behavior in the elevator traffic controlled by capacity when the inflow rate of passengers into elevators varies periodically with time. The dynamics of elevators is described by the piecewise map model combined with the circle map. The motion of the elevators depends on the inflow rate, its period, and the number of elevators. The motion in the piecewise map model combined with the circle map shows a complex behavior different from the motion in the piecewise map model.
Bottom-up learning of hierarchical models in a class of deterministic POMDP environments
Directory of Open Access Journals (Sweden)
Itoh Hideaki
2015-09-01
Full Text Available The theory of partially observable Markov decision processes (POMDPs is a useful tool for developing various intelligent agents, and learning hierarchical POMDP models is one of the key approaches for building such agents when the environments of the agents are unknown and large. To learn hierarchical models, bottom-up learning methods in which learning takes place in a layer-by-layer manner from the lowest to the highest layer are already extensively used in some research fields such as hidden Markov models and neural networks. However, little attention has been paid to bottom-up approaches for learning POMDP models. In this paper, we present a novel bottom-up learning algorithm for hierarchical POMDP models and prove that, by using this algorithm, a perfect model (i.e., a model that can perfectly predict future observations can be learned at least in a class of deterministic POMDP environments
International Nuclear Information System (INIS)
Hong-Bin, Zhang; Jian-Wei, Xia; Yong-Bin, Yu; Chuang-Yin, Dang
2010-01-01
This paper investigates the chaos synchronisation between two coupled chaotic Chua's circuits. The sufficient condition presented by linear matrix inequalities (LMIs) of global asymptotic synchronisation is attained based on piecewise quadratic Lyapunov functions. First, we obtain the piecewise linear differential inclusions (pwLDIs) model of synchronisation error dynamics, then we design a switching (piecewise-linear) feedback control law to stabilise it based on the piecewise quadratic Laypunov functions. Then we give some numerical simulations to demonstrate the effectiveness of our theoretical results
A Parallel Encryption Algorithm Based on Piecewise Linear Chaotic Map
Directory of Open Access Journals (Sweden)
Xizhong Wang
2013-01-01
Full Text Available We introduce a parallel chaos-based encryption algorithm for taking advantage of multicore processors. The chaotic cryptosystem is generated by the piecewise linear chaotic map (PWLCM. The parallel algorithm is designed with a master/slave communication model with the Message Passing Interface (MPI. The algorithm is suitable not only for multicore processors but also for the single-processor architecture. The experimental results show that the chaos-based cryptosystem possesses good statistical properties. The parallel algorithm provides much better performance than the serial ones and would be useful to apply in encryption/decryption file with large size or multimedia.
Piecewise linear manifolds: Einstein metrics and Ricci flows
International Nuclear Information System (INIS)
Schrader, Robert
2016-01-01
This article provides an attempt to extend concepts from the theory of Riemannian manifolds to piecewise linear (p.l.) spaces. In particular we propose an analogue of the Ricci tensor, which we give the name of an Einstein vector field . On a given set of p.l. spaces we define and discuss (normalized) Einstein flows. p.l. Einstein metrics are defined and examples are provided. Criteria for flows to approach Einstein metrics are formulated. Second variations of the total scalar curvature at a specific Einstein space are calculated. (paper)
Cardinal Basis Piecewise Hermite Interpolation on Fuzzy Data
Directory of Open Access Journals (Sweden)
H. Vosoughi
2016-01-01
Full Text Available A numerical method along with explicit construction to interpolation of fuzzy data through the extension principle results by widely used fuzzy-valued piecewise Hermite polynomial in general case based on the cardinal basis functions, which satisfy a vanishing property on the successive intervals, has been introduced here. We have provided a numerical method in full detail using the linear space notions for calculating the presented method. In order to illustrate the method in computational examples, we take recourse to three prime cases: linear, cubic, and quintic.
Exact treatment of mode locking for a piecewise linear map
International Nuclear Information System (INIS)
Ding, E.J.; Hemmer, P.C.
1987-01-01
A piecewise linear map with one discontinuity is studied by analytic means in the two-dimensional parameter space. When the slope of the map is less than unity, periodic orbits are present, and they give the precise symbolic dynamic classification of these. The localization of the periodic domains in parameter space is given by closed expressions. The winding number forms a devil's terrace, a two-dimensional function whose cross sections are complete devil's staircases. In such a cross section the complementary set to the periodic intervals is a Cantor set with dimension D = 0
Relaxation Methods for Strictly Convex Regularizations of Piecewise Linear Programs
International Nuclear Information System (INIS)
Kiwiel, K. C.
1998-01-01
We give an algorithm for minimizing the sum of a strictly convex function and a convex piecewise linear function. It extends several dual coordinate ascent methods for large-scale linearly constrained problems that occur in entropy maximization, quadratic programming, and network flows. In particular, it may solve exact penalty versions of such (possibly inconsistent) problems, and subproblems of bundle methods for nondifferentiable optimization. It is simple, can exploit sparsity, and in certain cases is highly parallelizable. Its global convergence is established in the recent framework of B -functions (generalized Bregman functions)
Configuration Selection for Reconfigurable Control of Piecewise Affine Systems
DEFF Research Database (Denmark)
Tabatabaeipour, Mojtaba; Gholami, M.; Bak, T.
2015-01-01
the recongurability of the system and the optimal conguration in the architecture design phase. A recongurable control must ensure stability of the recongured system and, if possible, a graceful degradation in the performance. Therefore, in the proposed recongurability analysis, we consider both stabilizability......In this paper, the problem of conguration selection i.e. sensor/actuator placement for piecewise ane (PWA) systems subject to both sensor and actuator faults is considered. A method is proposed that provides a tool for the design phase to decide about the optimal placement of sensor/actuators where...... and performance of the system. The efficiency of the proposed method is demonstrated on several numerical examples...
Piecewise-parabolic methods for astrophysical fluid dynamics
International Nuclear Information System (INIS)
Woodward, P.R.
1983-01-01
A general description of some modern numerical techniques for the simulation of astrophysical fluid flow is presented. The methods are introduced with a thorough discussion of the especially simple case of advection. Attention is focused on the piecewise-parabolic method (PPM). A description of the SLIC method for treating multifluid problems is also given. The discussion is illustrated by a number of advection and hydrodynamics test problems. Finally, a study of Kelvin-Helmholtz instability of supersonic jets using PPM with SLIC fluid interfaces is presented
Liu, Xiangdong; Li, Qingze; Pan, Jianxin
2018-06-01
Modern medical studies show that chemotherapy can help most cancer patients, especially for those diagnosed early, to stabilize their disease conditions from months to years, which means the population of tumor cells remained nearly unchanged in quite a long time after fighting against immune system and drugs. In order to better understand the dynamics of tumor-immune responses under chemotherapy, deterministic and stochastic differential equation models are constructed to characterize the dynamical change of tumor cells and immune cells in this paper. The basic dynamical properties, such as boundedness, existence and stability of equilibrium points, are investigated in the deterministic model. Extended stochastic models include stochastic differential equations (SDEs) model and continuous-time Markov chain (CTMC) model, which accounts for the variability in cellular reproduction, growth and death, interspecific competitions, and immune response to chemotherapy. The CTMC model is harnessed to estimate the extinction probability of tumor cells. Numerical simulations are performed, which confirms the obtained theoretical results.
Markov Networks in Evolutionary Computation
Shakya, Siddhartha
2012-01-01
Markov networks and other probabilistic graphical modes have recently received an upsurge in attention from Evolutionary computation community, particularly in the area of Estimation of distribution algorithms (EDAs). EDAs have arisen as one of the most successful experiences in the application of machine learning methods in optimization, mainly due to their efficiency to solve complex real-world optimization problems and their suitability for theoretical analysis. This book focuses on the different steps involved in the conception, implementation and application of EDAs that use Markov networks, and undirected models in general. It can serve as a general introduction to EDAs but covers also an important current void in the study of these algorithms by explaining the specificities and benefits of modeling optimization problems by means of undirected probabilistic models. All major developments to date in the progressive introduction of Markov networks based EDAs are reviewed in the book. Hot current researc...
Markov chains and mixing times
Levin, David A; Wilmer, Elizabeth L
2009-01-01
This book is an introduction to the modern approach to the theory of Markov chains. The main goal of this approach is to determine the rate of convergence of a Markov chain to the stationary distribution as a function of the size and geometry of the state space. The authors develop the key tools for estimating convergence times, including coupling, strong stationary times, and spectral methods. Whenever possible, probabilistic methods are emphasized. The book includes many examples and provides brief introductions to some central models of statistical mechanics. Also provided are accounts of r
Markov Models for Handwriting Recognition
Plotz, Thomas
2011-01-01
Since their first inception, automatic reading systems have evolved substantially, yet the recognition of handwriting remains an open research problem due to its substantial variation in appearance. With the introduction of Markovian models to the field, a promising modeling and recognition paradigm was established for automatic handwriting recognition. However, no standard procedures for building Markov model-based recognizers have yet been established. This text provides a comprehensive overview of the application of Markov models in the field of handwriting recognition, covering both hidden
Chaotic dynamics and diffusion in a piecewise linear equation
International Nuclear Information System (INIS)
Shahrear, Pabel; Glass, Leon; Edwards, Rod
2015-01-01
Genetic interactions are often modeled by logical networks in which time is discrete and all gene activity states update simultaneously. However, there is no synchronizing clock in organisms. An alternative model assumes that the logical network is preserved and plays a key role in driving the dynamics in piecewise nonlinear differential equations. We examine dynamics in a particular 4-dimensional equation of this class. In the equation, two of the variables form a negative feedback loop that drives a second negative feedback loop. By modifying the original equations by eliminating exponential decay, we generate a modified system that is amenable to detailed analysis. In the modified system, we can determine in detail the Poincaré (return) map on a cross section to the flow. By analyzing the eigenvalues of the map for the different trajectories, we are able to show that except for a set of measure 0, the flow must necessarily have an eigenvalue greater than 1 and hence there is sensitive dependence on initial conditions. Further, there is an irregular oscillation whose amplitude is described by a diffusive process that is well-modeled by the Irwin-Hall distribution. There is a large class of other piecewise-linear networks that might be analyzed using similar methods. The analysis gives insight into possible origins of chaotic dynamics in periodically forced dynamical systems
Chaotic dynamics and diffusion in a piecewise linear equation
Shahrear, Pabel; Glass, Leon; Edwards, Rod
2015-03-01
Genetic interactions are often modeled by logical networks in which time is discrete and all gene activity states update simultaneously. However, there is no synchronizing clock in organisms. An alternative model assumes that the logical network is preserved and plays a key role in driving the dynamics in piecewise nonlinear differential equations. We examine dynamics in a particular 4-dimensional equation of this class. In the equation, two of the variables form a negative feedback loop that drives a second negative feedback loop. By modifying the original equations by eliminating exponential decay, we generate a modified system that is amenable to detailed analysis. In the modified system, we can determine in detail the Poincaré (return) map on a cross section to the flow. By analyzing the eigenvalues of the map for the different trajectories, we are able to show that except for a set of measure 0, the flow must necessarily have an eigenvalue greater than 1 and hence there is sensitive dependence on initial conditions. Further, there is an irregular oscillation whose amplitude is described by a diffusive process that is well-modeled by the Irwin-Hall distribution. There is a large class of other piecewise-linear networks that might be analyzed using similar methods. The analysis gives insight into possible origins of chaotic dynamics in periodically forced dynamical systems.
Deterministic and unambiguous dense coding
International Nuclear Information System (INIS)
Wu Shengjun; Cohen, Scott M.; Sun Yuqing; Griffiths, Robert B.
2006-01-01
Optimal dense coding using a partially-entangled pure state of Schmidt rank D and a noiseless quantum channel of dimension D is studied both in the deterministic case where at most L d messages can be transmitted with perfect fidelity, and in the unambiguous case where when the protocol succeeds (probability τ x ) Bob knows for sure that Alice sent message x, and when it fails (probability 1-τ x ) he knows it has failed. Alice is allowed any single-shot (one use) encoding procedure, and Bob any single-shot measurement. For D≤D a bound is obtained for L d in terms of the largest Schmidt coefficient of the entangled state, and is compared with published results by Mozes et al. [Phys. Rev. A71, 012311 (2005)]. For D>D it is shown that L d is strictly less than D 2 unless D is an integer multiple of D, in which case uniform (maximal) entanglement is not needed to achieve the optimal protocol. The unambiguous case is studied for D≤D, assuming τ x >0 for a set of DD messages, and a bound is obtained for the average . A bound on the average requires an additional assumption of encoding by isometries (unitaries when D=D) that are orthogonal for different messages. Both bounds are saturated when τ x is a constant independent of x, by a protocol based on one-shot entanglement concentration. For D>D it is shown that (at least) D 2 messages can be sent unambiguously. Whether unitary (isometric) encoding suffices for optimal protocols remains a major unanswered question, both for our work and for previous studies of dense coding using partially-entangled states, including noisy (mixed) states
Deterministic quantitative risk assessment development
Energy Technology Data Exchange (ETDEWEB)
Dawson, Jane; Colquhoun, Iain [PII Pipeline Solutions Business of GE Oil and Gas, Cramlington Northumberland (United Kingdom)
2009-07-01
Current risk assessment practice in pipeline integrity management is to use a semi-quantitative index-based or model based methodology. This approach has been found to be very flexible and provide useful results for identifying high risk areas and for prioritizing physical integrity assessments. However, as pipeline operators progressively adopt an operating strategy of continual risk reduction with a view to minimizing total expenditures within safety, environmental, and reliability constraints, the need for quantitative assessments of risk levels is becoming evident. Whereas reliability based quantitative risk assessments can be and are routinely carried out on a site-specific basis, they require significant amounts of quantitative data for the results to be meaningful. This need for detailed and reliable data tends to make these methods unwieldy for system-wide risk k assessment applications. This paper describes methods for estimating risk quantitatively through the calibration of semi-quantitative estimates to failure rates for peer pipeline systems. The methods involve the analysis of the failure rate distribution, and techniques for mapping the rate to the distribution of likelihoods available from currently available semi-quantitative programs. By applying point value probabilities to the failure rates, deterministic quantitative risk assessment (QRA) provides greater rigor and objectivity than can usually be achieved through the implementation of semi-quantitative risk assessment results. The method permits a fully quantitative approach or a mixture of QRA and semi-QRA to suit the operator's data availability and quality, and analysis needs. For example, consequence analysis can be quantitative or can address qualitative ranges for consequence categories. Likewise, failure likelihoods can be output as classical probabilities or as expected failure frequencies as required. (author)
Deterministic computation of functional integrals
International Nuclear Information System (INIS)
Lobanov, Yu.Yu.
1995-09-01
A new method of numerical integration in functional spaces is described. This method is based on the rigorous definition of a functional integral in complete separable metric space and on the use of approximation formulas which we constructed for this kind of integral. The method is applicable to solution of some partial differential equations and to calculation of various characteristics in quantum physics. No preliminary discretization of space and time is required in this method, as well as no simplifying assumptions like semi-classical, mean field approximations, collective excitations, introduction of ''short-time'' propagators, etc are necessary in our approach. The constructed approximation formulas satisfy the condition of being exact on a given class of functionals, namely polynomial functionals of a given degree. The employment of these formulas replaces the evaluation of a functional integral by computation of the ''ordinary'' (Riemannian) integral of a low dimension, thus allowing to use the more preferable deterministic algorithms (normally - Gaussian quadratures) in computations rather than traditional stochastic (Monte Carlo) methods which are commonly used for solution of the problem under consideration. The results of application of the method to computation of the Green function of the Schroedinger equation in imaginary time as well as the study of some models of Euclidean quantum mechanics are presented. The comparison with results of other authors shows that our method gives significant (by an order of magnitude) economy of computer time and memory versus other known methods while providing the results with the same or better accuracy. The funcitonal measure of the Gaussian type is considered and some of its particular cases, namely conditional Wiener measure in quantum statistical mechanics and functional measure in a Schwartz distribution space in two-dimensional quantum field theory are studied in detail. Numerical examples demonstrating the
Consistency and refinement for Interval Markov Chains
DEFF Research Database (Denmark)
Delahaye, Benoit; Larsen, Kim Guldstrand; Legay, Axel
2012-01-01
Interval Markov Chains (IMC), or Markov Chains with probability intervals in the transition matrix, are the base of a classic specification theory for probabilistic systems [18]. The standard semantics of IMCs assigns to a specification the set of all Markov Chains that satisfy its interval...
Katoen, Joost P.; Maneesh Khattri, M.; Zapreev, I.S.; Zapreev, I.S.
2005-01-01
This short tool paper introduces MRMC, a model checker for discrete-time and continuous-time Markov reward models. It supports reward extensions of PCTL and CSL, and allows for the automated verification of properties concerning long-run and instantaneous rewards as well as cumulative rewards. In
Adaptive Partially Hidden Markov Models
DEFF Research Database (Denmark)
Forchhammer, Søren Otto; Rasmussen, Tage
1996-01-01
Partially Hidden Markov Models (PHMM) have recently been introduced. The transition and emission probabilities are conditioned on the past. In this report, the PHMM is extended with a multiple token version. The different versions of the PHMM are applied to bi-level image coding....
Markov Decision Processes in Practice
Boucherie, Richardus J.; van Dijk, N.M.
2017-01-01
It is over 30 years ago since D.J. White started his series of surveys on practical applications of Markov decision processes (MDP), over 20 years after the phenomenal book by Martin Puterman on the theory of MDP, and over 10 years since Eugene A. Feinberg and Adam Shwartz published their Handbook
The exit-time problem for a Markov jump process
Burch, N.; D'Elia, M.; Lehoucq, R. B.
2014-12-01
The purpose of this paper is to consider the exit-time problem for a finite-range Markov jump process, i.e, the distance the particle can jump is bounded independent of its location. Such jump diffusions are expedient models for anomalous transport exhibiting super-diffusion or nonstandard normal diffusion. We refer to the associated deterministic equation as a volume-constrained nonlocal diffusion equation. The volume constraint is the nonlocal analogue of a boundary condition necessary to demonstrate that the nonlocal diffusion equation is well-posed and is consistent with the jump process. A critical aspect of the analysis is a variational formulation and a recently developed nonlocal vector calculus. This calculus allows us to pose nonlocal backward and forward Kolmogorov equations, the former equation granting the various moments of the exit-time distribution.
Passive Fault-tolerant Control of Discrete-time Piecewise Affine Systems against Actuator Faults
DEFF Research Database (Denmark)
Tabatabaeipour, Seyed Mojtaba; Izadi-Zamanabadi, Roozbeh; Bak, Thomas
2012-01-01
In this paper, we propose a new method for passive fault-tolerant control of discrete time piecewise affine systems. Actuator faults are considered. A reliable piecewise linear quadratic regulator (LQR) state feedback is designed such that it can tolerate actuator faults. A sufficient condition f...... is illustrated on a numerical example and a two degree of freedom helicopter....
Piecewise Linear-Linear Latent Growth Mixture Models with Unknown Knots
Kohli, Nidhi; Harring, Jeffrey R.; Hancock, Gregory R.
2013-01-01
Latent growth curve models with piecewise functions are flexible and useful analytic models for investigating individual behaviors that exhibit distinct phases of development in observed variables. As an extension of this framework, this study considers a piecewise linear-linear latent growth mixture model (LGMM) for describing segmented change of…
Deterministic secure communication protocol without using entanglement
Cai, Qing-yu
2003-01-01
We show a deterministic secure direct communication protocol using single qubit in mixed state. The security of this protocol is based on the security proof of BB84 protocol. It can be realized with current technologies.
Deterministic chaos in the processor load
International Nuclear Information System (INIS)
Halbiniak, Zbigniew; Jozwiak, Ireneusz J.
2007-01-01
In this article we present the results of research whose purpose was to identify the phenomenon of deterministic chaos in the processor load. We analysed the time series of the processor load during efficiency tests of database software. Our research was done on a Sparc Alpha processor working on the UNIX Sun Solaris 5.7 operating system. The conducted analyses proved the presence of the deterministic chaos phenomenon in the processor load in this particular case
Piecewise Polynomial Fitting with Trend Item Removal and Its Application in a Cab Vibration Test
Directory of Open Access Journals (Sweden)
Wu Ren
2018-01-01
Full Text Available The trend item of a long-term vibration signal is difficult to remove. This paper proposes a piecewise integration method to remove trend items. Examples of direct integration without trend item removal, global integration after piecewise polynomial fitting with trend item removal, and direct integration after piecewise polynomial fitting with trend item removal were simulated. The results showed that direct integration of the fitted piecewise polynomial provided greater acceleration and displacement precision than the other two integration methods. A vibration test was then performed on a special equipment cab. The results indicated that direct integration by piecewise polynomial fitting with trend item removal was highly consistent with the measured signal data. However, the direct integration method without trend item removal resulted in signal distortion. The proposed method can help with frequency domain analysis of vibration signals and modal parameter identification for such equipment.
Risk-based and deterministic regulation
International Nuclear Information System (INIS)
Fischer, L.E.; Brown, N.W.
1995-07-01
Both risk-based and deterministic methods are used for regulating the nuclear industry to protect the public safety and health from undue risk. The deterministic method is one where performance standards are specified for each kind of nuclear system or facility. The deterministic performance standards address normal operations and design basis events which include transient and accident conditions. The risk-based method uses probabilistic risk assessment methods to supplement the deterministic one by (1) addressing all possible events (including those beyond the design basis events), (2) using a systematic, logical process for identifying and evaluating accidents, and (3) considering alternative means to reduce accident frequency and/or consequences. Although both deterministic and risk-based methods have been successfully applied, there is need for a better understanding of their applications and supportive roles. This paper describes the relationship between the two methods and how they are used to develop and assess regulations in the nuclear industry. Preliminary guidance is suggested for determining the need for using risk based methods to supplement deterministic ones. However, it is recommended that more detailed guidance and criteria be developed for this purpose
An Improved Piecewise Linear Chaotic Map Based Image Encryption Algorithm
Directory of Open Access Journals (Sweden)
Yuping Hu
2014-01-01
Full Text Available An image encryption algorithm based on improved piecewise linear chaotic map (MPWLCM model was proposed. The algorithm uses the MPWLCM to permute and diffuse plain image simultaneously. Due to the sensitivity to initial key values, system parameters, and ergodicity in chaotic system, two pseudorandom sequences are designed and used in the processes of permutation and diffusion. The order of processing pixels is not in accordance with the index of pixels, but it is from beginning or end alternately. The cipher feedback was introduced in diffusion process. Test results and security analysis show that not only the scheme can achieve good encryption results but also its key space is large enough to resist against brute attack.
Optimal Piecewise-Linear Approximation of the Quadratic Chaotic Dynamics
Directory of Open Access Journals (Sweden)
J. Petrzela
2012-04-01
Full Text Available This paper shows the influence of piecewise-linear approximation on the global dynamics associated with autonomous third-order dynamical systems with the quadratic vector fields. The novel method for optimal nonlinear function approximation preserving the system behavior is proposed and experimentally verified. This approach is based on the calculation of the state attractor metric dimension inside a stochastic optimization routine. The approximated systems are compared to the original by means of the numerical integration. Real electronic circuits representing individual dynamical systems are derived using classical as well as integrator-based synthesis and verified by time-domain analysis in Orcad Pspice simulator. The universality of the proposed method is briefly discussed, especially from the viewpoint of the higher-order dynamical systems. Future topics and perspectives are also provided
A family of quantization based piecewise linear filter networks
DEFF Research Database (Denmark)
Sørensen, John Aasted
1992-01-01
A family of quantization-based piecewise linear filter networks is proposed. For stationary signals, a filter network from this family is a generalization of the classical Wiener filter with an input signal and a desired response. The construction of the filter network is based on quantization...... of the input signal x(n) into quantization classes. With each quantization class is associated a linear filter. The filtering at time n is carried out by the filter belonging to the actual quantization class of x(n ) and the filters belonging to the neighbor quantization classes of x(n) (regularization......). This construction leads to a three-layer filter network. The first layer consists of the quantization class filters for the input signal. The second layer carries out the regularization between neighbor quantization classes, and the third layer constitutes a decision of quantization class from where the resulting...
Linear response formula for piecewise expanding unimodal maps
International Nuclear Information System (INIS)
Baladi, Viviane; Smania, Daniel
2008-01-01
The average R(t) = ∫φdμ t of a smooth function ψ with respect to the SRB measure μ t of a smooth one-parameter family f t of piecewise expanding interval maps is not always Lipschitz (Baladi 2007 Commun. Math. Phys. 275 839–59, Mazzolena 2007 Master's Thesis Rome 2, Tor Vergata). We prove that if f t is tangent to the topological class of f, and if ∂ t f t | t=0 = X circle f, then R(t) is differentiable at zero, and R'(0) coincides with the resummation proposed (Baladi 2007) of the (a priori divergent) series given by Ruelle's conjecture. In fact, we show that t map μ t is differentiable within Radon measures. Linear response is violated if and only if f t is transversal to the topological class of f
Hash function based on piecewise nonlinear chaotic map
International Nuclear Information System (INIS)
Akhavan, A.; Samsudin, A.; Akhshani, A.
2009-01-01
Chaos-based cryptography appeared recently in the early 1990s as an original application of nonlinear dynamics in the chaotic regime. In this paper, an algorithm for one-way hash function construction based on piecewise nonlinear chaotic map with a variant probability parameter is proposed. Also the proposed algorithm is an attempt to present a new chaotic hash function based on multithreaded programming. In this chaotic scheme, the message is connected to the chaotic map using probability parameter and other parameters of chaotic map such as control parameter and initial condition, so that the generated hash value is highly sensitive to the message. Simulation results indicate that the proposed algorithm presented several interesting features, such as high flexibility, good statistical properties, high key sensitivity and message sensitivity. These properties make the scheme a suitable choice for practical applications.
Piecewise Polynomial Aggregation as Preprocessing for Data Numerical Modeling
Dobronets, B. S.; Popova, O. A.
2018-05-01
Data aggregation issues for numerical modeling are reviewed in the present study. The authors discuss data aggregation procedures as preprocessing for subsequent numerical modeling. To calculate the data aggregation, the authors propose using numerical probabilistic analysis (NPA). An important feature of this study is how the authors represent the aggregated data. The study shows that the offered approach to data aggregation can be interpreted as the frequency distribution of a variable. To study its properties, the density function is used. For this purpose, the authors propose using the piecewise polynomial models. A suitable example of such approach is the spline. The authors show that their approach to data aggregation allows reducing the level of data uncertainty and significantly increasing the efficiency of numerical calculations. To demonstrate the degree of the correspondence of the proposed methods to reality, the authors developed a theoretical framework and considered numerical examples devoted to time series aggregation.
2D discontinuous piecewise linear map: Emergence of fashion cycles.
Gardini, L; Sushko, I; Matsuyama, K
2018-05-01
We consider a discrete-time version of the continuous-time fashion cycle model introduced in Matsuyama, 1992. Its dynamics are defined by a 2D discontinuous piecewise linear map depending on three parameters. In the parameter space of the map periodicity, regions associated with attracting cycles of different periods are organized in the period adding and period incrementing bifurcation structures. The boundaries of all the periodicity regions related to border collision bifurcations are obtained analytically in explicit form. We show the existence of several partially overlapping period incrementing structures, that is, a novelty for the considered class of maps. Moreover, we show that if the time-delay in the discrete time formulation of the model shrinks to zero, the number of period incrementing structures tends to infinity and the dynamics of the discrete time fashion cycle model converges to those of continuous-time fashion cycle model.
Long characteristics with piecewise linear sources designed for unstructured grids
International Nuclear Information System (INIS)
Pandya, Tara M.; Adams, Marvin L.; Hawkins, W. Daryl
2011-01-01
We present a method of long characteristics (MOC or LC) that employs a piece-wise linear (PWL) finite-element representation of the total source in each cell. PWL basis functions were designed to allow discontinuous finite-element methods (DFEMs) and characteristic methods to obtain accurate solutions in optically thick diffusive regions with polygonal (2D) or polyhedral (3D) cells. Our work is motivated by the following observations. Our PWL-LC should reproduce the excellent diffusion-limit behavior of the PWL DFEM but should be more accurate in streaming regions. As an LC method it also offer the potential for improved performance of transport sweeps on massively parallel architectures, because it allows face-based and track-based sweeps in addition to cell-based. We have implemented the two-dimensional (x, y) polygonal-cell version of this method in the parallel transport code PDT. The rectangular-grid results shown here demonstrate that the method with PWL sources is accurate for thick diffusive problems, for which methods with piece-wise constant or higher-order polynomial sources fail. Our results also demonstrate that the PWL-LC method is more accurate than the PWL-DFEM in streaming dominated steady-state problems. We discuss options for time discretization and present results from time-dependent problems that illustrate pros and cons of some options. Our results suggest that the most accurate solutions will be obtained via long characteristics in space and time but that less memory-intensive treatments can provide MOC solutions that are at least as robust and accurate as those obtained by PWL-DFEM. (author)
Markov chains and mixing times
Levin, David A
2017-01-01
Markov Chains and Mixing Times is a magical book, managing to be both friendly and deep. It gently introduces probabilistic techniques so that an outsider can follow. At the same time, it is the first book covering the geometric theory of Markov chains and has much that will be new to experts. It is certainly THE book that I will use to teach from. I recommend it to all comers, an amazing achievement. -Persi Diaconis, Mary V. Sunseri Professor of Statistics and Mathematics, Stanford University Mixing times are an active research topic within many fields from statistical physics to the theory of algorithms, as well as having intrinsic interest within mathematical probability and exploiting discrete analogs of important geometry concepts. The first edition became an instant classic, being accessible to advanced undergraduates and yet bringing readers close to current research frontiers. This second edition adds chapters on monotone chains, the exclusion process and hitting time parameters. Having both exercises...
Markov Chain Ontology Analysis (MCOA).
Frost, H Robert; McCray, Alexa T
2012-02-03
Biomedical ontologies have become an increasingly critical lens through which researchers analyze the genomic, clinical and bibliographic data that fuels scientific research. Of particular relevance are methods, such as enrichment analysis, that quantify the importance of ontology classes relative to a collection of domain data. Current analytical techniques, however, remain limited in their ability to handle many important types of structural complexity encountered in real biological systems including class overlaps, continuously valued data, inter-instance relationships, non-hierarchical relationships between classes, semantic distance and sparse data. In this paper, we describe a methodology called Markov Chain Ontology Analysis (MCOA) and illustrate its use through a MCOA-based enrichment analysis application based on a generative model of gene activation. MCOA models the classes in an ontology, the instances from an associated dataset and all directional inter-class, class-to-instance and inter-instance relationships as a single finite ergodic Markov chain. The adjusted transition probability matrix for this Markov chain enables the calculation of eigenvector values that quantify the importance of each ontology class relative to other classes and the associated data set members. On both controlled Gene Ontology (GO) data sets created with Escherichia coli, Drosophila melanogaster and Homo sapiens annotations and real gene expression data extracted from the Gene Expression Omnibus (GEO), the MCOA enrichment analysis approach provides the best performance of comparable state-of-the-art methods. A methodology based on Markov chain models and network analytic metrics can help detect the relevant signal within large, highly interdependent and noisy data sets and, for applications such as enrichment analysis, has been shown to generate superior performance on both real and simulated data relative to existing state-of-the-art approaches.
Markov processes characterization and convergence
Ethier, Stewart N
2009-01-01
The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists."[A]nyone who works with Markov processes whose state space is uncountably infinite will need this most impressive book as a guide and reference."-American Scientist"There is no question but that space should immediately be reserved for [this] book on the library shelf. Those who aspire to mastery of the contents should also reserve a large number of long winter evenings."-Zentralblatt f?r Mathematik und ihre Grenzgebiete/Mathematics Abstracts"Ethier and Kurtz have produced an excellent treatment of the modern theory of Markov processes that [is] useful both as a reference work and as a graduate textbook."-Journal of Statistical PhysicsMarkov Proce...
Design of deterministic interleaver for turbo codes
International Nuclear Information System (INIS)
Arif, M.A.; Sheikh, N.M.; Sheikh, A.U.H.
2008-01-01
The choice of suitable interleaver for turbo codes can improve the performance considerably. For long block lengths, random interleavers perform well, but for some applications it is desirable to keep the block length shorter to avoid latency. For such applications deterministic interleavers perform better. The performance and design of a deterministic interleaver for short frame turbo codes is considered in this paper. The main characteristic of this class of deterministic interleaver is that their algebraic design selects the best permutation generator such that the points in smaller subsets of the interleaved output are uniformly spread over the entire range of the information data frame. It is observed that the interleaver designed in this manner improves the minimum distance or reduces the multiplicity of first few spectral lines of minimum distance spectrum. Finally we introduce a circular shift in the permutation function to reduce the correlation between the parity bits corresponding to the original and interleaved data frames to improve the decoding capability of MAP (Maximum A Posteriori) probability decoder. Our solution to design a deterministic interleaver outperforms the semi-random interleavers and the deterministic interleavers reported in the literature. (author)
Fault detection for piecewise affine systems with application to ship propulsion systems.
Yang, Ying; Linlin, Li; Ding, Steven X; Qiu, Jianbin; Peng, Kaixiang
2017-09-09
In this paper, the design approach of non-synchronized diagnostic observer-based fault detection (FD) systems is investigated for piecewise affine processes via continuous piecewise Lyapunov functions. Considering that the dynamics of piecewise affine systems in different regions can be considerably different, the weighting matrices are used to weight the residual of each region, so as to optimize the fault detectability. A numerical example and a case study on a ship propulsion system are presented in the end to demonstrate the effectiveness of the proposed results. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
Proving Non-Deterministic Computations in Agda
Directory of Open Access Journals (Sweden)
Sergio Antoy
2017-01-01
Full Text Available We investigate proving properties of Curry programs using Agda. First, we address the functional correctness of Curry functions that, apart from some syntactic and semantic differences, are in the intersection of the two languages. Second, we use Agda to model non-deterministic functions with two distinct and competitive approaches incorporating the non-determinism. The first approach eliminates non-determinism by considering the set of all non-deterministic values produced by an application. The second approach encodes every non-deterministic choice that the application could perform. We consider our initial experiment a success. Although proving properties of programs is a notoriously difficult task, the functional logic paradigm does not seem to add any significant layer of difficulty or complexity to the task.
Deterministic dense coding with partially entangled states
Mozes, Shay; Oppenheim, Jonathan; Reznik, Benni
2005-01-01
The utilization of a d -level partially entangled state, shared by two parties wishing to communicate classical information without errors over a noiseless quantum channel, is discussed. We analytically construct deterministic dense coding schemes for certain classes of nonmaximally entangled states, and numerically obtain schemes in the general case. We study the dependency of the maximal alphabet size of such schemes on the partially entangled state shared by the two parties. Surprisingly, for d>2 it is possible to have deterministic dense coding with less than one ebit. In this case the number of alphabet letters that can be communicated by a single particle is between d and 2d . In general, we numerically find that the maximal alphabet size is any integer in the range [d,d2] with the possible exception of d2-1 . We also find that states with less entanglement can have a greater deterministic communication capacity than other more entangled states.
Breaking the continuity of a piecewise linear map
Directory of Open Access Journals (Sweden)
Schenke Björn
2012-08-01
Full Text Available Knowledge about the behavior of discontinuous piecewise-linear maps is important for a wide range of applications. An efficient way to investigate the bifurcation structure in 2D parameter spaces of such maps is to detect specific codimension-2 bifurcation points, called organizing centers, and to describe the bifurcation structure in their neighborhood. In this work, we present the organizing centers in the 1D discontinuous piecewise-linear map in the generic form, which can be used as a normal form for these bifurcations in other 1D discontinuous maps with one discontinuity. These organizing centers appear when the continuity of the system function is broken in a fixed point. The type of an organizing center depends on the slopes of the piecewise-linear map. The organizing centers that occur if the slopes have an absolute value smaller than one were already described in previous works, so we concentrate on presenting the organizing centers that occur if one or both slopes have absolute values larger than one. By doing this, we also show that the behavior for each organizing center can be explained using four basic bifurcation scenarios: the period incrementing and the period adding scenarios in the periodic domain, as well as the bandcount incrementing and the bandcount adding scenarios in the chaotic domain. Les connaissances sur le comportement d’applications linéaires par morceaux discontinues sont importantes pour de nombreuses applications. Une méthode puissante pour étudier la structure de bifurcation dans les espaces de paramètre 2D de telles applications est de détecter des points de bifurcation spécifiques de codimension 2, appelés centres organisateurs, et de décrire la structure de bifurcation dans leur voisinage. Dans ce travail, nous présentons les centres organisateurs pour une application linéaire par morceaux discontinue 1D sous forme générique, ce qui peut être utilisé comme une forme normale pour ces
DETERMINISTIC METHODS USED IN FINANCIAL ANALYSIS
Directory of Open Access Journals (Sweden)
MICULEAC Melania Elena
2014-06-01
Full Text Available The deterministic methods are those quantitative methods that have as a goal to appreciate through numerical quantification the creation and expression mechanisms of factorial and causal, influence and propagation relations of effects, where the phenomenon can be expressed through a direct functional relation of cause-effect. The functional and deterministic relations are the causal relations where at a certain value of the characteristics corresponds a well defined value of the resulting phenomenon. They can express directly the correlation between the phenomenon and the influence factors, under the form of a function-type mathematical formula.
Introducing Synchronisation in Deterministic Network Models
DEFF Research Database (Denmark)
Schiøler, Henrik; Jessen, Jan Jakob; Nielsen, Jens Frederik D.
2006-01-01
The paper addresses performance analysis for distributed real time systems through deterministic network modelling. Its main contribution is the introduction and analysis of models for synchronisation between tasks and/or network elements. Typical patterns of synchronisation are presented leading...... to the suggestion of suitable network models. An existing model for flow control is presented and an inherent weakness is revealed and remedied. Examples are given and numerically analysed through deterministic network modelling. Results are presented to highlight the properties of the suggested models...
Optimal Deterministic Investment Strategies for Insurers
Directory of Open Access Journals (Sweden)
Ulrich Rieder
2013-11-01
Full Text Available We consider an insurance company whose risk reserve is given by a Brownian motion with drift and which is able to invest the money into a Black–Scholes financial market. As optimization criteria, we treat mean-variance problems, problems with other risk measures, exponential utility and the probability of ruin. Following recent research, we assume that investment strategies have to be deterministic. This leads to deterministic control problems, which are quite easy to solve. Moreover, it turns out that there are some interesting links between the optimal investment strategies of these problems. Finally, we also show that this approach works in the Lévy process framework.
Road maintenance optimization through a discrete-time semi-Markov decision process
International Nuclear Information System (INIS)
Zhang Xueqing; Gao Hui
2012-01-01
Optimization models are necessary for efficient and cost-effective maintenance of a road network. In this regard, road deterioration is commonly modeled as a discrete-time Markov process such that an optimal maintenance policy can be obtained based on the Markov decision process, or as a renewal process such that an optimal maintenance policy can be obtained based on the renewal theory. However, the discrete-time Markov process cannot capture the real time at which the state transits while the renewal process considers only one state and one maintenance action. In this paper, road deterioration is modeled as a semi-Markov process in which the state transition has the Markov property and the holding time in each state is assumed to follow a discrete Weibull distribution. Based on this semi-Markov process, linear programming models are formulated for both infinite and finite planning horizons in order to derive optimal maintenance policies to minimize the life-cycle cost of a road network. A hypothetical road network is used to illustrate the application of the proposed optimization models. The results indicate that these linear programming models are practical for the maintenance of a road network having a large number of road segments and that they are convenient to incorporate various constraints on the decision process, for example, performance requirements and available budgets. Although the optimal maintenance policies obtained for the road network are randomized stationary policies, the extent of this randomness in decision making is limited. The maintenance actions are deterministic for most states and the randomness in selecting actions occurs only for a few states.
Verification of Open Interactive Markov Chains
Brazdil, Tomas; Hermanns, Holger; Krcal, Jan; Kretinsky, Jan; Rehak, Vojtech
2012-01-01
Interactive Markov chains (IMC) are compositional behavioral models extending both labeled transition systems and continuous-time Markov chains. IMC pair modeling convenience - owed to compositionality properties - with effective verification algorithms and tools - owed to Markov properties. Thus far however, IMC verification did not consider compositionality properties, but considered closed systems. This paper discusses the evaluation of IMC in an open and thus compositional interpretation....
Spectral methods for quantum Markov chains
Energy Technology Data Exchange (ETDEWEB)
Szehr, Oleg
2014-05-08
The aim of this project is to contribute to our understanding of quantum time evolutions, whereby we focus on quantum Markov chains. The latter constitute a natural generalization of the ubiquitous concept of a classical Markov chain to describe evolutions of quantum mechanical systems. We contribute to the theory of such processes by introducing novel methods that allow us to relate the eigenvalue spectrum of the transition map to convergence as well as stability properties of the Markov chain.
Spectral methods for quantum Markov chains
International Nuclear Information System (INIS)
Szehr, Oleg
2014-01-01
The aim of this project is to contribute to our understanding of quantum time evolutions, whereby we focus on quantum Markov chains. The latter constitute a natural generalization of the ubiquitous concept of a classical Markov chain to describe evolutions of quantum mechanical systems. We contribute to the theory of such processes by introducing novel methods that allow us to relate the eigenvalue spectrum of the transition map to convergence as well as stability properties of the Markov chain.
A scaling analysis of a cat and mouse Markov chain
Litvak, Nelli; Robert, Philippe
2012-01-01
If ($C_n$) a Markov chain on a discrete state space $S$, a Markov chain ($C_n, M_n$) on the product space $S \\times S$, the cat and mouse Markov chain, is constructed. The first coordinate of this Markov chain behaves like the original Markov chain and the second component changes only when both
Criterion of Semi-Markov Dependent Risk Model
Institute of Scientific and Technical Information of China (English)
Xiao Yun MO; Xiang Qun YANG
2014-01-01
A rigorous definition of semi-Markov dependent risk model is given. This model is a generalization of the Markov dependent risk model. A criterion and necessary conditions of semi-Markov dependent risk model are obtained. The results clarify relations between elements among semi-Markov dependent risk model more clear and are applicable for Markov dependent risk model.
Markov chain model helps predict pitting corrosion depth and rate in underground pipelines
Energy Technology Data Exchange (ETDEWEB)
Caleyo, F.; Velazquez, J.C.; Hallen, J. M. [ESIQIE, Instituto Politecnico Nacional, Mexico D. F. (Mexico); Esquivel-Amezcua, A. [PEMEX PEP Region Sur, Villahermosa, Tabasco (Mexico); Valor, A. [Universidad de la Habana, Vedado, La Habana (Cuba)
2010-07-01
Recent reports place pipeline corrosion costs in North America at seven billion dollars per year. Pitting corrosion causes the higher percentage of failures among other corrosion mechanisms. This has motivated multiple modelling studies to be focused on corrosion pitting of underground pipelines. In this study, a continuous-time, non-homogenous pure birth Markov chain serves to model external pitting corrosion in buried pipelines. The analytical solution of Kolmogorov's forward equations for this type of Markov process gives the transition probability function in a discrete space of pit depths. The transition probability function can be completely identified by making a correlation between the stochastic pit depth mean and the deterministic mean obtained experimentally. The model proposed in this study can be applied to pitting corrosion data from repeated in-line pipeline inspections. Case studies presented in this work show how pipeline inspection and maintenance planning can be improved by using the proposed Markovian model for pitting corrosion.
Piecewise quadratic Lyapunov functions for stability verification of approximate explicit MPC
Directory of Open Access Journals (Sweden)
Morten Hovd
2010-04-01
Full Text Available Explicit MPC of constrained linear systems is known to result in a piecewise affine controller and therefore also piecewise affine closed loop dynamics. The complexity of such analytic formulations of the control law can grow exponentially with the prediction horizon. The suboptimal solutions offer a trade-off in terms of complexity and several approaches can be found in the literature for the construction of approximate MPC laws. In the present paper a piecewise quadratic (PWQ Lyapunov function is used for the stability verification of an of approximate explicit Model Predictive Control (MPC. A novel relaxation method is proposed for the LMI criteria on the Lyapunov function design. This relaxation is applicable to the design of PWQ Lyapunov functions for discrete-time piecewise affine systems in general.
Border-Collision Bifurcations and Chaotic Oscillations in a Piecewise-Smooth Dynamical System
DEFF Research Database (Denmark)
Zhusubaliyev, Z.T.; Soukhoterin, E.A.; Mosekilde, Erik
2002-01-01
Many problems of engineering and applied science result in the consideration of piecewise-smooth dynamical systems. Examples are relay and pulse-width control systems, impact oscillators, power converters, and various electronic circuits with piecewise-smooth characteristics. The subject...... of investigation in the present paper is the dynamical model of a constant voltage converter which represents a three-dimensional piecewise-smooth system of nonautonomous differential equations. A specific type of phenomena that arise in the dynamics of piecewise-smooth systems are the so-called border......-collision bifurcations. The paper contains a detailed analysis of this type of bifurcational transition in the dynamics of the voltage converter, in particular, the merging and subsequent disappearance of cycles of different types, change of solution type, and period-doubling, -tripling, -quadrupling and -quintupling...
On the Convergence of Piecewise Linear Strategic Interaction Dynamics on Networks
Gharesifard, Bahman; Touri, Behrouz; Basar, Tamer; Shamma, Jeff S.
2015-01-01
We prove that the piecewise linear best-response dynamical systems of strategic interactions are asymptotically convergent to their set of equilibria on any weighted undirected graph. We study various features of these dynamical systems, including
An Algorithm for Isolating the Real Solutions of Piecewise Algebraic Curves
Directory of Open Access Journals (Sweden)
Jinming Wu
2011-01-01
to compute the real solutions of two piecewise algebraic curves. It is primarily based on the Krawczyk-Moore iterative algorithm and good initial iterative interval searching algorithm. The proposed algorithm is relatively easy to implement.
Markov Decision Process Measurement Model.
LaMar, Michelle M
2018-03-01
Within-task actions can provide additional information on student competencies but are challenging to model. This paper explores the potential of using a cognitive model for decision making, the Markov decision process, to provide a mapping between within-task actions and latent traits of interest. Psychometric properties of the model are explored, and simulation studies report on parameter recovery within the context of a simple strategy game. The model is then applied to empirical data from an educational game. Estimates from the model are found to correlate more strongly with posttest results than a partial-credit IRT model based on outcome data alone.
Directory of Open Access Journals (Sweden)
Jean B. Lasserre
2000-01-01
Full Text Available We consider the class of Markov kernels for which the weak or strong Feller property fails to hold at some discontinuity set. We provide a simple necessary and sufficient condition for existence of an invariant probability measure as well as a Foster-Lyapunov sufficient condition. We also characterize a subclass, the quasi (weak or strong Feller kernels, for which the sequences of expected occupation measures share the same asymptotic properties as for (weak or strong Feller kernels. In particular, it is shown that the sequences of expected occupation measures of strong and quasi strong-Feller kernels with an invariant probability measure converge setwise to an invariant measure.
Markov process of muscle motors
International Nuclear Information System (INIS)
Kondratiev, Yu; Pechersky, E; Pirogov, S
2008-01-01
We study a Markov random process describing muscle molecular motor behaviour. Every motor is either bound up with a thin filament or unbound. In the bound state the motor creates a force proportional to its displacement from the neutral position. In both states the motor spends an exponential time depending on the state. The thin filament moves at a velocity proportional to the average of all displacements of all motors. We assume that the time which a motor stays in the bound state does not depend on its displacement. Then one can find an exact solution of a nonlinear equation appearing in the limit of an infinite number of motors
Optimal Piecewise Linear Basis Functions in Two Dimensions
Energy Technology Data Exchange (ETDEWEB)
Brooks III, E D; Szoke, A
2009-01-26
We use a variational approach to optimize the center point coefficients associated with the piecewise linear basis functions introduced by Stone and Adams [1], for polygonal zones in two Cartesian dimensions. Our strategy provides optimal center point coefficients, as a function of the location of the center point, by minimizing the error induced when the basis function interpolation is used for the solution of the time independent diffusion equation within the polygonal zone. By using optimal center point coefficients, one expects to minimize the errors that occur when these basis functions are used to discretize diffusion equations, or transport equations in optically thick zones (where they approach the solution of the diffusion equation). Our optimal center point coefficients satisfy the requirements placed upon the basis functions for any location of the center point. We also find that the location of the center point can be optimized, but this requires numerical calculations. Curiously, the optimum center point location is independent of the values of the dependent variable on the corners only for quadrilaterals.
Linear response formula for piecewise expanding unimodal maps
Baladi, Viviane; Smania, Daniel
2008-04-01
The average R(t)=\\int \\varphi\\,\\rmd \\mu_t of a smooth function phiv with respect to the SRB measure μt of a smooth one-parameter family ft of piecewise expanding interval maps is not always Lipschitz (Baladi 2007 Commun. Math. Phys. 275 839-59, Mazzolena 2007 Master's Thesis Rome 2, Tor Vergata). We prove that if ft is tangent to the topological class of f, and if ∂t ft|t = 0 = X circle f, then R(t) is differentiable at zero, and R'(0) coincides with the resummation proposed (Baladi 2007) of the (a priori divergent) series \\sum_{n=0}^\\infty \\int X(y) \\partial_y (\\varphi \\circ f^n)(y)\\,\\rmd \\mu_0(y) given by Ruelle's conjecture. In fact, we show that t map μt is differentiable within Radon measures. Linear response is violated if and only if ft is transversal to the topological class of f.
Dynamical zeta functions for piecewise monotone maps of the interval
Ruelle, David
2004-01-01
Consider a space M, a map f:M\\to M, and a function g:M \\to {\\mathbb C}. The formal power series \\zeta (z) = \\exp \\sum ^\\infty _{m=1} \\frac {z^m}{m} \\sum _{x \\in \\mathrm {Fix}\\,f^m} \\prod ^{m-1}_{k=0} g (f^kx) yields an example of a dynamical zeta function. Such functions have unexpected analytic properties and interesting relations to the theory of dynamical systems, statistical mechanics, and the spectral theory of certain operators (transfer operators). The first part of this monograph presents a general introduction to this subject. The second part is a detailed study of the zeta functions associated with piecewise monotone maps of the interval [0,1]. In particular, Ruelle gives a proof of a generalized form of the Baladi-Keller theorem relating the poles of \\zeta (z) and the eigenvalues of the transfer operator. He also proves a theorem expressing the largest eigenvalue of the transfer operator in terms of the ergodic properties of (M,f,g).
A pitfall of piecewise-polytropic equation of state inference
Raaijmakers, Geert; Riley, Thomas E.; Watts, Anna L.
2018-05-01
The only messenger radiation in the Universe which one can use to statistically probe the Equation of State (EOS) of cold dense matter is that originating from the near-field vicinities of compact stars. Constraining gravitational masses and equatorial radii of rotating compact stars is a major goal for current and future telescope missions, with a primary purpose of constraining the EOS. From a Bayesian perspective it is necessary to carefully discuss prior definition; in this context a complicating issue is that in practice there exist pathologies in the general relativistic mapping between spaces of local (interior source matter) and global (exterior spacetime) parameters. In a companion paper, these issues were raised on a theoretical basis. In this study we reproduce a probability transformation procedure from the literature in order to map a joint posterior distribution of Schwarzschild gravitational masses and radii into a joint posterior distribution of EOS parameters. We demonstrate computationally that EOS parameter inferences are sensitive to the choice to define a prior on a joint space of these masses and radii, instead of on a joint space interior source matter parameters. We focus on the piecewise-polytropic EOS model, which is currently standard in the field of astrophysical dense matter study. We discuss the implications of this issue for the field.
Interactive seismic interpretation with piecewise global energy minimization
Hollt, Thomas
2011-03-01
Increasing demands in world-wide energy consumption and oil depletion of large reservoirs have resulted in the need for exploring smaller and more complex oil reservoirs. Planning of the reservoir valorization usually starts with creating a model of the subsurface structures, including seismic faults and horizons. However, seismic interpretation and horizon tracing is a difficult and error-prone task, often resulting in hours of work needing to be manually repeated. In this paper, we propose a novel, interactive workflow for horizon interpretation based on well positions, which include additional geological and geophysical data captured by actual drillings. Instead of interpreting the volume slice-by-slice in 2D, we propose 3D seismic interpretation based on well positions. We introduce a combination of 2D and 3D minimal cost path and minimal cost surface tracing for extracting horizons with very little user input. By processing the volume based on well positions rather than slice-based, we are able to create a piecewise optimal horizon surface at interactive rates. We have integrated our system into a visual analysis platform which supports multiple linked views for fast verification, exploration and analysis of the extracted horizons. The system is currently being evaluated by our collaborating domain experts. © 2011 IEEE.
Interactive seismic interpretation with piecewise global energy minimization
Hollt, Thomas; Beyer, Johanna; Gschwantner, Fritz M.; Muigg, Philipp; Doleisch, Helmut; Heinemann, Gabor F.; Hadwiger, Markus
2011-01-01
Increasing demands in world-wide energy consumption and oil depletion of large reservoirs have resulted in the need for exploring smaller and more complex oil reservoirs. Planning of the reservoir valorization usually starts with creating a model of the subsurface structures, including seismic faults and horizons. However, seismic interpretation and horizon tracing is a difficult and error-prone task, often resulting in hours of work needing to be manually repeated. In this paper, we propose a novel, interactive workflow for horizon interpretation based on well positions, which include additional geological and geophysical data captured by actual drillings. Instead of interpreting the volume slice-by-slice in 2D, we propose 3D seismic interpretation based on well positions. We introduce a combination of 2D and 3D minimal cost path and minimal cost surface tracing for extracting horizons with very little user input. By processing the volume based on well positions rather than slice-based, we are able to create a piecewise optimal horizon surface at interactive rates. We have integrated our system into a visual analysis platform which supports multiple linked views for fast verification, exploration and analysis of the extracted horizons. The system is currently being evaluated by our collaborating domain experts. © 2011 IEEE.
Barbu, Vlad
2008-01-01
Semi-Markov processes are much more general and better adapted to applications than the Markov ones because sojourn times in any state can be arbitrarily distributed, as opposed to the geometrically distributed sojourn time in the Markov case. This book concerns with the estimation of discrete-time semi-Markov and hidden semi-Markov processes
A Theory of Deterministic Event Structures
Lee, I.; Rensink, Arend; Smolka, S.A.
1995-01-01
We present an w-complete algebra of a class of deterministic event structures which are labelled prime event structures where the labelling function satises a certain distinctness condition. The operators of the algebra are summation sequential composition and join. Each of these gives rise to a
A Numerical Simulation for a Deterministic Compartmental ...
African Journals Online (AJOL)
In this work, an earlier deterministic mathematical model of HIV/AIDS is revisited and numerical solutions obtained using Eulers numerical method. Using hypothetical values for the parameters, a program was written in VISUAL BASIC programming language to generate series for the system of difference equations from the ...
Leibov Roman
2017-01-01
This paper presents a bilinear approach to nonlinear differential equations system approximation problem. Sometimes the nonlinear differential equations right-hand sides linearization is extremely difficult or even impossible. Then piecewise-linear approximation of nonlinear differential equations can be used. The bilinear differential equations allow to improve piecewise-linear differential equations behavior and reduce errors on the border of different linear differential equations systems ...
Timed Comparisons of Semi-Markov Processes
DEFF Research Database (Denmark)
Pedersen, Mathias Ruggaard; Larsen, Kim Guldstrand; Bacci, Giorgio
2018-01-01
-Markov processes, and investigate the question of how to compare two semi-Markov processes with respect to their time-dependent behaviour. To this end, we introduce the relation of being “faster than” between processes and study its algorithmic complexity. Through a connection to probabilistic automata we obtain...
Probabilistic Reachability for Parametric Markov Models
DEFF Research Database (Denmark)
Hahn, Ernst Moritz; Hermanns, Holger; Zhang, Lijun
2011-01-01
Given a parametric Markov model, we consider the problem of computing the rational function expressing the probability of reaching a given set of states. To attack this principal problem, Daws has suggested to first convert the Markov chain into a finite automaton, from which a regular expression...
Inhomogeneous Markov point processes by transformation
DEFF Research Database (Denmark)
Jensen, Eva B. Vedel; Nielsen, Linda Stougaard
2000-01-01
We construct parametrized models for point processes, allowing for both inhomogeneity and interaction. The inhomogeneity is obtained by applying parametrized transformations to homogeneous Markov point processes. An interesting model class, which can be constructed by this transformation approach......, is that of exponential inhomogeneous Markov point processes. Statistical inference For such processes is discussed in some detail....
Markov-modulated and feedback fluid queues
Scheinhardt, Willem R.W.
1998-01-01
In the last twenty years the field of Markov-modulated fluid queues has received considerable attention. In these models a fluid reservoir receives and/or releases fluid at rates which depend on the actual state of a background Markov chain. In the first chapter of this thesis we give a short
Classification Using Markov Blanket for Feature Selection
DEFF Research Database (Denmark)
Zeng, Yifeng; Luo, Jian
2009-01-01
Selecting relevant features is in demand when a large data set is of interest in a classification task. It produces a tractable number of features that are sufficient and possibly improve the classification performance. This paper studies a statistical method of Markov blanket induction algorithm...... for filtering features and then applies a classifier using the Markov blanket predictors. The Markov blanket contains a minimal subset of relevant features that yields optimal classification performance. We experimentally demonstrate the improved performance of several classifiers using a Markov blanket...... induction as a feature selection method. In addition, we point out an important assumption behind the Markov blanket induction algorithm and show its effect on the classification performance....
Quantum Markov Chain Mixing and Dissipative Engineering
DEFF Research Database (Denmark)
Kastoryano, Michael James
2012-01-01
This thesis is the fruit of investigations on the extension of ideas of Markov chain mixing to the quantum setting, and its application to problems of dissipative engineering. A Markov chain describes a statistical process where the probability of future events depends only on the state...... of the system at the present point in time, but not on the history of events. Very many important processes in nature are of this type, therefore a good understanding of their behaviour has turned out to be very fruitful for science. Markov chains always have a non-empty set of limiting distributions...... (stationary states). The aim of Markov chain mixing is to obtain (upper and/or lower) bounds on the number of steps it takes for the Markov chain to reach a stationary state. The natural quantum extensions of these notions are density matrices and quantum channels. We set out to develop a general mathematical...
A piecewise-focused high DQE detector for MV imaging.
Star-Lack, Josh; Shedlock, Daniel; Swahn, Dennis; Humber, Dave; Wang, Adam; Hirsh, Hayley; Zentai, George; Sawkey, Daren; Kruger, Isaac; Sun, Mingshan; Abel, Eric; Virshup, Gary; Shin, Mihye; Fahrig, Rebecca
2015-09-01
Electronic portal imagers (EPIDs) with high detective quantum efficiencies (DQEs) are sought to facilitate the use of the megavoltage (MV) radiotherapy treatment beam for image guidance. Potential advantages include high quality (treatment) beam's eye view imaging, and improved cone-beam computed tomography (CBCT) generating images with more accurate electron density maps with immunity to metal artifacts. One approach to increasing detector sensitivity is to couple a thick pixelated scintillator array to an active matrix flat panel imager (AMFPI) incorporating amorphous silicon thin film electronics. Cadmium tungstate (CWO) has many desirable scintillation properties including good light output, a high index of refraction, high optical transparency, and reasonable cost. However, due to the 0 1 0 cleave plane inherent in its crystalline structure, the difficulty of cutting and polishing CWO has, in part, limited its study relative to other scintillators such as cesium iodide and bismuth germanate (BGO). The goal of this work was to build and test a focused large-area pixelated "strip" CWO detector. A 361 × 52 mm scintillator assembly that contained a total of 28 072 pixels was constructed. The assembly comprised seven subarrays, each 15 mm thick. Six of the subarrays were fabricated from CWO with a pixel pitch of 0.784 mm, while one array was constructed from BGO for comparison. Focusing was achieved by coupling the arrays to the Varian AS1000 AMFPI through a piecewise linear arc-shaped fiber optic plate. Simulation and experimental studies of modulation transfer function (MTF) and DQE were undertaken using a 6 MV beam, and comparisons were made between the performance of the pixelated strip assembly and the most common EPID configuration comprising a 1 mm-thick copper build-up plate attached to a 133 mg/cm(2) gadolinium oxysulfide scintillator screen (Cu-GOS). Projection radiographs and CBCT images of phantoms were acquired. The work also introduces the use of a
The Bacterial Sequential Markov Coalescent.
De Maio, Nicola; Wilson, Daniel J
2017-05-01
Bacteria can exchange and acquire new genetic material from other organisms directly and via the environment. This process, known as bacterial recombination, has a strong impact on the evolution of bacteria, for example, leading to the spread of antibiotic resistance across clades and species, and to the avoidance of clonal interference. Recombination hinders phylogenetic and transmission inference because it creates patterns of substitutions (homoplasies) inconsistent with the hypothesis of a single evolutionary tree. Bacterial recombination is typically modeled as statistically akin to gene conversion in eukaryotes, i.e. , using the coalescent with gene conversion (CGC). However, this model can be very computationally demanding as it needs to account for the correlations of evolutionary histories of even distant loci. So, with the increasing popularity of whole genome sequencing, the need has emerged for a faster approach to model and simulate bacterial genome evolution. We present a new model that approximates the coalescent with gene conversion: the bacterial sequential Markov coalescent (BSMC). Our approach is based on a similar idea to the sequential Markov coalescent (SMC)-an approximation of the coalescent with crossover recombination. However, bacterial recombination poses hurdles to a sequential Markov approximation, as it leads to strong correlations and linkage disequilibrium across very distant sites in the genome. Our BSMC overcomes these difficulties, and shows a considerable reduction in computational demand compared to the exact CGC, and very similar patterns in simulated data. We implemented our BSMC model within new simulation software FastSimBac. In addition to the decreased computational demand compared to previous bacterial genome evolution simulators, FastSimBac provides more general options for evolutionary scenarios, allowing population structure with migration, speciation, population size changes, and recombination hotspots. FastSimBac is
Deterministic nonlinear systems a short course
Anishchenko, Vadim S; Strelkova, Galina I
2014-01-01
This text is a short yet complete course on nonlinear dynamics of deterministic systems. Conceived as a modular set of 15 concise lectures it reflects the many years of teaching experience by the authors. The lectures treat in turn the fundamental aspects of the theory of dynamical systems, aspects of stability and bifurcations, the theory of deterministic chaos and attractor dimensions, as well as the elements of the theory of Poincare recurrences.Particular attention is paid to the analysis of the generation of periodic, quasiperiodic and chaotic self-sustained oscillations and to the issue of synchronization in such systems. This book is aimed at graduate students and non-specialist researchers with a background in physics, applied mathematics and engineering wishing to enter this exciting field of research.
Deterministic nanoparticle assemblies: from substrate to solution
International Nuclear Information System (INIS)
Barcelo, Steven J; Gibson, Gary A; Yamakawa, Mineo; Li, Zhiyong; Kim, Ansoon; Norris, Kate J
2014-01-01
The deterministic assembly of metallic nanoparticles is an exciting field with many potential benefits. Many promising techniques have been developed, but challenges remain, particularly for the assembly of larger nanoparticles which often have more interesting plasmonic properties. Here we present a scalable process combining the strengths of top down and bottom up fabrication to generate deterministic 2D assemblies of metallic nanoparticles and demonstrate their stable transfer to solution. Scanning electron and high-resolution transmission electron microscopy studies of these assemblies suggested the formation of nanobridges between touching nanoparticles that hold them together so as to maintain the integrity of the assembly throughout the transfer process. The application of these nanoparticle assemblies as solution-based surface-enhanced Raman scattering (SERS) materials is demonstrated by trapping analyte molecules in the nanoparticle gaps during assembly, yielding uniformly high enhancement factors at all stages of the fabrication process. (paper)
Deterministic dynamics of plasma focus discharges
International Nuclear Information System (INIS)
Gratton, J.; Alabraba, M.A.; Warmate, A.G.; Giudice, G.
1992-04-01
The performance (neutron yield, X-ray production, etc.) of plasma focus discharges fluctuates strongly in series performed with fixed experimental conditions. Previous work suggests that these fluctuations are due to a deterministic ''internal'' dynamics involving degrees of freedom not controlled by the operator, possibly related to adsorption and desorption of impurities from the electrodes. According to these dynamics the yield of a discharge depends on the outcome of the previous ones. We study 8 series of discharges in three different facilities, with various electrode materials and operating conditions. More evidence of a deterministic internal dynamics is found. The fluctuation pattern depends on the electrode materials and other characteristics of the experiment. A heuristic mathematical model that describes adsorption and desorption of impurities from the electrodes and their consequences on the yield is presented. The model predicts steady yield or periodic and chaotic fluctuations, depending on parameters related to the experimental conditions. (author). 27 refs, 7 figs, 4 tabs
Advances in stochastic and deterministic global optimization
Zhigljavsky, Anatoly; Žilinskas, Julius
2016-01-01
Current research results in stochastic and deterministic global optimization including single and multiple objectives are explored and presented in this book by leading specialists from various fields. Contributions include applications to multidimensional data visualization, regression, survey calibration, inventory management, timetabling, chemical engineering, energy systems, and competitive facility location. Graduate students, researchers, and scientists in computer science, numerical analysis, optimization, and applied mathematics will be fascinated by the theoretical, computational, and application-oriented aspects of stochastic and deterministic global optimization explored in this book. This volume is dedicated to the 70th birthday of Antanas Žilinskas who is a leading world expert in global optimization. Professor Žilinskas's research has concentrated on studying models for the objective function, the development and implementation of efficient algorithms for global optimization with single and mu...
Understanding deterministic diffusion by correlated random walks
International Nuclear Information System (INIS)
Klages, R.; Korabel, N.
2002-01-01
Low-dimensional periodic arrays of scatterers with a moving point particle are ideal models for studying deterministic diffusion. For such systems the diffusion coefficient is typically an irregular function under variation of a control parameter. Here we propose a systematic scheme of how to approximate deterministic diffusion coefficients of this kind in terms of correlated random walks. We apply this approach to two simple examples which are a one-dimensional map on the line and the periodic Lorentz gas. Starting from suitable Green-Kubo formulae we evaluate hierarchies of approximations for their parameter-dependent diffusion coefficients. These approximations converge exactly yielding a straightforward interpretation of the structure of these irregular diffusion coefficients in terms of dynamical correlations. (author)
Deterministic geologic processes and stochastic modeling
International Nuclear Information System (INIS)
Rautman, C.A.; Flint, A.L.
1992-01-01
This paper reports that recent outcrop sampling at Yucca Mountain, Nevada, has produced significant new information regarding the distribution of physical properties at the site of a potential high-level nuclear waste repository. consideration of the spatial variability indicates that her are a number of widespread deterministic geologic features at the site that have important implications for numerical modeling of such performance aspects as ground water flow and radionuclide transport. Because the geologic processes responsible for formation of Yucca Mountain are relatively well understood and operate on a more-or-less regional scale, understanding of these processes can be used in modeling the physical properties and performance of the site. Information reflecting these deterministic geologic processes may be incorporated into the modeling program explicitly using geostatistical concepts such as soft information, or implicitly, through the adoption of a particular approach to modeling
Deterministic analyses of severe accident issues
International Nuclear Information System (INIS)
Dua, S.S.; Moody, F.J.; Muralidharan, R.; Claassen, L.B.
2004-01-01
Severe accidents in light water reactors involve complex physical phenomena. In the past there has been a heavy reliance on simple assumptions regarding physical phenomena alongside of probability methods to evaluate risks associated with severe accidents. Recently GE has developed realistic methodologies that permit deterministic evaluations of severe accident progression and of some of the associated phenomena in the case of Boiling Water Reactors (BWRs). These deterministic analyses indicate that with appropriate system modifications, and operator actions, core damage can be prevented in most cases. Furthermore, in cases where core-melt is postulated, containment failure can either be prevented or significantly delayed to allow sufficient time for recovery actions to mitigate severe accidents
Schmidt games and Markov partitions
International Nuclear Information System (INIS)
Tseng, Jimmy
2009-01-01
Let T be a C 2 -expanding self-map of a compact, connected, C ∞ , Riemannian manifold M. We correct a minor gap in the proof of a theorem from the literature: the set of points whose forward orbits are nondense has full Hausdorff dimension. Our correction allows us to strengthen the theorem. Combining the correction with Schmidt games, we generalize the theorem in dimension one: given a point x 0 in M, the set of points whose forward orbit closures miss x 0 is a winning set. Finally, our key lemma, the no matching lemma, may be of independent interest in the theory of symbolic dynamics or the theory of Markov partitions
Deterministic automata for extended regular expressions
Directory of Open Access Journals (Sweden)
Syzdykov Mirzakhmet
2017-12-01
Full Text Available In this work we present the algorithms to produce deterministic finite automaton (DFA for extended operators in regular expressions like intersection, subtraction and complement. The method like “overriding” of the source NFA(NFA not defined with subset construction rules is used. The past work described only the algorithm for AND-operator (or intersection of regular languages; in this paper the construction for the MINUS-operator (and complement is shown.
Deterministic Mean-Field Ensemble Kalman Filtering
Law, Kody
2016-05-03
The proof of convergence of the standard ensemble Kalman filter (EnKF) from Le Gland, Monbet, and Tran [Large sample asymptotics for the ensemble Kalman filter, in The Oxford Handbook of Nonlinear Filtering, Oxford University Press, Oxford, UK, 2011, pp. 598--631] is extended to non-Gaussian state-space models. A density-based deterministic approximation of the mean-field limit EnKF (DMFEnKF) is proposed, consisting of a PDE solver and a quadrature rule. Given a certain minimal order of convergence k between the two, this extends to the deterministic filter approximation, which is therefore asymptotically superior to standard EnKF for dimension d<2k. The fidelity of approximation of the true distribution is also established using an extension of the total variation metric to random measures. This is limited by a Gaussian bias term arising from nonlinearity/non-Gaussianity of the model, which arises in both deterministic and standard EnKF. Numerical results support and extend the theory.
Deterministic Mean-Field Ensemble Kalman Filtering
Law, Kody; Tembine, Hamidou; Tempone, Raul
2016-01-01
The proof of convergence of the standard ensemble Kalman filter (EnKF) from Le Gland, Monbet, and Tran [Large sample asymptotics for the ensemble Kalman filter, in The Oxford Handbook of Nonlinear Filtering, Oxford University Press, Oxford, UK, 2011, pp. 598--631] is extended to non-Gaussian state-space models. A density-based deterministic approximation of the mean-field limit EnKF (DMFEnKF) is proposed, consisting of a PDE solver and a quadrature rule. Given a certain minimal order of convergence k between the two, this extends to the deterministic filter approximation, which is therefore asymptotically superior to standard EnKF for dimension d<2k. The fidelity of approximation of the true distribution is also established using an extension of the total variation metric to random measures. This is limited by a Gaussian bias term arising from nonlinearity/non-Gaussianity of the model, which arises in both deterministic and standard EnKF. Numerical results support and extend the theory.
Tveito, Aslak; Lines, Glenn T; Edwards, Andrew G; McCulloch, Andrew
2016-07-01
Markov models are ubiquitously used to represent the function of single ion channels. However, solving the inverse problem to construct a Markov model of single channel dynamics from bilayer or patch-clamp recordings remains challenging, particularly for channels involving complex gating processes. Methods for solving the inverse problem are generally based on data from voltage clamp measurements. Here, we describe an alternative approach to this problem based on measurements of voltage traces. The voltage traces define probability density functions of the functional states of an ion channel. These probability density functions can also be computed by solving a deterministic system of partial differential equations. The inversion is based on tuning the rates of the Markov models used in the deterministic system of partial differential equations such that the solution mimics the properties of the probability density function gathered from (pseudo) experimental data as well as possible. The optimization is done by defining a cost function to measure the difference between the deterministic solution and the solution based on experimental data. By evoking the properties of this function, it is possible to infer whether the rates of the Markov model are identifiable by our method. We present applications to Markov model well-known from the literature. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.
Nickelsen, Daniel
2017-07-01
The statistics of velocity increments in homogeneous and isotropic turbulence exhibit universal features in the limit of infinite Reynolds numbers. After Kolmogorov’s scaling law from 1941, many turbulence models aim for capturing these universal features, some are known to have an equivalent formulation in terms of Markov processes. We derive the Markov process equivalent to the particularly successful scaling law postulated by She and Leveque. The Markov process is a jump process for velocity increments u(r) in scale r in which the jumps occur randomly but with deterministic width in u. From its master equation we establish a prescription to simulate the She-Leveque process and compare it with Kolmogorov scaling. To put the She-Leveque process into the context of other established turbulence models on the Markov level, we derive a diffusion process for u(r) using two properties of the Navier-Stokes equation. This diffusion process already includes Kolmogorov scaling, extended self-similarity and a class of random cascade models. The fluctuation theorem of this Markov process implies a ‘second law’ that puts a loose bound on the multipliers of the random cascade models. This bound explicitly allows for instances of inverse cascades, which are necessary to satisfy the fluctuation theorem. By adding a jump process to the diffusion process, we go beyond Kolmogorov scaling and formulate the most general scaling law for the class of Markov processes having both diffusion and jump parts. This Markov scaling law includes She-Leveque scaling and a scaling law derived by Yakhot.
Piecewise Potential Vorticity Inversion for Intense Extratropical Cyclones
Seiler, C.; Zwiers, F. W.
2017-12-01
Global climate models (GCMs) tend to simulate too few intense extratropical cyclones (ETCs) in the Northern Hemisphere (NH) under historic climate conditions. This bias may arise from the interactions of multiple drivers, including surface temperature gradients, latent heating in the lower troposphere, and the upper-level jet stream. Previous attempts to quantify the importance of these drivers include idealized model experiments or statistical approaches. The first method however cannot easily be implemented for a multi-GCM ensemble, and the second approach does not disentangle the interactions among drivers, nor does it prove causality. An alternative method that overcomes these limitations is piecewise potential vorticity inversion (PPVI). PPVI derives the wind and geopotential height fields by inverting potential vorticity (PV) for discrete atmospheric levels. Despite being a powerful diagnostic tool, PPVI has primarily been used to study the dynamics of individual events only. This study presents the first PPVI climatology for the 5% most intense NH ETCs that occurred from 1980 to 2016. Conducting PPVI to 3273 ETC tracks identified in ERA-Interim reanalysis, we quantified the contributions from 3 atmospheric layers to ETC intensity. The respective layers are the surface (1000 hPa), a lower atmospheric level (700-850 hPa) and an upper atmospheric level (100-500 hPa) that are associated with the contributions from surface temperature gradients, latent heating, and the jet stream, respectively. Results show that contributions are dominated by the lower level (40%), followed by the upper level (20%) and the surface (17%), while the remaining 23% are associated with the background flow. Contributions from the surface and the lower level are stronger in the western ocean basins owed to the presence of the warm ocean currents, while contributions from the upper level are stronger in the eastern basins. Vertical cross sections of ETC-centered composites show an
Dose reduction using a dynamic, piecewise-linear attenuator
Energy Technology Data Exchange (ETDEWEB)
Hsieh, Scott S., E-mail: sshsieh@stanford.edu [Department of Radiology, Stanford University, Stanford, California 94305 and Department of Electrical Engineering, Stanford University, Stanford, California 94305 (United States); Fleischmann, Dominik [Department of Radiology, Stanford University, Stanford, California 94305 (United States); Pelc, Norbert J. [Department of Radiology, Stanford University, Stanford, California 94305 and Department of Bioengineering, Stanford University, Stanford, California 94305 (United States)
2014-02-15
Purpose: The authors recently proposed a dynamic, prepatient x-ray attenuator capable of producing a piecewise-linear attenuation profile customized to each patient and viewing angle. This attenuator was intended to reduce scatter-to-primary ratio (SPR), dynamic range, and dose by redistributing flux. In this work the authors tested the ability of the attenuator to reduce dose and SPR in simulations. Methods: The authors selected four clinical applications, including routine full field-of-view scans of the thorax and abdomen, and targeted reconstruction tasks for an abdominal aortic aneurysm and the pancreas. Raw data were estimated by forward projection of the image volume datasets. The dynamic attenuator was controlled to reduce dose while maintaining peak variance by solving a convex optimization problem, assuminga priori knowledge of the patient anatomy. In targeted reconstruction tasks, the noise in specific regions was given increased weighting. A system with a standard attenuator (or “bowtie filter”) was used as a reference, and used either convex optimized tube current modulation (TCM) or a standard TCM heuristic. The noise of the scan was determined analytically while the dose was estimated using Monte Carlo simulations. Scatter was also estimated using Monte Carlo simulations. The sensitivity of the dynamic attenuator to patient centering was also examined by shifting the abdomen in 2 cm intervals. Results: Compared to a reference system with optimized TCM, use of the dynamic attenuator reduced dose by about 30% in routine scans and 50% in targeted scans. Compared to the TCM heuristics which are typically used withouta priori knowledge, the dose reduction is about 50% for routine scans. The dynamic attenuator gives the ability to redistribute noise and variance and produces more uniform noise profiles than systems with a conventional bowtie filter. The SPR was also modestly reduced by 10% in the thorax and 24% in the abdomen. Imaging with the dynamic
Effects of Piecewise Spatial Smoothing in 4-D SPECT Reconstruction
Qi, Wenyuan; Yang, Yongyi; King, Michael A.
2014-02-01
In nuclear medicine, cardiac gated SPECT images are known to suffer from significantly increased noise owing to limited data counts. Consequently, spatial (and temporal) smoothing has been indispensable for suppressing the noise artifacts in SPECT reconstruction. However, recently we demonstrated that the benefit of spatial processing in motion-compensated reconstruction of gated SPECT (aka 4-D) could be outweighed by its adverse effects on the myocardium, which included degraded wall motion and perfusion defect detectability. In this work, we investigate whether we can alleviate these adverse effects by exploiting an alternative spatial smoothing prior in 4-D based on image total variation (TV). TV based prior is known to induce piecewise smoothing which can preserve edge features (such as boundaries of the heart wall) in reconstruction. However, it is not clear whether such a property would necessarily be beneficial for improving the accuracy of the myocardium in 4-D reconstruction. In particular, it is unknown whether it would adversely affect the detectability of perfusion defects that are small in size or low in contrast. In our evaluation study, we first use Monte Carlo simulated imaging with 4-D NURBS-based cardiac-torso (NCAT) phantom wherein the ground truth is known for quantitative comparison. We evaluated the accuracy of the reconstructed myocardium using a number of metrics, including regional and overall accuracy of the myocardium, accuracy of the phase activity curve (PAC) of the LV wall for wall motion, uniformity and spatial resolution of the LV wall, and detectability of perfusion defects using a channelized Hotelling observer (CHO). For lesion detection, we simulated perfusion defects with different sizes and contrast levels with the focus being on perfusion defects that are subtle. As a preliminary demonstration, we also tested on three sets of clinical acquisitions. From the quantitative results, it was demonstrated that TV smoothing could
Finite Markov processes and their applications
Iosifescu, Marius
2007-01-01
A self-contained treatment of finite Markov chains and processes, this text covers both theory and applications. Author Marius Iosifescu, vice president of the Romanian Academy and director of its Center for Mathematical Statistics, begins with a review of relevant aspects of probability theory and linear algebra. Experienced readers may start with the second chapter, a treatment of fundamental concepts of homogeneous finite Markov chain theory that offers examples of applicable models.The text advances to studies of two basic types of homogeneous finite Markov chains: absorbing and ergodic ch
Markov chains models, algorithms and applications
Ching, Wai-Ki; Ng, Michael K; Siu, Tak-Kuen
2013-01-01
This new edition of Markov Chains: Models, Algorithms and Applications has been completely reformatted as a text, complete with end-of-chapter exercises, a new focus on management science, new applications of the models, and new examples with applications in financial risk management and modeling of financial data.This book consists of eight chapters. Chapter 1 gives a brief introduction to the classical theory on both discrete and continuous time Markov chains. The relationship between Markov chains of finite states and matrix theory will also be highlighted. Some classical iterative methods
Markov chains analytic and Monte Carlo computations
Graham, Carl
2014-01-01
Markov Chains: Analytic and Monte Carlo Computations introduces the main notions related to Markov chains and provides explanations on how to characterize, simulate, and recognize them. Starting with basic notions, this book leads progressively to advanced and recent topics in the field, allowing the reader to master the main aspects of the classical theory. This book also features: Numerous exercises with solutions as well as extended case studies.A detailed and rigorous presentation of Markov chains with discrete time and state space.An appendix presenting probabilistic notions that are nec
Study and program implementation of transient curves' piecewise linearization
International Nuclear Information System (INIS)
Shi Yang; Zu Hongbiao
2014-01-01
Background: Transient curves are essential for the stress analysis of related equipment in nuclear power plant (NPP). The actually operating data or the design transient data of a NPP usually consist of a large number of data points with very short time intervals. To simplify the analysis, transient curves are generally piecewise linearized in advance. Up to now, the piecewise linearization of transient curves is accomplished manually, Purpose: The aim is to develop a method for the piecewise linearization of transient curves, and to implement it by programming. Methods: First of all, the fitting line of a number of data points was obtained by the least square method. The segment of the fitting line is set while the accumulation error of linearization exceeds the preset limit with the increasing number of points. Then the linearization of subsequent data points was begun from the last point of the preceding curve segment to get the next segment in the same way, and continue until the final data point involved. Finally, averaging of junction points is taken for the segment connection. Results: A computer program named PLTC (Piecewise Linearization for Transient Curves) was implemented and verified by the linearization of the standard sine curve and typical transient curves of a NPP. Conclusion: The method and the PLTC program can be well used to the piecewise linearization of transient curves, with improving efficiency and precision. (authors)
Time and Memory Efficient Online Piecewise Linear Approximation of Sensor Signals.
Grützmacher, Florian; Beichler, Benjamin; Hein, Albert; Kirste, Thomas; Haubelt, Christian
2018-05-23
Piecewise linear approximation of sensor signals is a well-known technique in the fields of Data Mining and Activity Recognition. In this context, several algorithms have been developed, some of them with the purpose to be performed on resource constrained microcontroller architectures of wireless sensor nodes. While microcontrollers are usually constrained in computational power and memory resources, all state-of-the-art piecewise linear approximation techniques either need to buffer sensor data or have an execution time depending on the segment’s length. In the paper at hand, we propose a novel piecewise linear approximation algorithm, with a constant computational complexity as well as a constant memory complexity. Our proposed algorithm’s worst-case execution time is one to three orders of magnitude smaller and its average execution time is three to seventy times smaller compared to the state-of-the-art Piecewise Linear Approximation (PLA) algorithms in our experiments. In our evaluations, we show that our algorithm is time and memory efficient without sacrificing the approximation quality compared to other state-of-the-art piecewise linear approximation techniques, while providing a maximum error guarantee per segment, a small parameter space of only one parameter, and a maximum latency of one sample period plus its worst-case execution time.
Deterministic chaotic dynamics of Raba River flow (Polish Carpathian Mountains)
Kędra, Mariola
2014-02-01
Is the underlying dynamics of river flow random or deterministic? If it is deterministic, is it deterministic chaotic? This issue is still controversial. The application of several independent methods, techniques and tools for studying daily river flow data gives consistent, reliable and clear-cut results to the question. The outcomes point out that the investigated discharge dynamics is not random but deterministic. Moreover, the results completely confirm the nonlinear deterministic chaotic nature of the studied process. The research was conducted on daily discharge from two selected gauging stations of the mountain river in southern Poland, the Raba River.
A scaling analysis of a cat and mouse Markov chain
Litvak, Nelli; Robert, Philippe
Motivated by an original on-line page-ranking algorithm, starting from an arbitrary Markov chain $(C_n)$ on a discrete state space ${\\cal S}$, a Markov chain $(C_n,M_n)$ on the product space ${\\cal S}^2$, the cat and mouse Markov chain, is constructed. The first coordinate of this Markov chain
Observation uncertainty in reversible Markov chains.
Metzner, Philipp; Weber, Marcus; Schütte, Christof
2010-09-01
In many applications one is interested in finding a simplified model which captures the essential dynamical behavior of a real life process. If the essential dynamics can be assumed to be (approximately) memoryless then a reasonable choice for a model is a Markov model whose parameters are estimated by means of Bayesian inference from an observed time series. We propose an efficient Monte Carlo Markov chain framework to assess the uncertainty of the Markov model and related observables. The derived Gibbs sampler allows for sampling distributions of transition matrices subject to reversibility and/or sparsity constraints. The performance of the suggested sampling scheme is demonstrated and discussed for a variety of model examples. The uncertainty analysis of functions of the Markov model under investigation is discussed in application to the identification of conformations of the trialanine molecule via Robust Perron Cluster Analysis (PCCA+) .
Generated dynamics of Markov and quantum processes
Janßen, Martin
2016-01-01
This book presents Markov and quantum processes as two sides of a coin called generated stochastic processes. It deals with quantum processes as reversible stochastic processes generated by one-step unitary operators, while Markov processes are irreversible stochastic processes generated by one-step stochastic operators. The characteristic feature of quantum processes are oscillations, interference, lots of stationary states in bounded systems and possible asymptotic stationary scattering states in open systems, while the characteristic feature of Markov processes are relaxations to a single stationary state. Quantum processes apply to systems where all variables, that control reversibility, are taken as relevant variables, while Markov processes emerge when some of those variables cannot be followed and are thus irrelevant for the dynamic description. Their absence renders the dynamic irreversible. A further aim is to demonstrate that almost any subdiscipline of theoretical physics can conceptually be put in...
Confluence reduction for Markov automata (extended version)
Timmer, Mark; van de Pol, Jan Cornelis; Stoelinga, Mariëlle Ida Antoinette
Markov automata are a novel formalism for specifying systems exhibiting nondeterminism, probabilistic choices and Markovian rates. Recently, the process algebra MAPA was introduced to efficiently model such systems. As always, the state space explosion threatens the analysability of the models
DEFF Research Database (Denmark)
Ahmadi, Mohamadreza; Mojallali, Hamed; Wisniewski, Rafal
2012-01-01
This paper addresses the robust stability and control problem of uncertain piecewise linear switched systems where, instead of the conventional Carathe ́odory solutions, we allow for Filippov solutions. In other words, in contrast to the previous studies, solutions with infinite switching in fini...... algorithm is proposed to surmount the aforementioned matrix inequality conditions....... time along the facets and on faces of arbitrary dimensions are also taken into account. Firstly, based on earlier results, the stability problem of piecewise linear systems with Filippov solutions is translated into a number of linear matrix inequality feasibility tests. Subsequently, a set of matrix...... inequalities are brought forward, which determines the asymptotic stability of the Filippov solutions of a given uncertain piecewise linear system. Afterwards, bilinear matrix inequality conditions for synthesizing a robust controller with a guaranteed H∞ per- formance are formulated. Finally, a V-K iteration...
Semi-Markov Arnason-Schwarz models.
King, Ruth; Langrock, Roland
2016-06-01
We consider multi-state capture-recapture-recovery data where observed individuals are recorded in a set of possible discrete states. Traditionally, the Arnason-Schwarz model has been fitted to such data where the state process is modeled as a first-order Markov chain, though second-order models have also been proposed and fitted to data. However, low-order Markov models may not accurately represent the underlying biology. For example, specifying a (time-independent) first-order Markov process involves the assumption that the dwell time in each state (i.e., the duration of a stay in a given state) has a geometric distribution, and hence that the modal dwell time is one. Specifying time-dependent or higher-order processes provides additional flexibility, but at the expense of a potentially significant number of additional model parameters. We extend the Arnason-Schwarz model by specifying a semi-Markov model for the state process, where the dwell-time distribution is specified more generally, using, for example, a shifted Poisson or negative binomial distribution. A state expansion technique is applied in order to represent the resulting semi-Markov Arnason-Schwarz model in terms of a simpler and computationally tractable hidden Markov model. Semi-Markov Arnason-Schwarz models come with only a very modest increase in the number of parameters, yet permit a significantly more flexible state process. Model selection can be performed using standard procedures, and in particular via the use of information criteria. The semi-Markov approach allows for important biological inference to be drawn on the underlying state process, for example, on the times spent in the different states. The feasibility of the approach is demonstrated in a simulation study, before being applied to real data corresponding to house finches where the states correspond to the presence or absence of conjunctivitis. © 2015, The International Biometric Society.
A Bayesian model for binary Markov chains
Directory of Open Access Journals (Sweden)
Belkheir Essebbar
2004-02-01
Full Text Available This note is concerned with Bayesian estimation of the transition probabilities of a binary Markov chain observed from heterogeneous individuals. The model is founded on the Jeffreys' prior which allows for transition probabilities to be correlated. The Bayesian estimator is approximated by means of Monte Carlo Markov chain (MCMC techniques. The performance of the Bayesian estimates is illustrated by analyzing a small simulated data set.
Bayesian analysis of Markov point processes
DEFF Research Database (Denmark)
Berthelsen, Kasper Klitgaard; Møller, Jesper
2006-01-01
Recently Møller, Pettitt, Berthelsen and Reeves introduced a new MCMC methodology for drawing samples from a posterior distribution when the likelihood function is only specified up to a normalising constant. We illustrate the method in the setting of Bayesian inference for Markov point processes...... a partially ordered Markov point process as the auxiliary variable. As the method requires simulation from the "unknown" likelihood, perfect simulation algorithms for spatial point processes become useful....
Subharmonic projections for a quantum Markov semigroup
International Nuclear Information System (INIS)
Fagnola, Franco; Rebolledo, Rolando
2002-01-01
This article introduces a concept of subharmonic projections for a quantum Markov semigroup, in view of characterizing the support projection of a stationary state in terms of the semigroup generator. These results, together with those of our previous article [J. Math. Phys. 42, 1296 (2001)], lead to a method for proving the existence of faithful stationary states. This is often crucial in the analysis of ergodic properties of quantum Markov semigroups. The method is illustrated by applications to physical models
Transition Effect Matrices and Quantum Markov Chains
Gudder, Stan
2009-06-01
A transition effect matrix (TEM) is a quantum generalization of a classical stochastic matrix. By employing a TEM we obtain a quantum generalization of a classical Markov chain. We first discuss state and operator dynamics for a quantum Markov chain. We then consider various types of TEMs and vector states. In particular, we study invariant, equilibrium and singular vector states and investigate projective, bistochastic, invertible and unitary TEMs.
Energy Technology Data Exchange (ETDEWEB)
Frank, T D [Center for the Ecological Study of Perception and Action, Department of Psychology, University of Connecticut, 406 Babbidge Road, Storrs, CT 06269 (United States)
2008-07-18
We discuss nonlinear Markov processes defined on discrete time points and discrete state spaces using Markov chains. In this context, special attention is paid to the distinction between linear and nonlinear Markov processes. We illustrate that the Chapman-Kolmogorov equation holds for nonlinear Markov processes by a winner-takes-all model for social conformity. (fast track communication)
International Nuclear Information System (INIS)
Frank, T D
2008-01-01
We discuss nonlinear Markov processes defined on discrete time points and discrete state spaces using Markov chains. In this context, special attention is paid to the distinction between linear and nonlinear Markov processes. We illustrate that the Chapman-Kolmogorov equation holds for nonlinear Markov processes by a winner-takes-all model for social conformity. (fast track communication)
Deterministic and probabilistic approach to safety analysis
International Nuclear Information System (INIS)
Heuser, F.W.
1980-01-01
The examples discussed in this paper show that reliability analysis methods fairly well can be applied in order to interpret deterministic safety criteria in quantitative terms. For further improved extension of applied reliability analysis it has turned out that the influence of operational and control systems and of component protection devices should be considered with the aid of reliability analysis methods in detail. Of course, an extension of probabilistic analysis must be accompanied by further development of the methods and a broadening of the data base. (orig.)
Diffusion in Deterministic Interacting Lattice Systems
Medenjak, Marko; Klobas, Katja; Prosen, Tomaž
2017-09-01
We study reversible deterministic dynamics of classical charged particles on a lattice with hard-core interaction. It is rigorously shown that the system exhibits three types of transport phenomena, ranging from ballistic, through diffusive to insulating. By obtaining an exact expressions for the current time-autocorrelation function we are able to calculate the linear response transport coefficients, such as the diffusion constant and the Drude weight. Additionally, we calculate the long-time charge profile after an inhomogeneous quench and obtain diffusive profilewith the Green-Kubo diffusion constant. Exact analytical results are corroborated by Monte Carlo simulations.
Stochastic demand patterns for Markov service facilities with neutral and active periods
International Nuclear Information System (INIS)
Csenki, Attila
2009-01-01
In an earlier paper, a closed form expression was obtained for the joint interval reliability of a Markov system with a partitioned state space S=U union D, i.e. for the probability that the system will reside in the set of up states U throughout the union of some specific disjoint time intervals I l =[θ l ,θ l +ζ l ],l=1,...,k. The deterministic time intervals I l formed a demand pattern specifying the desired active periods. In the present paper, we admit stochastic demand patterns by assuming that the lengths of the active periods, ζ l , as well as the lengths of the neutral periods, θ l -(θ l-1 +ζ l-1 ), are random. We explore two mechanisms for modelling random demand: (1) by alternating renewal processes; (2) by sojourn times of some continuous time Markov chain with a partitioned state space. The first construction results in an expression in terms of a revised version of the moment generating functions of the sojourns of the alternating renewal process. The second construction involves the probability that a Markov chain follows certain patterns of visits to some groups of states and yields an expression using Kronecker matrix operations. The model of a small computer system is analysed to exemplify the ideas
Markov Processes in Image Processing
Petrov, E. P.; Kharina, N. L.
2018-05-01
Digital images are used as an information carrier in different sciences and technologies. The aspiration to increase the number of bits in the image pixels for the purpose of obtaining more information is observed. In the paper, some methods of compression and contour detection on the basis of two-dimensional Markov chain are offered. Increasing the number of bits on the image pixels will allow one to allocate fine object details more precisely, but it significantly complicates image processing. The methods of image processing do not concede by the efficiency to well-known analogues, but surpass them in processing speed. An image is separated into binary images, and processing is carried out in parallel with each without an increase in speed, when increasing the number of bits on the image pixels. One more advantage of methods is the low consumption of energy resources. Only logical procedures are used and there are no computing operations. The methods can be useful in processing images of any class and assignment in processing systems with a limited time and energy resources.
Adaptive Markov Chain Monte Carlo
Jadoon, Khan
2016-08-08
A substantial interpretation of electromagnetic induction (EMI) measurements requires quantifying optimal model parameters and uncertainty of a nonlinear inverse problem. For this purpose, an adaptive Bayesian Markov chain Monte Carlo (MCMC) algorithm is used to assess multi-orientation and multi-offset EMI measurements in an agriculture field with non-saline and saline soil. In the MCMC simulations, posterior distribution was computed using Bayes rule. The electromagnetic forward model based on the full solution of Maxwell\\'s equations was used to simulate the apparent electrical conductivity measured with the configurations of EMI instrument, the CMD mini-Explorer. The model parameters and uncertainty for the three-layered earth model are investigated by using synthetic data. Our results show that in the scenario of non-saline soil, the parameters of layer thickness are not well estimated as compared to layers electrical conductivity because layer thicknesses in the model exhibits a low sensitivity to the EMI measurements, and is hence difficult to resolve. Application of the proposed MCMC based inversion to the field measurements in a drip irrigation system demonstrate that the parameters of the model can be well estimated for the saline soil as compared to the non-saline soil, and provide useful insight about parameter uncertainty for the assessment of the model outputs.
Fitting Hidden Markov Models to Psychological Data
Directory of Open Access Journals (Sweden)
Ingmar Visser
2002-01-01
Full Text Available Markov models have been used extensively in psychology of learning. Applications of hidden Markov models are rare however. This is partially due to the fact that comprehensive statistics for model selection and model assessment are lacking in the psychological literature. We present model selection and model assessment statistics that are particularly useful in applying hidden Markov models in psychology. These statistics are presented and evaluated by simulation studies for a toy example. We compare AIC, BIC and related criteria and introduce a prediction error measure for assessing goodness-of-fit. In a simulation study, two methods of fitting equality constraints are compared. In two illustrative examples with experimental data we apply selection criteria, fit models with constraints and assess goodness-of-fit. First, data from a concept identification task is analyzed. Hidden Markov models provide a flexible approach to analyzing such data when compared to other modeling methods. Second, a novel application of hidden Markov models in implicit learning is presented. Hidden Markov models are used in this context to quantify knowledge that subjects express in an implicit learning task. This method of analyzing implicit learning data provides a comprehensive approach for addressing important theoretical issues in the field.
Hierarchical Markov Model in Life Insurance and Social Benefit Schemes
Directory of Open Access Journals (Sweden)
Jiwook Jang
2018-06-01
Full Text Available We explored the effect of the jump-diffusion process on a social benefit scheme consisting of life insurance, unemployment/disability benefits, and retirement benefits. To do so, we used a four-state Markov chain with multiple decrements. Assuming independent state-wise intensities taking the form of a jump-diffusion process and deterministic interest rates, we evaluated the prospective reserves for this scheme in which the individual is employed at inception. We then numerically demonstrated the state of the reserves for the scheme under jump-diffusion and non-jump-diffusion settings. By decomposing the reserve equation into five components, our numerical illustration indicated that an extension of the retirement age has a spillover effect that would increase government expenses for other social insurance programs. We also conducted sensitivity analyses and examined the total-reserves components by changing the relevant parameters of the transition intensities, which are the average jump-size parameter, average jump frequency, and diffusion parameters of the chosen states, with figures provided. Our computation revealed that the total reserve is most sensitive to changes in average jump frequency.
Energy Technology Data Exchange (ETDEWEB)
Bailey, T S; Adams, M L [Texas A M Univ., Dept. of Nuclear Engineering, College Station, TX (United States); Yang, B; Zika, M R [Lawrence Livermore National Lab., Livermore, CA (United States)
2005-07-01
We develop a piecewise linear (PWL) Galerkin finite element spatial discretization for the multi-dimensional radiation diffusion equation. It uses piecewise linear weight and basis functions in the finite element approximation, and it can be applied on arbitrary polygonal (2-dimensional) or polyhedral (3-dimensional) grids. We show that this new PWL method gives solutions comparable to those from Palmer's finite-volume method. However, since the PWL method produces a symmetric positive definite coefficient matrix, it should be substantially more computationally efficient than Palmer's method, which produces an asymmetric matrix. We conclude that the Galerkin PWL method is an attractive option for solving diffusion equations on unstructured grids. (authors)
Parameter-dependent PWQ Lyapunov function stability criteria for uncertain piecewise linear systems
Directory of Open Access Journals (Sweden)
Morten Hovd
2018-01-01
Full Text Available The calculation of piecewise quadratic (PWQ Lyapunov functions is addressed in view of stability analysis of uncertain piecewise linear dynamics. As main contribution, the linear matrix inequality (LMI approach proposed in (Johansson and Rantzer, 1998 for the stability analysis of PWL and PWA dynamics is extended to account for parametric uncertainty based on a improved relaxation technique. The results are applied for the analysis of a Phase Locked Loop (PLL benchmark and the ability to guarantee a stability region in the parameter space well beyond the state of the art is demonstrated.
Smoothing a Piecewise-Smooth: An Example from Plankton Population Dynamics
DEFF Research Database (Denmark)
Piltz, Sofia Helena
2016-01-01
In this work we discuss a piecewise-smooth dynamical system inspired by plankton observations and constructed for one predator switching its diet between two different types of prey. We then discuss two smooth formulations of the piecewise-smooth model obtained by using a hyperbolic tangent funct...... function and adding a dimension to the system. We compare model behaviour of the three systems and show an example case where the steepness of the switch is determined from a comparison with data on freshwater plankton....
A Piecewise Affine Hybrid Systems Approach to Fault Tolerant Satellite Formation Control
DEFF Research Database (Denmark)
Grunnet, Jacob Deleuran; Larsen, Jesper Abildgaard; Bak, Thomas
2008-01-01
In this paper a procedure for modelling satellite formations including failure dynamics as a piecewise-affine hybrid system is shown. The formulation enables recently developed methods and tools for control and analysis of piecewise-affine systems to be applied leading to synthesis of fault...... tolerant controllers and analysis of the system behaviour given possible faults. The method is illustrated using a simple example involving two satellites trying to reach a specific formation despite of actuator faults occurring....
International Nuclear Information System (INIS)
Zhdanovich, S.; Shapiro, E. A.; Shapiro, M.; Hepburn, J. W.; Milner, V.
2008-01-01
We propose and experimentally demonstrate the method of population transfer by piecewise adiabatic passage between two quantum states. Coherent excitation of a two-level system with a train of ultrashort laser pulses is shown to reproduce the effect of an adiabatic passage, conventionally achieved with a single frequency-chirped pulse. By properly adjusting the amplitudes and phases of the pulses in the excitation pulse train, we achieve complete and robust population transfer to the target state. The piecewise nature of the process suggests a possibility for the selective population transfer in complex quantum systems
Directory of Open Access Journals (Sweden)
J. Eeckman
2017-09-01
Full Text Available This paper provides a new representation of the effect of altitude on precipitation that represents spatial and temporal variability in precipitation in the Everest region. Exclusive observation data are used to infer a piecewise linear function for the relation between altitude and precipitation and significant seasonal variations are highlighted. An original ensemble approach is applied to provide non-deterministic water budgets for middle and high-mountain catchments. Physical processes at the soil–atmosphere interface are represented through the Interactions Soil–Biosphere–Atmosphere (ISBA surface scheme. Uncertainties associated with the model parametrization are limited by the integration of in situ measurements of soils and vegetation properties. Uncertainties associated with the representation of the orographic effect are shown to account for up to 16 % of annual total precipitation. Annual evapotranspiration is shown to represent 26 % ± 1 % of annual total precipitation for the mid-altitude catchment and 34% ± 3 % for the high-altitude catchment. Snowfall contribution is shown to be neglectable for the mid-altitude catchment, and it represents up to 44 % ± 8 % of total precipitation for the high-altitude catchment. These simulations on the local scale enhance current knowledge of the spatial variability in hydroclimatic processes in high- and mid-altitude mountain environments.
Safety margins in deterministic safety analysis
International Nuclear Information System (INIS)
Viktorov, A.
2011-01-01
The concept of safety margins has acquired certain prominence in the attempts to demonstrate quantitatively the level of the nuclear power plant safety by means of deterministic analysis, especially when considering impacts from plant ageing and discovery issues. A number of international or industry publications exist that discuss various applications and interpretations of safety margins. The objective of this presentation is to bring together and examine in some detail, from the regulatory point of view, the safety margins that relate to deterministic safety analysis. In this paper, definitions of various safety margins are presented and discussed along with the regulatory expectations for them. Interrelationships of analysis input and output parameters with corresponding limits are explored. It is shown that the overall safety margin is composed of several components each having different origins and potential uses; in particular, margins associated with analysis output parameters are contrasted with margins linked to the analysis input. While these are separate, it is possible to influence output margins through the analysis input, and analysis method. Preserving safety margins is tantamount to maintaining safety. At the same time, efficiency of operation requires optimization of safety margins taking into account various technical and regulatory considerations. For this, basic definitions and rules for safety margins must be first established. (author)
Streamflow disaggregation: a nonlinear deterministic approach
Directory of Open Access Journals (Sweden)
B. Sivakumar
2004-01-01
Full Text Available This study introduces a nonlinear deterministic approach for streamflow disaggregation. According to this approach, the streamflow transformation process from one scale to another is treated as a nonlinear deterministic process, rather than a stochastic process as generally assumed. The approach follows two important steps: (1 reconstruction of the scalar (streamflow series in a multi-dimensional phase-space for representing the transformation dynamics; and (2 use of a local approximation (nearest neighbor method for disaggregation. The approach is employed for streamflow disaggregation in the Mississippi River basin, USA. Data of successively doubled resolutions between daily and 16 days (i.e. daily, 2-day, 4-day, 8-day, and 16-day are studied, and disaggregations are attempted only between successive resolutions (i.e. 2-day to daily, 4-day to 2-day, 8-day to 4-day, and 16-day to 8-day. Comparisons between the disaggregated values and the actual values reveal excellent agreements for all the cases studied, indicating the suitability of the approach for streamflow disaggregation. A further insight into the results reveals that the best results are, in general, achieved for low embedding dimensions (2 or 3 and small number of neighbors (less than 50, suggesting possible presence of nonlinear determinism in the underlying transformation process. A decrease in accuracy with increasing disaggregation scale is also observed, a possible implication of the existence of a scaling regime in streamflow.
A mathematical theory for deterministic quantum mechanics
Energy Technology Data Exchange (ETDEWEB)
Hooft, Gerard ' t [Institute for Theoretical Physics, Utrecht University (Netherlands); Spinoza Institute, Postbox 80.195, 3508 TD Utrecht (Netherlands)
2007-05-15
Classical, i.e. deterministic theories underlying quantum mechanics are considered, and it is shown how an apparent quantum mechanical Hamiltonian can be defined in such theories, being the operator that generates evolution in time. It includes various types of interactions. An explanation must be found for the fact that, in the real world, this Hamiltonian is bounded from below. The mechanism that can produce exactly such a constraint is identified in this paper. It is the fact that not all classical data are registered in the quantum description. Large sets of values of these data are assumed to be indistinguishable, forming equivalence classes. It is argued that this should be attributed to information loss, such as what one might suspect to happen during the formation and annihilation of virtual black holes. The nature of the equivalence classes follows from the positivity of the Hamiltonian. Our world is assumed to consist of a very large number of subsystems that may be regarded as approximately independent, or weakly interacting with one another. As long as two (or more) sectors of our world are treated as being independent, they all must be demanded to be restricted to positive energy states only. What follows from these considerations is a unique definition of energy in the quantum system in terms of the periodicity of the limit cycles of the deterministic model.
Design of deterministic OS for SPLC
International Nuclear Information System (INIS)
Son, Choul Woong; Kim, Dong Hoon; Son, Gwang Seop
2012-01-01
Existing safety PLCs for using in nuclear power plants operates based on priority based scheduling, in which the highest priority task runs first. This type of scheduling scheme determines processing priorities when multiple requests for processing or when there is a lack of resources available for processing, guaranteeing execution of higher priority tasks. This type of scheduling is prone to exhaustion of resources and continuous preemptions by devices with high priorities, and therefore there is uncertainty every period in terms of smooth running of the overall system. Hence, it is difficult to apply this type of scheme to where deterministic operation is required, such as in nuclear power plant. Also, existing PLCs either have no output logic with regard to devices' redundant selection or it was set in a fixed way, and as a result it was extremely inefficient to use them for redundant systems such as that of a nuclear power plant and their use was limited. Therefore, functional modules that can manage and control all devices need to be developed by improving on the way priorities are assigned among the devices, making it more flexible. A management module should be able to schedule all devices of the system, manage resources, analyze states of the devices, and give warnings in case of abnormal situations, such as device fail or resource scarcity and decide on how to handle it. Also, the management module should have output logic for device redundancy, as well as deterministic processing capabilities, such as with regard to device interrupt events
Deterministic prediction of surface wind speed variations
Directory of Open Access Journals (Sweden)
G. V. Drisya
2014-11-01
Full Text Available Accurate prediction of wind speed is an important aspect of various tasks related to wind energy management such as wind turbine predictive control and wind power scheduling. The most typical characteristic of wind speed data is its persistent temporal variations. Most of the techniques reported in the literature for prediction of wind speed and power are based on statistical methods or probabilistic distribution of wind speed data. In this paper we demonstrate that deterministic forecasting methods can make accurate short-term predictions of wind speed using past data, at locations where the wind dynamics exhibit chaotic behaviour. The predictions are remarkably accurate up to 1 h with a normalised RMSE (root mean square error of less than 0.02 and reasonably accurate up to 3 h with an error of less than 0.06. Repeated application of these methods at 234 different geographical locations for predicting wind speeds at 30-day intervals for 3 years reveals that the accuracy of prediction is more or less the same across all locations and time periods. Comparison of the results with f-ARIMA model predictions shows that the deterministic models with suitable parameters are capable of returning improved prediction accuracy and capturing the dynamical variations of the actual time series more faithfully. These methods are simple and computationally efficient and require only records of past data for making short-term wind speed forecasts within practically tolerable margin of errors.
Esquível, Manuel L.; Fernandes, José Moniz; Guerreiro, Gracinda R.
2016-06-01
We introduce a schematic formalism for the time evolution of a random population entering some set of classes and such that each member of the population evolves among these classes according to a scheme based on a Markov chain model. We consider that the flow of incoming members is modeled by a time series and we detail the time series structure of the elements in each of the classes. We present a practical application to data from a credit portfolio of a Cape Verdian bank; after modeling the entering population in two different ways - namely as an ARIMA process and as a deterministic sigmoid type trend plus a SARMA process for the residues - we simulate the behavior of the population and compare the results. We get that the second method is more accurate in describing the behavior of the populations when compared to the observed values in a direct simulation of the Markov chain.
Convergent piecewise affine systems : analysis and design Part II: discontinuous case
Pavlov, A.V.; Pogromski, A.Y.; Wouw, van de N.; Nijmeijer, H.; Rooda, J.E.
2005-01-01
In this paper convergence properties of piecewise affine (PWA) systems with discontinuous right-hand sides are studied. It is shown that for discontinuous PWA systems existence of a common quadratic Lyapunov function is not sufficient for convergence. For discontinuous bimodal PWA systems necessary
Doris, A.; Wouw, van de N.; Heemels, W.P.M.H.; Nijmeijer, H.
2010-01-01
We consider the disturbance attenuation problem for a class of continuous piecewise affine systems. Hereto, observer-based output-feedback controllers are proposed that render the closed-loop system uniformly convergent. The convergence property ensures, first, stability and, second, the existence
Passive Fault Tolerant Control of Piecewise Affine Systems Based on H Infinity Synthesis
DEFF Research Database (Denmark)
Gholami, Mehdi; Cocquempot, vincent; Schiøler, Henrik
2011-01-01
In this paper we design a passive fault tolerant controller against actuator faults for discretetime piecewise affine (PWA) systems. By using dissipativity theory and H analysis, fault tolerant state feedback controller design is expressed as a set of Linear Matrix Inequalities (LMIs). In the cur...
DEFF Research Database (Denmark)
Tabatabaeipour, Seyed Mojtaba; Bak, Thomas
2012-01-01
In this paper we consider the problem of fault estimation and accommodation for discrete time piecewise linear systems. A robust fault estimator is designed to estimate the fault such that the estimation error converges to zero and H∞ performance of the fault estimation is minimized. Then, the es...
Directory of Open Access Journals (Sweden)
Kuo-Shou Chiu
2011-11-01
Full Text Available We examine scalar differential equations with a general piecewise constant argument, in short DEPCAG, that is, the argument is a general step function. Criteria of existence of the oscillatory and nonoscillatory solutions of such equations are proposed. Necessary and sufficient conditions for stability of the zero solution are obtained. Appropriate examples are given to show our results.
Controllability of a Class of Bimodal Discrete-Time Piecewise Linear Systems
Yurtseven, E.; Camlibel, M.K.; Heemels, W.P.M.H.
2013-01-01
In this paper we will provide algebraic necessary and sufficient conditions for the controllability/reachability/null controllability of a class of bimodal discrete-time piecewise linear systems including several instances of interest that are not covered by existing works which focus primarily on
Generalized Riemann zeta-function regularization and Casimir energy for a piecewise uniform string
International Nuclear Information System (INIS)
Li Xinzhou; Shi Xin; Zhang Jianzu.
1990-12-01
The generalized zeta-function techniques will be utilized to investigate the Casimir energy for the transverse oscillations of a piecewise uniform closed string. We find that zeta-function regularization method can lead straightforwardly to a correct result. (author). 6 refs
Near constant-time optimal piecewise LDR to HDR inverse tone mapping
Chen, Qian; Su, Guan-Ming; Yin, Peng
2015-02-01
In a backward compatible HDR image/video compression, it is a general approach to reconstruct HDR from compressed LDR as a prediction to original HDR, which is referred to as inverse tone mapping. Experimental results show that 2- piecewise 2nd order polynomial has the best mapping accuracy than 1 piece high order or 2-piecewise linear, but it is also the most time-consuming method because to find the optimal pivot point to split LDR range to 2 pieces requires exhaustive search. In this paper, we propose a fast algorithm that completes optimal 2-piecewise 2nd order polynomial inverse tone mapping in near constant time without quality degradation. We observe that in least square solution, each entry in the intermediate matrix can be written as the sum of some basic terms, which can be pre-calculated into look-up tables. Since solving the matrix becomes looking up values in tables, computation time barely differs regardless of the number of points searched. Hence, we can carry out the most thorough pivot point search to find the optimal pivot that minimizes MSE in near constant time. Experiment shows that our proposed method achieves the same PSNR performance while saving 60 times computation time compared to the traditional exhaustive search in 2-piecewise 2nd order polynomial inverse tone mapping with continuous constraint.
Model predictive control for Max-Plus-Linear and piecewise affine systems
Necoara, I.
2006-01-01
This Ph.D. thesis considers the development of new analysis and control techniques for special classes of hybrid systems and discrete event systems. Two particular classes of hybrid systems (piecewise affine systems and max-min-plus-scaling systems), and two particular classes of discrete event
Schryver, T. de; Eisinga, R.
2010-01-01
The key question in research on dismissals of head coaches in sports clubs is not whether they should happen but when they will happen. This paper applies piecewise linear regression to advance our understanding of the timing of head coach dismissals. Essentially, the regression sacrifices degrees
Transitions from phase-locked dynamics to chaos in a piecewise-linear map
DEFF Research Database (Denmark)
Zhusubaliyev, Z.T.; Mosekilde, Erik; De, S.
2008-01-01
place via border-collision fold bifurcations. We examine the transition to chaos through torus destruction in such maps. Considering a piecewise-linear normal-form map we show that this transition, by virtue of the interplay of border-collision bifurcations with period-doubling and homoclinic...
Zipf exponent of trajectory distribution in the hidden Markov model
Bochkarev, V. V.; Lerner, E. Yu
2014-03-01
This paper is the first step of generalization of the previously obtained full classification of the asymptotic behavior of the probability for Markov chain trajectories for the case of hidden Markov models. The main goal is to study the power (Zipf) and nonpower asymptotics of the frequency list of trajectories of hidden Markov frequencys and to obtain explicit formulae for the exponent of the power asymptotics. We consider several simple classes of hidden Markov models. We prove that the asymptotics for a hidden Markov model and for the corresponding Markov chain can be essentially different.
Zipf exponent of trajectory distribution in the hidden Markov model
International Nuclear Information System (INIS)
Bochkarev, V V; Lerner, E Yu
2014-01-01
This paper is the first step of generalization of the previously obtained full classification of the asymptotic behavior of the probability for Markov chain trajectories for the case of hidden Markov models. The main goal is to study the power (Zipf) and nonpower asymptotics of the frequency list of trajectories of hidden Markov frequencys and to obtain explicit formulae for the exponent of the power asymptotics. We consider several simple classes of hidden Markov models. We prove that the asymptotics for a hidden Markov model and for the corresponding Markov chain can be essentially different
Performance Modeling of Communication Networks with Markov Chains
Mo, Jeonghoon
2010-01-01
This book is an introduction to Markov chain modeling with applications to communication networks. It begins with a general introduction to performance modeling in Chapter 1 where we introduce different performance models. We then introduce basic ideas of Markov chain modeling: Markov property, discrete time Markov chain (DTMe and continuous time Markov chain (CTMe. We also discuss how to find the steady state distributions from these Markov chains and how they can be used to compute the system performance metric. The solution methodologies include a balance equation technique, limiting probab
Inferring hierarchical clustering structures by deterministic annealing
International Nuclear Information System (INIS)
Hofmann, T.; Buhmann, J.M.
1996-01-01
The unsupervised detection of hierarchical structures is a major topic in unsupervised learning and one of the key questions in data analysis and representation. We propose a novel algorithm for the problem of learning decision trees for data clustering and related problems. In contrast to many other methods based on successive tree growing and pruning, we propose an objective function for tree evaluation and we derive a non-greedy technique for tree growing. Applying the principles of maximum entropy and minimum cross entropy, a deterministic annealing algorithm is derived in a meanfield approximation. This technique allows us to canonically superimpose tree structures and to fit parameters to averaged or open-quote fuzzified close-quote trees
Mechanics from Newton's laws to deterministic chaos
Scheck, Florian
2018-01-01
This book covers all topics in mechanics from elementary Newtonian mechanics, the principles of canonical mechanics and rigid body mechanics to relativistic mechanics and nonlinear dynamics. It was among the first textbooks to include dynamical systems and deterministic chaos in due detail. As compared to the previous editions the present 6th edition is updated and revised with more explanations, additional examples and problems with solutions, together with new sections on applications in science. Symmetries and invariance principles, the basic geometric aspects of mechanics as well as elements of continuum mechanics also play an important role. The book will enable the reader to develop general principles from which equations of motion follow, to understand the importance of canonical mechanics and of symmetries as a basis for quantum mechanics, and to get practice in using general theoretical concepts and tools that are essential for all branches of physics. The book contains more than 150 problems ...
Deterministic Diffusion in Delayed Coupled Maps
International Nuclear Information System (INIS)
Sozanski, M.
2005-01-01
Coupled Map Lattices (CML) are discrete time and discrete space dynamical systems used for modeling phenomena arising in nonlinear systems with many degrees of freedom. In this work, the dynamical and statistical properties of a modified version of the CML with global coupling are considered. The main modification of the model is the extension of the coupling over a set of local map states corresponding to different time iterations. The model with both stochastic and chaotic one-dimensional local maps is studied. Deterministic diffusion in the CML under variation of a control parameter is analyzed for unimodal maps. As a main result, simple relations between statistical and dynamical measures are found for the model and the cases where substituting nonlinear lattices with simpler processes is possible are presented. (author)
Deterministic effects of interventional radiology procedures
International Nuclear Information System (INIS)
Shope, Thomas B.
1997-01-01
The purpose of this paper is to describe deterministic radiation injuries reported to the Food and Drug Administration (FDA) that resulted from therapeutic, interventional procedures performed under fluoroscopic guidance, and to investigate the procedure or equipment-related factors that may have contributed to the injury. Reports submitted to the FDA under both mandatory and voluntary reporting requirements which described radiation-induced skin injuries from fluoroscopy were investigated. Serious skin injuries, including moist desquamation and tissues necrosis, have occurred since 1992. These injuries have resulted from a variety of interventional procedures which have required extended periods of fluoroscopy compared to typical diagnostic procedures. Facilities conducting therapeutic interventional procedures need to be aware of the potential for patient radiation injury and take appropriate steps to limit the potential for injury. (author)
Deterministic Chaos in Radon Time Variation
International Nuclear Information System (INIS)
Planinic, J.; Vukovic, B.; Radolic, V.; Faj, Z.; Stanic, D.
2003-01-01
Radon concentrations were continuously measured outdoors, in living room and basement in 10-minute intervals for a month. The radon time series were analyzed by comparing algorithms to extract phase-space dynamical information. The application of fractal methods enabled to explore the chaotic nature of radon in the atmosphere. The computed fractal dimensions, such as Hurst exponent (H) from the rescaled range analysis, Lyapunov exponent (λ ) and attractor dimension, provided estimates of the degree of chaotic behavior. The obtained low values of the Hurst exponent (0< H<0.5) indicated anti-persistent behavior (non random changes) of the time series, but the positive values of the λ pointed out the grate sensitivity on initial conditions and appearing deterministic chaos by radon time variations. The calculated fractal dimensions of attractors indicated more influencing (meteorological) parameters on radon in the atmosphere. (author)
Radon time variations and deterministic chaos
Energy Technology Data Exchange (ETDEWEB)
Planinic, J. E-mail: planinic@pedos.hr; Vukovic, B.; Radolic, V
2004-07-01
Radon concentrations were continuously measured outdoors, in the living room and in the basement at 10 min intervals for a month. Radon time series were analyzed by comparing algorithms to extract phase space dynamical information. The application of fractal methods enabled exploration of the chaotic nature of radon in atmosphere. The computed fractal dimensions, such as the Hurst exponent (H) from the rescaled range analysis, Lyapunov exponent ({lambda}) and attractor dimension, provided estimates of the degree of chaotic behavior. The obtained low values of the Hurst exponent (0
Radon time variations and deterministic chaos
International Nuclear Information System (INIS)
Planinic, J.; Vukovic, B.; Radolic, V.
2004-01-01
Radon concentrations were continuously measured outdoors, in the living room and in the basement at 10 min intervals for a month. Radon time series were analyzed by comparing algorithms to extract phase space dynamical information. The application of fractal methods enabled exploration of the chaotic nature of radon in atmosphere. The computed fractal dimensions, such as the Hurst exponent (H) from the rescaled range analysis, Lyapunov exponent (λ) and attractor dimension, provided estimates of the degree of chaotic behavior. The obtained low values of the Hurst exponent (0< H<0.5) indicated anti-persistent behavior (non-random changes) of the time series, but the positive values of λ pointed out the grate sensitivity on initial conditions and the deterministic chaos that appeared due to radon time variations. The calculated fractal dimensions of attractors indicated more influencing (meteorological) parameters on radon in the atmosphere
Deterministic SLIR model for tuberculosis disease mapping
Aziz, Nazrina; Diah, Ijlal Mohd; Ahmad, Nazihah; Kasim, Maznah Mat
2017-11-01
Tuberculosis (TB) occurs worldwide. It can be transmitted to others directly through air when active TB persons sneeze, cough or spit. In Malaysia, it was reported that TB cases had been recognized as one of the most infectious disease that lead to death. Disease mapping is one of the methods that can be used as the prevention strategies since it can displays clear picture for the high-low risk areas. Important thing that need to be considered when studying the disease occurrence is relative risk estimation. The transmission of TB disease is studied through mathematical model. Therefore, in this study, deterministic SLIR models are used to estimate relative risk for TB disease transmission.
Primality deterministic and primality probabilistic tests
Directory of Open Access Journals (Sweden)
Alfredo Rizzi
2007-10-01
Full Text Available In this paper the A. comments the importance of prime numbers in mathematics and in cryptography. He remembers the very important researches of Eulero, Fermat, Legen-re, Rieman and others scholarships. There are many expressions that give prime numbers. Between them Mersenne’s primes have interesting properties. There are also many conjectures that still have to be demonstrated or rejected. The primality deterministic tests are the algorithms that permit to establish if a number is prime or not. There are not applicable in many practical situations, for instance in public key cryptography, because the computer time would be very long. The primality probabilistic tests consent to verify the null hypothesis: the number is prime. In the paper there are comments about the most important statistical tests.
Coding with partially hidden Markov models
DEFF Research Database (Denmark)
Forchhammer, Søren; Rissanen, J.
1995-01-01
Partially hidden Markov models (PHMM) are introduced. They are a variation of the hidden Markov models (HMM) combining the power of explicit conditioning on past observations and the power of using hidden states. (P)HMM may be combined with arithmetic coding for lossless data compression. A general...... 2-part coding scheme for given model order but unknown parameters based on PHMM is presented. A forward-backward reestimation of parameters with a redefined backward variable is given for these models and used for estimating the unknown parameters. Proof of convergence of this reestimation is given....... The PHMM structure and the conditions of the convergence proof allows for application of the PHMM to image coding. Relations between the PHMM and hidden Markov models (HMM) are treated. Results of coding bi-level images with the PHMM coding scheme is given. The results indicate that the PHMM can adapt...
Markov and mixed models with applications
DEFF Research Database (Denmark)
Mortensen, Stig Bousgaard
This thesis deals with mathematical and statistical models with focus on applications in pharmacokinetic and pharmacodynamic (PK/PD) modelling. These models are today an important aspect of the drug development in the pharmaceutical industry and continued research in statistical methodology within...... or uncontrollable factors in an individual. Modelling using SDEs also provides new tools for estimation of unknown inputs to a system and is illustrated with an application to estimation of insulin secretion rates in diabetic patients. Models for the eect of a drug is a broader area since drugs may affect...... for non-parametric estimation of Markov processes are proposed to give a detailed description of the sleep process during the night. Statistically the Markov models considered for sleep states are closely related to the PK models based on SDEs as both models share the Markov property. When the models...
Consistent Estimation of Partition Markov Models
Directory of Open Access Journals (Sweden)
Jesús E. García
2017-04-01
Full Text Available The Partition Markov Model characterizes the process by a partition L of the state space, where the elements in each part of L share the same transition probability to an arbitrary element in the alphabet. This model aims to answer the following questions: what is the minimal number of parameters needed to specify a Markov chain and how to estimate these parameters. In order to answer these questions, we build a consistent strategy for model selection which consist of: giving a size n realization of the process, finding a model within the Partition Markov class, with a minimal number of parts to represent the process law. From the strategy, we derive a measure that establishes a metric in the state space. In addition, we show that if the law of the process is Markovian, then, eventually, when n goes to infinity, L will be retrieved. We show an application to model internet navigation patterns.
International Nuclear Information System (INIS)
Calloo, A.A.
2012-01-01
In reactor physics, calculation schemes with deterministic codes are validated with respect to a reference Monte Carlo code. The remaining biases are attributed to the approximations and models induced by the multigroup theory (self-shielding models and expansion of the scattering law using Legendre polynomials) to represent physical phenomena (resonant absorption and scattering anisotropy respectively). This work focuses on the relevance of a polynomial expansion to model the scattering law. Since the outset of reactor physics, the latter has been expanded on a truncated Legendre polynomial basis. However, the transfer cross sections are highly anisotropic, with non-zero values for a very small range of the cosine of the scattering angle. Besides, the finer the energy mesh and the lighter the scattering nucleus, the more exacerbated is the peaked shape of this cross section. As such, the Legendre expansion is less suited to represent the scattering law. Furthermore, this model induces negative values which are non-physical. In this work, various scattering laws are briefly described and the limitations of the existing model are pointed out. Hence, piecewise-constant functions have been used to represent the multigroup scattering cross section. This representation requires a different model for the diffusion source. The discrete ordinates method which is widely employed to solve the transport equation has been adapted. Thus, the finite volume method for angular discretization has been developed and implemented in Paris environment which hosts the S n solver, Snatch. The angular finite volume method has been compared to the collocation method with Legendre moments to ensure its proper performance. Moreover, unlike the latter, this method is adapted for both the Legendre moments and the piecewise-constant functions representations of the scattering cross section. This hybrid-source method has been validated for different cases: fuel cell in infinite lattice
Markov decision processes in artificial intelligence
Sigaud, Olivier
2013-01-01
Markov Decision Processes (MDPs) are a mathematical framework for modeling sequential decision problems under uncertainty as well as Reinforcement Learning problems. Written by experts in the field, this book provides a global view of current research using MDPs in Artificial Intelligence. It starts with an introductory presentation of the fundamental aspects of MDPs (planning in MDPs, Reinforcement Learning, Partially Observable MDPs, Markov games and the use of non-classical criteria). Then it presents more advanced research trends in the domain and gives some concrete examples using illustr
Markov bridges, bisection and variance reduction
DEFF Research Database (Denmark)
Asmussen, Søren; Hobolth, Asger
. In this paper we firstly consider the problem of generating sample paths from a continuous-time Markov chain conditioned on the endpoints using a new algorithm based on the idea of bisection. Secondly we study the potential of the bisection algorithm for variance reduction. In particular, examples are presented......Time-continuous Markov jump processes is a popular modelling tool in disciplines ranging from computational finance and operations research to human genetics and genomics. The data is often sampled at discrete points in time, and it can be useful to simulate sample paths between the datapoints...
Inhomogeneous Markov Models for Describing Driving Patterns
DEFF Research Database (Denmark)
Iversen, Emil Banning; Møller, Jan K.; Morales, Juan Miguel
2017-01-01
. Specifically, an inhomogeneous Markov model that captures the diurnal variation in the use of a vehicle is presented. The model is defined by the time-varying probabilities of starting and ending a trip, and is justified due to the uncertainty associated with the use of the vehicle. The model is fitted to data...... collected from the actual utilization of a vehicle. Inhomogeneous Markov models imply a large number of parameters. The number of parameters in the proposed model is reduced using B-splines....
Inhomogeneous Markov Models for Describing Driving Patterns
DEFF Research Database (Denmark)
Iversen, Jan Emil Banning; Møller, Jan Kloppenborg; Morales González, Juan Miguel
. Specically, an inhomogeneous Markov model that captures the diurnal variation in the use of a vehicle is presented. The model is dened by the time-varying probabilities of starting and ending a trip and is justied due to the uncertainty associated with the use of the vehicle. The model is tted to data...... collected from the actual utilization of a vehicle. Inhomogeneous Markov models imply a large number of parameters. The number of parameters in the proposed model is reduced using B-splines....
Detecting Structural Breaks using Hidden Markov Models
DEFF Research Database (Denmark)
Ntantamis, Christos
Testing for structural breaks and identifying their location is essential for econometric modeling. In this paper, a Hidden Markov Model (HMM) approach is used in order to perform these tasks. Breaks are defined as the data points where the underlying Markov Chain switches from one state to another....... The estimation of the HMM is conducted using a variant of the Iterative Conditional Expectation-Generalized Mixture (ICE-GEMI) algorithm proposed by Delignon et al. (1997), that permits analysis of the conditional distributions of economic data and allows for different functional forms across regimes...
Predicting Protein Secondary Structure with Markov Models
DEFF Research Database (Denmark)
Fischer, Paul; Larsen, Simon; Thomsen, Claus
2004-01-01
we are considering here, is to predict the secondary structure from the primary one. To this end we train a Markov model on training data and then use it to classify parts of unknown protein sequences as sheets, helices or coils. We show how to exploit the directional information contained...... in the Markov model for this task. Classifications that are purely based on statistical models might not always be biologically meaningful. We present combinatorial methods to incorporate biological background knowledge to enhance the prediction performance....
CSL model checking of deterministic and stochastic Petri nets
Martinez Verdugo, J.M.; Haverkort, Boudewijn R.H.M.; German, R.; Heindl, A.
2006-01-01
Deterministic and Stochastic Petri Nets (DSPNs) are a widely used high-level formalism for modeling discrete-event systems where events may occur either without consuming time, after a deterministic time, or after an exponentially distributed time. The underlying process dened by DSPNs, under
Recognition of deterministic ETOL languages in logarithmic space
DEFF Research Database (Denmark)
Jones, Neil D.; Skyum, Sven
1977-01-01
It is shown that if G is a deterministic ETOL system, there is a nondeterministic log space algorithm to determine membership in L(G). Consequently, every deterministic ETOL language is recognizable in polynomial time. As a corollary, all context-free languages of finite index, and all Indian...
Prediction of Annual Rainfall Pattern Using Hidden Markov Model ...
African Journals Online (AJOL)
ADOWIE PERE
Hidden Markov model is very influential in stochastic world because of its ... the earth from the clouds. The usual ... Rainfall modelling and ... Markov Models have become popular tools ... environment sciences, University of Jos, plateau state,.
Extending Markov Automata with State and Action Rewards
Guck, Dennis; Timmer, Mark; Blom, Stefan; Bertrand, N.; Bortolussi, L.
This presentation introduces the Markov Reward Automaton (MRA), an extension of the Markov automaton that allows the modelling of systems incorporating rewards in addition to nondeterminism, discrete probabilistic choice and continuous stochastic timing. Our models support both rewards that are
Experimental aspects of deterministic secure quantum key distribution
Energy Technology Data Exchange (ETDEWEB)
Walenta, Nino; Korn, Dietmar; Puhlmann, Dirk; Felbinger, Timo; Hoffmann, Holger; Ostermeyer, Martin [Universitaet Potsdam (Germany). Institut fuer Physik; Bostroem, Kim [Universitaet Muenster (Germany)
2008-07-01
Most common protocols for quantum key distribution (QKD) use non-deterministic algorithms to establish a shared key. But deterministic implementations can allow for higher net key transfer rates and eavesdropping detection rates. The Ping-Pong coding scheme by Bostroem and Felbinger[1] employs deterministic information encoding in entangled states with its characteristic quantum channel from Bob to Alice and back to Bob. Based on a table-top implementation of this protocol with polarization-entangled photons fundamental advantages as well as practical issues like transmission losses, photon storage and requirements for progress towards longer transmission distances are discussed and compared to non-deterministic protocols. Modifications of common protocols towards a deterministic quantum key distribution are addressed.
Bikowski, J.; Huisman, J.A.; Vrugt, J.A.; Vereecken, H.; van der Kruk, J.
2012-01-01
Ground-penetrating radar (GPR) data affected by waveguide dispersion are not straightforward to analyse. Therefore, waveguide dispersed common midpoint measurements are typically interpreted using so-called dispersion curves, which describe the phase velocity as a function of frequency. These
Perturbation theory for Markov chains via Wasserstein distance
Rudolf, Daniel; Schweizer, Nikolaus
2017-01-01
Perturbation theory for Markov chains addresses the question of how small differences in the transition probabilities of Markov chains are reflected in differences between their distributions. We prove powerful and flexible bounds on the distance of the nth step distributions of two Markov chains
Quantum Enhanced Inference in Markov Logic Networks.
Wittek, Peter; Gogolin, Christian
2017-04-19
Markov logic networks (MLNs) reconcile two opposing schools in machine learning and artificial intelligence: causal networks, which account for uncertainty extremely well, and first-order logic, which allows for formal deduction. An MLN is essentially a first-order logic template to generate Markov networks. Inference in MLNs is probabilistic and it is often performed by approximate methods such as Markov chain Monte Carlo (MCMC) Gibbs sampling. An MLN has many regular, symmetric structures that can be exploited at both first-order level and in the generated Markov network. We analyze the graph structures that are produced by various lifting methods and investigate the extent to which quantum protocols can be used to speed up Gibbs sampling with state preparation and measurement schemes. We review different such approaches, discuss their advantages, theoretical limitations, and their appeal to implementations. We find that a straightforward application of a recent result yields exponential speedup compared to classical heuristics in approximate probabilistic inference, thereby demonstrating another example where advanced quantum resources can potentially prove useful in machine learning.
Markov Random Fields on Triangle Meshes
DEFF Research Database (Denmark)
Andersen, Vedrana; Aanæs, Henrik; Bærentzen, Jakob Andreas
2010-01-01
In this paper we propose a novel anisotropic smoothing scheme based on Markov Random Fields (MRF). Our scheme is formulated as two coupled processes. A vertex process is used to smooth the mesh by displacing the vertices according to a MRF smoothness prior, while an independent edge process label...
A Martingale Decomposition of Discrete Markov Chains
DEFF Research Database (Denmark)
Hansen, Peter Reinhard
We consider a multivariate time series whose increments are given from a homogeneous Markov chain. We show that the martingale component of this process can be extracted by a filtering method and establish the corresponding martingale decomposition in closed-form. This representation is useful fo...
Renewal characterization of Markov modulated Poisson processes
Directory of Open Access Journals (Sweden)
Marcel F. Neuts
1989-01-01
Full Text Available A Markov Modulated Poisson Process (MMPP M(t defined on a Markov chain J(t is a pure jump process where jumps of M(t occur according to a Poisson process with intensity λi whenever the Markov chain J(t is in state i. M(t is called strongly renewal (SR if M(t is a renewal process for an arbitrary initial probability vector of J(t with full support on P={i:λi>0}. M(t is called weakly renewal (WR if there exists an initial probability vector of J(t such that the resulting MMPP is a renewal process. The purpose of this paper is to develop general characterization theorems for the class SR and some sufficiency theorems for the class WR in terms of the first passage times of the bivariate Markov chain [J(t,M(t]. Relevance to the lumpability of J(t is also studied.
Evaluation of Usability Utilizing Markov Models
Penedo, Janaina Rodrigues; Diniz, Morganna; Ferreira, Simone Bacellar Leal; Silveira, Denis S.; Capra, Eliane
2012-01-01
Purpose: The purpose of this paper is to analyze the usability of a remote learning system in its initial development phase, using a quantitative usability evaluation method through Markov models. Design/methodology/approach: The paper opted for an exploratory study. The data of interest of the research correspond to the possible accesses of users…
Bayesian analysis for reversible Markov chains
Diaconis, P.; Rolles, S.W.W.
2006-01-01
We introduce a natural conjugate prior for the transition matrix of a reversible Markov chain. This allows estimation and testing. The prior arises from random walk with reinforcement in the same way the Dirichlet prior arises from Pólya’s urn. We give closed form normalizing constants, a simple
Bisimulation and Simulation Relations for Markov Chains
Baier, Christel; Hermanns, H.; Katoen, Joost P.; Wolf, Verena; Aceto, L.; Gordon, A.
2006-01-01
Formal notions of bisimulation and simulation relation play a central role for any kind of process algebra. This short paper sketches the main concepts for bisimulation and simulation relations for probabilistic systems, modelled by discrete- or continuous-time Markov chains.
Discounted Markov games : generalized policy iteration method
Wal, van der J.
1978-01-01
In this paper, we consider two-person zero-sum discounted Markov games with finite state and action spaces. We show that the Newton-Raphson or policy iteration method as presented by Pollats-chek and Avi-Itzhak does not necessarily converge, contradicting a proof of Rao, Chandrasekaran, and Nair.
Hidden Markov Models for Human Genes
DEFF Research Database (Denmark)
Baldi, Pierre; Brunak, Søren; Chauvin, Yves
1997-01-01
We analyse the sequential structure of human genomic DNA by hidden Markov models. We apply models of widely different design: conventional left-right constructs and models with a built-in periodic architecture. The models are trained on segments of DNA sequences extracted such that they cover com...
Markov Trends in Macroeconomic Time Series
R. Paap (Richard)
1997-01-01
textabstractMany macroeconomic time series are characterised by long periods of positive growth, expansion periods, and short periods of negative growth, recessions. A popular model to describe this phenomenon is the Markov trend, which is a stochastic segmented trend where the slope depends on the
Optimal dividend distribution under Markov regime switching
Jiang, Z.; Pistorius, M.
2012-01-01
We investigate the problem of optimal dividend distribution for a company in the presence of regime shifts. We consider a company whose cumulative net revenues evolve as a Brownian motion with positive drift that is modulated by a finite state Markov chain, and model the discount rate as a
Revisiting Weak Simulation for Substochastic Markov Chains
DEFF Research Database (Denmark)
Jansen, David N.; Song, Lei; Zhang, Lijun
2013-01-01
of the logic PCTL\\x, and its completeness was conjectured. We revisit this result and show that soundness does not hold in general, but only for Markov chains without divergence. It is refuted for some systems with substochastic distributions. Moreover, we provide a counterexample to completeness...
Multi-dimensional quasitoeplitz Markov chains
Directory of Open Access Journals (Sweden)
Alexander N. Dudin
1999-01-01
Full Text Available This paper deals with multi-dimensional quasitoeplitz Markov chains. We establish a sufficient equilibrium condition and derive a functional matrix equation for the corresponding vector-generating function, whose solution is given algorithmically. The results are demonstrated in the form of examples and applications in queues with BMAP-input, which operate in synchronous random environment.
Markov chains with quasitoeplitz transition matrix
Directory of Open Access Journals (Sweden)
Alexander M. Dukhovny
1989-01-01
Full Text Available This paper investigates a class of Markov chains which are frequently encountered in various applications (e.g. queueing systems, dams and inventories with feedback. Generating functions of transient and steady state probabilities are found by solving a special Riemann boundary value problem on the unit circle. A criterion of ergodicity is established.
Markov Chain Estimation of Avian Seasonal Fecundity
To explore the consequences of modeling decisions on inference about avian seasonal fecundity we generalize previous Markov chain (MC) models of avian nest success to formulate two different MC models of avian seasonal fecundity that represent two different ways to model renestin...
Noise can speed convergence in Markov chains.
Franzke, Brandon; Kosko, Bart
2011-10-01
A new theorem shows that noise can speed convergence to equilibrium in discrete finite-state Markov chains. The noise applies to the state density and helps the Markov chain explore improbable regions of the state space. The theorem ensures that a stochastic-resonance noise benefit exists for states that obey a vector-norm inequality. Such noise leads to faster convergence because the noise reduces the norm components. A corollary shows that a noise benefit still occurs if the system states obey an alternate norm inequality. This leads to a noise-benefit algorithm that requires knowledge of the steady state. An alternative blind algorithm uses only past state information to achieve a weaker noise benefit. Simulations illustrate the predicted noise benefits in three well-known Markov models. The first model is a two-parameter Ehrenfest diffusion model that shows how noise benefits can occur in the class of birth-death processes. The second model is a Wright-Fisher model of genotype drift in population genetics. The third model is a chemical reaction network of zeolite crystallization. A fourth simulation shows a convergence rate increase of 64% for states that satisfy the theorem and an increase of 53% for states that satisfy the corollary. A final simulation shows that even suboptimal noise can speed convergence if the noise applies over successive time cycles. Noise benefits tend to be sharpest in Markov models that do not converge quickly and that do not have strong absorbing states.
Model Checking Infinite-State Markov Chains
Remke, Anne Katharina Ingrid; Haverkort, Boudewijn R.H.M.; Cloth, L.
2004-01-01
In this paper algorithms for model checking CSL (continuous stochastic logic) against infinite-state continuous-time Markov chains of so-called quasi birth-death type are developed. In doing so we extend the applicability of CSL model checking beyond the recently proposed case for finite-state
Model Checking Markov Chains: Techniques and Tools
Zapreev, I.S.
2008-01-01
This dissertation deals with four important aspects of model checking Markov chains: the development of efficient model-checking tools, the improvement of model-checking algorithms, the efficiency of the state-space reduction techniques, and the development of simulation-based model-checking
Nonlinearly perturbed semi-Markov processes
Silvestrov, Dmitrii
2017-01-01
The book presents new methods of asymptotic analysis for nonlinearly perturbed semi-Markov processes with a finite phase space. These methods are based on special time-space screening procedures for sequential phase space reduction of semi-Markov processes combined with the systematical use of operational calculus for Laurent asymptotic expansions. Effective recurrent algorithms are composed for getting asymptotic expansions, without and with explicit upper bounds for remainders, for power moments of hitting times, stationary and conditional quasi-stationary distributions for nonlinearly perturbed semi-Markov processes. These results are illustrated by asymptotic expansions for birth-death-type semi-Markov processes, which play an important role in various applications. The book will be a useful contribution to the continuing intensive studies in the area. It is an essential reference for theoretical and applied researchers in the field of stochastic processes and their applications that will cont...
Quantum Enhanced Inference in Markov Logic Networks
Wittek, Peter; Gogolin, Christian
2017-04-01
Markov logic networks (MLNs) reconcile two opposing schools in machine learning and artificial intelligence: causal networks, which account for uncertainty extremely well, and first-order logic, which allows for formal deduction. An MLN is essentially a first-order logic template to generate Markov networks. Inference in MLNs is probabilistic and it is often performed by approximate methods such as Markov chain Monte Carlo (MCMC) Gibbs sampling. An MLN has many regular, symmetric structures that can be exploited at both first-order level and in the generated Markov network. We analyze the graph structures that are produced by various lifting methods and investigate the extent to which quantum protocols can be used to speed up Gibbs sampling with state preparation and measurement schemes. We review different such approaches, discuss their advantages, theoretical limitations, and their appeal to implementations. We find that a straightforward application of a recent result yields exponential speedup compared to classical heuristics in approximate probabilistic inference, thereby demonstrating another example where advanced quantum resources can potentially prove useful in machine learning.
Markov chain of distances between parked cars
International Nuclear Information System (INIS)
Seba, Petr
2008-01-01
We describe the distribution of distances between parked cars as a solution of certain Markov processes and show that its solution is obtained with the help of a distributional fixed point equation. Under certain conditions the process is solved explicitly. The resulting probability density is compared with the actual parking data measured in the city. (fast track communication)
Continuity Properties of Distances for Markov Processes
DEFF Research Database (Denmark)
Jaeger, Manfred; Mao, Hua; Larsen, Kim Guldstrand
2014-01-01
In this paper we investigate distance functions on finite state Markov processes that measure the behavioural similarity of non-bisimilar processes. We consider both probabilistic bisimilarity metrics, and trace-based distances derived from standard Lp and Kullback-Leibler distances. Two desirable...
Model Checking Structured Infinite Markov Chains
Remke, Anne Katharina Ingrid
2008-01-01
In the past probabilistic model checking hast mostly been restricted to finite state models. This thesis explores the possibilities of model checking with continuous stochastic logic (CSL) on infinite-state Markov chains. We present an in-depth treatment of model checking algorithms for two special
Hidden Markov models for labeled sequences
DEFF Research Database (Denmark)
Krogh, Anders Stærmose
1994-01-01
A hidden Markov model for labeled observations, called a class HMM, is introduced and a maximum likelihood method is developed for estimating the parameters of the model. Instead of training it to model the statistics of the training sequences it is trained to optimize recognition. It resembles MMI...
Efficient Modelling and Generation of Markov Automata
Koutny, M.; Timmer, Mark; Ulidowski, I.; Katoen, Joost P.; van de Pol, Jan Cornelis; Stoelinga, Mariëlle Ida Antoinette
This paper introduces a framework for the efficient modelling and generation of Markov automata. It consists of (1) the data-rich process-algebraic language MAPA, allowing concise modelling of systems with nondeterminism, probability and Markovian timing; (2) a restricted form of the language, the
A Metrized Duality Theorem for Markov Processes
DEFF Research Database (Denmark)
Kozen, Dexter; Mardare, Radu Iulian; Panangaden, Prakash
2014-01-01
We extend our previous duality theorem for Markov processes by equipping the processes with a pseudometric and the algebras with a notion of metric diameter. We are able to show that the isomorphisms of our previous duality theorem become isometries in this quantitative setting. This opens the wa...
Deterministic models for energy-loss straggling
International Nuclear Information System (INIS)
Prinja, A.K.; Gleicher, F.; Dunham, G.; Morel, J.E.
1999-01-01
Inelastic ion interactions with target electrons are dominated by extremely small energy transfers that are difficult to resolve numerically. The continuous-slowing-down (CSD) approximation is then commonly employed, which, however, only preserves the mean energy loss per collision through the stopping power, S(E) = ∫ 0 ∞ dEprime (E minus Eprime) σ s (E → Eprime). To accommodate energy loss straggling, a Gaussian distribution with the correct mean-squared energy loss (akin to a Fokker-Planck approximation in energy) is commonly used in continuous-energy Monte Carlo codes. Although this model has the unphysical feature that ions can be upscattered, it nevertheless yields accurate results. A multigroup model for energy loss straggling was recently presented for use in multigroup Monte Carlo codes or in deterministic codes that use multigroup data. The method has the advantage that the mean and mean-squared energy loss are preserved without unphysical upscatter and hence is computationally efficient. Results for energy spectra compared extremely well with Gaussian distributions under the idealized conditions for which the Gaussian may be considered to be exact. Here, the authors present more consistent comparisons by extending the method to accommodate upscatter and, further, compare both methods with exact solutions obtained from an analog Monte Carlo simulation, for a straight-ahead transport problem
A Deterministic Approach to Earthquake Prediction
Directory of Open Access Journals (Sweden)
Vittorio Sgrigna
2012-01-01
Full Text Available The paper aims at giving suggestions for a deterministic approach to investigate possible earthquake prediction and warning. A fundamental contribution can come by observations and physical modeling of earthquake precursors aiming at seeing in perspective the phenomenon earthquake within the framework of a unified theory able to explain the causes of its genesis, and the dynamics, rheology, and microphysics of its preparation, occurrence, postseismic relaxation, and interseismic phases. Studies based on combined ground and space observations of earthquake precursors are essential to address the issue. Unfortunately, up to now, what is lacking is the demonstration of a causal relationship (with explained physical processes and looking for a correlation between data gathered simultaneously and continuously by space observations and ground-based measurements. In doing this, modern and/or new methods and technologies have to be adopted to try to solve the problem. Coordinated space- and ground-based observations imply available test sites on the Earth surface to correlate ground data, collected by appropriate networks of instruments, with space ones detected on board of Low-Earth-Orbit (LEO satellites. Moreover, a new strong theoretical scientific effort is necessary to try to understand the physics of the earthquake.
Deterministic Approach to Detect Heart Sound Irregularities
Directory of Open Access Journals (Sweden)
Richard Mengko
2017-07-01
Full Text Available A new method to detect heart sound that does not require machine learning is proposed. The heart sound is a time series event which is generated by the heart mechanical system. From the analysis of heart sound S-transform and the understanding of how heart works, it can be deducted that each heart sound component has unique properties in terms of timing, frequency, and amplitude. Based on these facts, a deterministic method can be designed to identify each heart sound components. The recorded heart sound then can be printed with each component correctly labeled. This greatly help the physician to diagnose the heart problem. The result shows that most known heart sounds were successfully detected. There are some murmur cases where the detection failed. This can be improved by adding more heuristics including setting some initial parameters such as noise threshold accurately, taking into account the recording equipment and also the environmental condition. It is expected that this method can be integrated into an electronic stethoscope biomedical system.
Deterministic dense coding and entanglement entropy
International Nuclear Information System (INIS)
Bourdon, P. S.; Gerjuoy, E.; McDonald, J. P.; Williams, H. T.
2008-01-01
We present an analytical study of the standard two-party deterministic dense-coding protocol, under which communication of perfectly distinguishable messages takes place via a qudit from a pair of nonmaximally entangled qudits in a pure state |ψ>. Our results include the following: (i) We prove that it is possible for a state |ψ> with lower entanglement entropy to support the sending of a greater number of perfectly distinguishable messages than one with higher entanglement entropy, confirming a result suggested via numerical analysis in Mozes et al. [Phys. Rev. A 71, 012311 (2005)]. (ii) By explicit construction of families of local unitary operators, we verify, for dimensions d=3 and d=4, a conjecture of Mozes et al. about the minimum entanglement entropy that supports the sending of d+j messages, 2≤j≤d-1; moreover, we show that the j=2 and j=d-1 cases of the conjecture are valid in all dimensions. (iii) Given that |ψ> allows the sending of K messages and has √(λ 0 ) as its largest Schmidt coefficient, we show that the inequality λ 0 ≤d/K, established by Wu et al. [Phys. Rev. A 73, 042311 (2006)], must actually take the form λ 0 < d/K if K=d+1, while our constructions of local unitaries show that equality can be realized if K=d+2 or K=2d-1
Analysis of pinching in deterministic particle separation
Risbud, Sumedh; Luo, Mingxiang; Frechette, Joelle; Drazer, German
2011-11-01
We investigate the problem of spherical particles vertically settling parallel to Y-axis (under gravity), through a pinching gap created by an obstacle (spherical or cylindrical, center at the origin) and a wall (normal to X axis), to uncover the physics governing microfluidic separation techniques such as deterministic lateral displacement and pinched flow fractionation: (1) theoretically, by linearly superimposing the resistances offered by the wall and the obstacle separately, (2) computationally, using the lattice Boltzmann method for particulate systems and (3) experimentally, by conducting macroscopic experiments. Both, theory and simulations, show that for a given initial separation between the particle centre and the Y-axis, presence of a wall pushes the particles closer to the obstacle, than its absence. Experimentally, this is expected to result in an early onset of the short-range repulsive forces caused by solid-solid contact. We indeed observe such an early onset, which we quantify by measuring the asymmetry in the trajectories of the spherical particles around the obstacle. This work is partially supported by the National Science Foundation Grant Nos. CBET- 0731032, CMMI-0748094, and CBET-0954840.
Energy Technology Data Exchange (ETDEWEB)
Bailey, Teresa S. [Texas A and M University, Department of Nuclear Engineering, College Station, TX 77843-3133 (United States)], E-mail: baileyte@tamu.edu; Adams, Marvin L. [Texas A and M University, Department of Nuclear Engineering, College Station, TX 77843-3133 (United States)], E-mail: mladams@tamu.edu; Yang, Brian [Lawrence Livermore National Laboratory, Livermore, CA 94551 (United States); Zika, Michael R. [Lawrence Livermore National Laboratory, Livermore, CA 94551 (United States)], E-mail: zika@llnl.gov
2008-04-01
We develop a piecewise linear (PWL) Galerkin finite element spatial discretization for the multi-dimensional radiation diffusion equation. It uses recently introduced piecewise linear weight and basis functions in the finite element approximation and it can be applied on arbitrary polygonal (2D) or polyhedral (3D) grids. We first demonstrate some analytical properties of the PWL method and perform a simple mode analysis to compare the PWL method with Palmer's vertex-centered finite-volume method and with a bilinear continuous finite element method. We then show that this new PWL method gives solutions comparable to those from Palmer's. However, since the PWL method produces a symmetric positive-definite coefficient matrix, it should be substantially more computationally efficient than Palmer's method, which produces an asymmetric matrix. We conclude that the Galerkin PWL method is an attractive option for solving diffusion equations on unstructured grids.
Numerical Solution of Piecewise Constant Delay Systems Based on a Hybrid Framework
Directory of Open Access Journals (Sweden)
H. R. Marzban
2016-01-01
Full Text Available An efficient numerical scheme for solving delay differential equations with a piecewise constant delay function is developed in this paper. The proposed approach is based on a hybrid of block-pulse functions and Taylor’s polynomials. The operational matrix of delay corresponding to the proposed hybrid functions is introduced. The sparsity of this matrix significantly reduces the computation time and memory requirement. The operational matrices of integration, delay, and product are employed to transform the problem under consideration into a system of algebraic equations. It is shown that the developed approach is also applicable to a special class of nonlinear piecewise constant delay differential equations. Several numerical experiments are examined to verify the validity and applicability of the presented technique.
Directory of Open Access Journals (Sweden)
H. Vazquez-Leal
2014-01-01
Full Text Available We present a homotopy continuation method (HCM for finding multiple operating points of nonlinear circuits composed of devices modelled by using piecewise linear (PWL representations. We propose an adaptation of the modified spheres path tracking algorithm to trace the homotopy trajectories of PWL circuits. In order to assess the benefits of this proposal, four nonlinear circuits composed of piecewise linear modelled devices are analysed to determine their multiple operating points. The results show that HCM can find multiple solutions within a single homotopy trajectory. Furthermore, we take advantage of the fact that homotopy trajectories are PWL curves meant to replace the multidimensional interpolation and fine tuning stages of the path tracking algorithm with a simple and highly accurate procedure based on the parametric straight line equation.
Energy Technology Data Exchange (ETDEWEB)
Bailey, T.S.; Adams, M.L. [Texas A M Univ., Dept. of Nuclear Engineering, College Station, TX (United States); Yang, B.; Zika, M.R. [Lawrence Livermore National Lab., Livermore, CA (United States)
2005-07-01
We develop a piecewise linear (PWL) Galerkin finite element spatial discretization for the multi-dimensional radiation diffusion equation. It uses piecewise linear weight and basis functions in the finite element approximation, and it can be applied on arbitrary polygonal (2-dimensional) or polyhedral (3-dimensional) grids. We show that this new PWL method gives solutions comparable to those from Palmer's finite-volume method. However, since the PWL method produces a symmetric positive definite coefficient matrix, it should be substantially more computationally efficient than Palmer's method, which produces an asymmetric matrix. We conclude that the Galerkin PWL method is an attractive option for solving diffusion equations on unstructured grids. (authors)
International Nuclear Information System (INIS)
Bailey, Teresa S.; Adams, Marvin L.; Yang, Brian; Zika, Michael R.
2008-01-01
We develop a piecewise linear (PWL) Galerkin finite element spatial discretization for the multi-dimensional radiation diffusion equation. It uses recently introduced piecewise linear weight and basis functions in the finite element approximation and it can be applied on arbitrary polygonal (2D) or polyhedral (3D) grids. We first demonstrate some analytical properties of the PWL method and perform a simple mode analysis to compare the PWL method with Palmer's vertex-centered finite-volume method and with a bilinear continuous finite element method. We then show that this new PWL method gives solutions comparable to those from Palmer's. However, since the PWL method produces a symmetric positive-definite coefficient matrix, it should be substantially more computationally efficient than Palmer's method, which produces an asymmetric matrix. We conclude that the Galerkin PWL method is an attractive option for solving diffusion equations on unstructured grids
International Nuclear Information System (INIS)
Bailey, Teresa S.; Warsa, James S.; Chang, Jae H.; Adams, Marvin L.
2011-01-01
We present a new spatial discretization of the discrete-ordinates transport equation in two dimensional Cartesian (X-Y) geometry for arbitrary polygonal meshes. The discretization is a discontinuous finite element method (DFEM) that utilizes piecewise bi-linear (PWBL) basis functions, which are formally introduced in this paper. We also present a series of numerical results on quadrilateral and polygonal grids and compare these results to a variety of other spatial discretization that have been shown to be successful on these grid types. Finally, we note that the properties of the PWBL basis functions are such that the leading-order piecewise bi-linear discontinuous finite element (PWBLD) solution will satisfy a reasonably accurate diffusion discretization in the thick diffusion limit, making the PWBLD method a viable candidate for many different classes of transport problems. (author)
International Nuclear Information System (INIS)
Bailey, T.S.; Chang, J.H.; Warsa, J.S.; Adams, M.L.
2010-01-01
We present a new spatial discretization of the discrete-ordinates transport equation in two-dimensional Cartesian (X-Y) geometry for arbitrary polygonal meshes. The discretization is a discontinuous finite element method (DFEM) that utilizes piecewise bi-linear (PWBL) basis functions, which are formally introduced in this paper. We also present a series of numerical results on quadrilateral and polygonal grids and compare these results to a variety of other spatial discretizations that have been shown to be successful on these grid types. Finally, we note that the properties of the PWBL basis functions are such that the leading-order piecewise bi-linear discontinuous finite element (PWBLD) solution will satisfy a reasonably accurate diffusion discretization in the thick diffusion limit, making the PWBLD method a viable candidate for many different classes of transport problems.
DEFF Research Database (Denmark)
Gholami, M.; Cocquempot, V.; Schiøler, H.
2014-01-01
An active fault tolerant control (AFTC) method is proposed for discrete-time piecewise affine (PWA) systems. Only actuator faults are considered. The AFTC framework contains a supervisory scheme, which selects a suitable controller in a set of controllers such that the stability and an acceptable...... performance of the faulty system are held. The design of the supervisory scheme is not considered here. The set of controllers is composed of a normal controller for the fault-free case, an active fault detection and isolation controller for isolation and identification of the faults, and a set of passive...... fault tolerant controllers (PFTCs) modules designed to be robust against a set of actuator faults. In this research, the piecewise nonlinear model is approximated by a PWA system. The PFTCs are state feedback laws. Each one is robust against a fixed set of actuator faults and is able to track...
Periodic motions and grazing in a harmonically forced, piecewise, linear oscillator with impacts
International Nuclear Information System (INIS)
Luo, Albert C.J.; Chen Lidi
2005-01-01
In this paper, an idealized, piecewise linear system is presented to model the vibration of gear transmission systems. Periodic motions in a generalized, piecewise linear oscillator with perfectly plastic impacts are predicted analytically. The analytical predictions of periodic motion are based on the mapping structures, and the generic mappings based on the discontinuous boundaries are developed. This method for the analytical prediction of the periodic motions in non-smooth dynamic systems can give all possible periodic motions based on the adequate mapping structures. The stability and bifurcation conditions for specified periodic motions are obtained. The periodic motions and grazing motion are demonstrated. This model is applicable to prediction of periodic motion in nonlinear dynamics of gear transmission systems
Limit cycles via higher order perturbations for some piecewise differential systems
Buzzi, Claudio A.; Lima, Maurício Firmino Silva; Torregrosa, Joan
2018-05-01
A classical perturbation problem is the polynomial perturbation of the harmonic oscillator, (x‧ ,y‧) =(- y + εf(x , y , ε) , x + εg(x , y , ε)) . In this paper we study the limit cycles that bifurcate from the period annulus via piecewise polynomial perturbations in two zones separated by a straight line. We prove that, for polynomial perturbations of degree n , no more than Nn - 1 limit cycles appear up to a study of order N. We also show that this upper bound is reached for orders one and two. Moreover, we study this problem in some classes of piecewise Liénard differential systems providing better upper bounds for higher order perturbation in ε, showing also when they are reached. The Poincaré-Pontryagin-Melnikov theory is the main technique used to prove all the results.
A Revised Piecewise Linear Recursive Convolution FDTD Method for Magnetized Plasmas
International Nuclear Information System (INIS)
Liu Song; Zhong Shuangying; Liu Shaobin
2005-01-01
The piecewise linear recursive convolution (PLRC) finite-different time-domain (FDTD) method improves accuracy over the original recursive convolution (RC) FDTD approach and current density convolution (JEC) but retains their advantages in speed and efficiency. This paper describes a revised piecewise linear recursive convolution PLRC-FDTD formulation for magnetized plasma which incorporates both anisotropy and frequency dispersion at the same time, enabling the transient analysis of magnetized plasma media. The technique is illustrated by numerical simulations of the reflection and transmission coefficients through a magnetized plasma layer. The results show that the revised PLRC-FDTD method has improved the accuracy over the original RC FDTD method and JEC FDTD method
Low-complexity piecewise-affine virtual sensors: theory and design
Rubagotti, Matteo; Poggi, Tomaso; Oliveri, Alberto; Pascucci, Carlo Alberto; Bemporad, Alberto; Storace, Marco
2014-03-01
This paper is focused on the theoretical development and the hardware implementation of low-complexity piecewise-affine direct virtual sensors for the estimation of unmeasured variables of interest of nonlinear systems. The direct virtual sensor is designed directly from measured inputs and outputs of the system and does not require a dynamical model. The proposed approach allows one to design estimators which mitigate the effect of the so-called 'curse of dimensionality' of simplicial piecewise-affine functions, and can be therefore applied to relatively high-order systems, enjoying convergence and optimality properties. An automatic toolchain is also presented to generate the VHDL code describing the digital circuit implementing the virtual sensor, starting from the set of measured input and output data. The proposed methodology is applied to generate an FPGA implementation of the virtual sensor for the estimation of vehicle lateral velocity, using a hardware-in-the-loop setting.
Energy Technology Data Exchange (ETDEWEB)
Bailey, T S; Chang, J H; Warsa, J S; Adams, M L
2010-12-22
We present a new spatial discretization of the discrete-ordinates transport equation in two-dimensional Cartesian (X-Y) geometry for arbitrary polygonal meshes. The discretization is a discontinuous finite element method (DFEM) that utilizes piecewise bi-linear (PWBL) basis functions, which are formally introduced in this paper. We also present a series of numerical results on quadrilateral and polygonal grids and compare these results to a variety of other spatial discretizations that have been shown to be successful on these grid types. Finally, we note that the properties of the PWBL basis functions are such that the leading-order piecewise bi-linear discontinuous finite element (PWBLD) solution will satisfy a reasonably accurate diffusion discretization in the thick diffusion limit, making the PWBLD method a viable candidate for many different classes of transport problems.
A Lyapunov method for stability analysis of piecewise-affine systems over non-invariant domains
Rubagotti, Matteo; Zaccarian, Luca; Bemporad, Alberto
2016-05-01
This paper analyses stability of discrete-time piecewise-affine systems, defined on possibly non-invariant domains, taking into account the possible presence of multiple dynamics in each of the polytopic regions of the system. An algorithm based on linear programming is proposed, in order to prove exponential stability of the origin and to find a positively invariant estimate of its region of attraction. The results are based on the definition of a piecewise-affine Lyapunov function, which is in general discontinuous on the boundaries of the regions. The proposed method is proven to lead to feasible solutions in a broader range of cases as compared to a previously proposed approach. Two numerical examples are shown, among which a case where the proposed method is applied to a closed-loop system, to which model predictive control was applied without a-priori guarantee of stability.
Uniqueness in the inverse boundary value problem for piecewise homogeneous anisotropic elasticity
Cârstea, Cătălin I.; Honda, Naofumi; Nakamura, Gen
2016-01-01
Consider a three dimensional piecewise homogeneous anisotropic elastic medium $\\Omega$ which is a bounded domain consisting of a finite number of bounded subdomains $D_\\alpha$, with each $D_\\alpha$ a homogeneous elastic medium. One typical example is a finite element model with elements with curvilinear interfaces for an ansiotropic elastic medium. Assuming the $D_\\alpha$ are known and Lipschitz, we are concerned with the uniqueness in the inverse boundary value problem of identifying the ani...
Active Power Filter DC Bus Voltage Piecewise Reaching Law Variable Structure Control
Liu, Baolian; Ding, Zujun; Zhao, Huanyu; Jin, Defei
2014-01-01
The DC bus voltage stability control is one key technology to ensure that Active Power Filter (APF) operates stably. The external disturbances such as power grid and load fluctuation and the system parameters changing may affect the stability of APF DC bus voltage and the normal operation of APF. The mathematical model of DC bus voltage is established according to power balance principle and a DC bus voltage piecewise reaching law variable structure control algorithm is proposed to solve the ...
A New 3-D Piecewise-Linear System for Chaos Generation
Directory of Open Access Journals (Sweden)
Z. Elhadj
2007-06-01
Full Text Available We propose in this paper a new simple continuous-time piecewise-linear three dimensional system for chaos generation. Nonlinearity in this model is introduced by the characteristic function of the Chua's circuit given in [1]. Simulated results of some chaotic attractors are shown and justified numerically via computing the largest Lyapunov exponent. The possibility and the robustness of the circuitry realization is also given and discussed.
Mehdi, S. Bilal; Puig-Navarro, Javier; Choe, Ronald; Cichella, Venanzio; Hovakimyan, Naira; Chandarana, Meghan; Trujillo, Anna; Rothhaar, Paul M.; Tran, Loc; Neilan, James H.;
2016-01-01
Autonomous operation of UAS holds promise for greater productivity of atmospheric science missions. However, several challenges need to be overcome before such missions can be made autonomous. This paper presents a framework for safe autonomous operations of multiple vehicles, particularly suited for atmospheric science missions. The framework revolves around the use of piecewise Bezier curves for trajectory representation, which in conjunction with path-following and time-coordination algorithms, allows for safe coordinated operations of multiple vehicles.
A piecewise modeling approach for climate sensitivity studies: Tests with a shallow-water model
Shao, Aimei; Qiu, Chongjian; Niu, Guo-Yue
2015-10-01
In model-based climate sensitivity studies, model errors may grow during continuous long-term integrations in both the "reference" and "perturbed" states and hence the climate sensitivity (defined as the difference between the two states). To reduce the errors, we propose a piecewise modeling approach that splits the continuous long-term simulation into subintervals of sequential short-term simulations, and updates the modeled states through re-initialization at the end of each subinterval. In the re-initialization processes, this approach updates the reference state with analysis data and updates the perturbed states with the sum of analysis data and the difference between the perturbed and the reference states, thereby improving the credibility of the modeled climate sensitivity. We conducted a series of experiments with a shallow-water model to evaluate the advantages of the piecewise approach over the conventional continuous modeling approach. We then investigated the impacts of analysis data error and subinterval length used in the piecewise approach on the simulations of the reference and perturbed states as well as the resulting climate sensitivity. The experiments show that the piecewise approach reduces the errors produced by the conventional continuous modeling approach, more effectively when the analysis data error becomes smaller and the subinterval length is shorter. In addition, we employed a nudging assimilation technique to solve possible spin-up problems caused by re-initializations by using analysis data that contain inconsistent errors between mass and velocity. The nudging technique can effectively diminish the spin-up problem, resulting in a higher modeling skill.
Directory of Open Access Journals (Sweden)
Kuo-Shou Chiu
2010-08-01
Full Text Available In this paper we investigate the existence of the periodic solutions of a quasilinear differential equation with piecewise constant argument of generalized type. By using some fixed point theorems and some new analysis technique, sufficient conditions are obtained for the existence and uniqueness of periodic solutions of these systems. A new Gronwall type lemma is proved. Some examples concerning biological models as Lasota-Wazewska, Nicholson's blowflies and logistic models are treated.
Generating two simultaneously chaotic attractors with a switching piecewise-linear controller
International Nuclear Information System (INIS)
Zheng Zuohuan; Lue Jinhu; Chen Guanrong; Zhou Tianshou; Zhang Suochun
2004-01-01
It has been demonstrated that a piecewise-linear system can generate chaos under suitable conditions. This paper proposes a novel method for simultaneously creating two symmetrical chaotic attractor--an upper-attractor and a lower-attractor--in a 3D linear autonomous system. Basically dynamical behaviors of this new chaotic system are further investigated. Especially, the chaos formation mechanism is explored by analyzing the structure of fixed points and the system trajectories
Integrating piecewise linear representation and ensemble neural network for stock price prediction
Asaduzzaman, Md.; Shahjahan, Md.; Ahmed, Fatema Johera; Islam, Md. Monirul; Murase, Kazuyuki
2014-01-01
Stock Prices are considered to be very dynamic and susceptible to quick changes because of the underlying nature of the financial domain, and in part because of the interchange between known parameters and unknown factors. Of late, several researchers have used Piecewise Linear Representation (PLR) to predict the stock market pricing. However, some improvements are needed to avoid the appropriate threshold of the trading decision, choosing the input index as well as improving the overall perf...
Beretta, Elena; Micheletti, Stefano; Perotto, Simona; Santacesaria, Matteo
2018-01-01
In this paper, we develop a shape optimization-based algorithm for the electrical impedance tomography (EIT) problem of determining a piecewise constant conductivity on a polygonal partition from boundary measurements. The key tool is to use a distributed shape derivative of a suitable cost functional with respect to movements of the partition. Numerical simulations showing the robustness and accuracy of the method are presented for simulated test cases in two dimensions.
Energy Technology Data Exchange (ETDEWEB)
Graham, Emily B. [Biological Sciences Division, Pacific Northwest National Laboratory, Richland WA USA; Crump, Alex R. [Biological Sciences Division, Pacific Northwest National Laboratory, Richland WA USA; Resch, Charles T. [Geochemistry Department, Pacific Northwest National Laboratory, Richland WA USA; Fansler, Sarah [Biological Sciences Division, Pacific Northwest National Laboratory, Richland WA USA; Arntzen, Evan [Environmental Compliance and Emergency Preparation, Pacific Northwest National Laboratory, Richland WA USA; Kennedy, David W. [Biological Sciences Division, Pacific Northwest National Laboratory, Richland WA USA; Fredrickson, Jim K. [Biological Sciences Division, Pacific Northwest National Laboratory, Richland WA USA; Stegen, James C. [Biological Sciences Division, Pacific Northwest National Laboratory, Richland WA USA
2017-03-28
Subsurface zones of groundwater and surface water mixing (hyporheic zones) are regions of enhanced rates of biogeochemical cycling, yet ecological processes governing hyporheic microbiome composition and function through space and time remain unknown. We sampled attached and planktonic microbiomes in the Columbia River hyporheic zone across seasonal hydrologic change, and employed statistical null models to infer mechanisms generating temporal changes in microbiomes within three hydrologically-connected, physicochemically-distinct geographic zones (inland, nearshore, river). We reveal that microbiomes remain dissimilar through time across all zones and habitat types (attached vs. planktonic) and that deterministic assembly processes regulate microbiome composition in all data subsets. The consistent presence of heterotrophic taxa and members of the Planctomycetes-Verrucomicrobia-Chlamydiae (PVC) superphylum nonetheless suggests common selective pressures for physiologies represented in these groups. Further, co-occurrence networks were used to provide insight into taxa most affected by deterministic assembly processes. We identified network clusters to represent groups of organisms that correlated with seasonal and physicochemical change. Extended network analyses identified keystone taxa within each cluster that we propose are central in microbiome composition and function. Finally, the abundance of one network cluster of nearshore organisms exhibited a seasonal shift from heterotrophic to autotrophic metabolisms and correlated with microbial metabolism, possibly indicating an ecological role for these organisms as foundational species in driving biogeochemical reactions within the hyporheic zone. Taken together, our research demonstrates a predominant role for deterministic assembly across highly-connected environments and provides insight into niche dynamics associated with seasonal changes in hyporheic microbiome composition and metabolism.
A HYBRID TECHNIQUE FOR PAPR REDUCTION OF OFDM USING DHT PRECODING WITH PIECEWISE LINEAR COMPANDING
Directory of Open Access Journals (Sweden)
Thammana Ajay
2016-06-01
Full Text Available Orthogonal Frequency Division Multiplexing (OFDM is a fascinating approach for wireless communication applications which require huge amount of data rates. However, OFDM signal suffers from its large Peak-to-Average Power Ratio (PAPR, which results in significant distortion while passing through a nonlinear device, such as a transmitter high power amplifier (HPA. Due to this high PAPR, the complexity of HPA as well as DAC also increases. For the reduction of PAPR in OFDM many techniques are available. Among them companding is an attractive low complexity technique for the OFDM signal’s PAPR reduction. Recently, a piecewise linear companding technique is recommended aiming at minimizing companding distortion. In this paper, a collective piecewise linear companding approach with Discrete Hartley Transform (DHT method is expected to reduce peak-to-average of OFDM to a great extent. Simulation results shows that this new proposed method obtains significant PAPR reduction while maintaining improved performance in the Bit Error Rate (BER and Power Spectral Density (PSD compared to piecewise linear companding method.
Equivalence relations between deterministic and quantum mechanical systems
International Nuclear Information System (INIS)
Hooft, G.
1988-01-01
Several quantum mechanical models are shown to be equivalent to certain deterministic systems because a basis can be found in terms of which the wave function does not spread. This suggests that apparently indeterministic behavior typical for a quantum mechanical world can be the result of locally deterministic laws of physics. We show how certain deterministic systems allow the construction of a Hilbert space and a Hamiltonian so that at long distance scales they may appear to behave as quantum field theories, including interactions but as yet no mass term. These observations are suggested to be useful for building theories at the Planck scale
Stochastic Modeling and Deterministic Limit of Catalytic Surface Processes
DEFF Research Database (Denmark)
Starke, Jens; Reichert, Christian; Eiswirth, Markus
2007-01-01
Three levels of modeling, microscopic, mesoscopic and macroscopic are discussed for the CO oxidation on low-index platinum single crystal surfaces. The introduced models on the microscopic and mesoscopic level are stochastic while the model on the macroscopic level is deterministic. It can......, such that in contrast to the microscopic model the spatial resolution is reduced. The derivation of deterministic limit equations is in correspondence with the successful description of experiments under low-pressure conditions by deterministic reaction-diffusion equations while for intermediate pressures phenomena...
Operational State Complexity of Deterministic Unranked Tree Automata
Directory of Open Access Journals (Sweden)
Xiaoxue Piao
2010-08-01
Full Text Available We consider the state complexity of basic operations on tree languages recognized by deterministic unranked tree automata. For the operations of union and intersection the upper and lower bounds of both weakly and strongly deterministic tree automata are obtained. For tree concatenation we establish a tight upper bound that is of a different order than the known state complexity of concatenation of regular string languages. We show that (n+1 ( (m+12^n-2^(n-1 -1 vertical states are sufficient, and necessary in the worst case, to recognize the concatenation of tree languages recognized by (strongly or weakly deterministic automata with, respectively, m and n vertical states.
ZERODUR: deterministic approach for strength design
Hartmann, Peter
2012-12-01
There is an increasing request for zero expansion glass ceramic ZERODUR substrates being capable of enduring higher operational static loads or accelerations. The integrity of structures such as optical or mechanical elements for satellites surviving rocket launches, filigree lightweight mirrors, wobbling mirrors, and reticle and wafer stages in microlithography must be guaranteed with low failure probability. Their design requires statistically relevant strength data. The traditional approach using the statistical two-parameter Weibull distribution suffered from two problems. The data sets were too small to obtain distribution parameters with sufficient accuracy and also too small to decide on the validity of the model. This holds especially for the low failure probability levels that are required for reliable applications. Extrapolation to 0.1% failure probability and below led to design strengths so low that higher load applications seemed to be not feasible. New data have been collected with numbers per set large enough to enable tests on the applicability of the three-parameter Weibull distribution. This distribution revealed to provide much better fitting of the data. Moreover it delivers a lower threshold value, which means a minimum value for breakage stress, allowing of removing statistical uncertainty by introducing a deterministic method to calculate design strength. Considerations taken from the theory of fracture mechanics as have been proven to be reliable with proof test qualifications of delicate structures made from brittle materials enable including fatigue due to stress corrosion in a straight forward way. With the formulae derived, either lifetime can be calculated from given stress or allowable stress from minimum required lifetime. The data, distributions, and design strength calculations for several practically relevant surface conditions of ZERODUR are given. The values obtained are significantly higher than those resulting from the two
Yang, R; Zelyak, O; Fallone, B G; St-Aubin, J
2018-01-30
Angular discretization impacts nearly every aspect of a deterministic solution to the linear Boltzmann transport equation, especially in the presence of magnetic fields, as modeled by a streaming operator in angle. In this work a novel stabilization treatment of the magnetic field term is developed for an angular finite element discretization on the unit sphere, specifically involving piecewise partitioning of path integrals along curved element edges into uninterrupted segments of incoming and outgoing flux, with outgoing components updated iteratively. Correct order-of-accuracy for this angular framework is verified using the method of manufactured solutions for linear, quadratic, and cubic basis functions in angle. Higher order basis functions were found to reduce the error especially in strong magnetic fields and low density media. We combine an angular finite element mesh respecting octant boundaries on the unit sphere to spatial Cartesian voxel elements to guarantee an unambiguous transport sweep ordering in space. Accuracy for a dosimetrically challenging scenario involving bone and air in the presence of a 1.5 T parallel magnetic field is validated against the Monte Carlo package GEANT4. Accuracy and relative computational efficiency were investigated for various angular discretization parameters. 32 angular elements with quadratic basis functions yielded a reasonable compromise, with gamma passing rates of 99.96% (96.22%) for a 2%/2 mm (1%/1 mm) criterion. A rotational transformation of the spatial calculation geometry is performed to orient an arbitrary magnetic field vector to be along the z-axis, a requirement for a constant azimuthal angular sweep ordering. Working on the unit sphere, we apply the same rotational transformation to the angular domain to align its octants with the rotated Cartesian mesh. Simulating an oblique 1.5 T magnetic field against GEANT4 yielded gamma passing rates of 99.42% (95.45%) for a 2%/2 mm (1%/1 mm) criterion.
Yang, R.; Zelyak, O.; Fallone, B. G.; St-Aubin, J.
2018-02-01
Angular discretization impacts nearly every aspect of a deterministic solution to the linear Boltzmann transport equation, especially in the presence of magnetic fields, as modeled by a streaming operator in angle. In this work a novel stabilization treatment of the magnetic field term is developed for an angular finite element discretization on the unit sphere, specifically involving piecewise partitioning of path integrals along curved element edges into uninterrupted segments of incoming and outgoing flux, with outgoing components updated iteratively. Correct order-of-accuracy for this angular framework is verified using the method of manufactured solutions for linear, quadratic, and cubic basis functions in angle. Higher order basis functions were found to reduce the error especially in strong magnetic fields and low density media. We combine an angular finite element mesh respecting octant boundaries on the unit sphere to spatial Cartesian voxel elements to guarantee an unambiguous transport sweep ordering in space. Accuracy for a dosimetrically challenging scenario involving bone and air in the presence of a 1.5 T parallel magnetic field is validated against the Monte Carlo package GEANT4. Accuracy and relative computational efficiency were investigated for various angular discretization parameters. 32 angular elements with quadratic basis functions yielded a reasonable compromise, with gamma passing rates of 99.96% (96.22%) for a 2%/2 mm (1%/1 mm) criterion. A rotational transformation of the spatial calculation geometry is performed to orient an arbitrary magnetic field vector to be along the z-axis, a requirement for a constant azimuthal angular sweep ordering. Working on the unit sphere, we apply the same rotational transformation to the angular domain to align its octants with the rotated Cartesian mesh. Simulating an oblique 1.5 T magnetic field against GEANT4 yielded gamma passing rates of 99.42% (95.45%) for a 2%/2 mm (1%/1 mm) criterion.
Vague Sets Security Measure for Steganographic System Based on High-Order Markov Model
Directory of Open Access Journals (Sweden)
Chun-Juan Ouyang
2017-01-01
Full Text Available Security measure is of great importance in both steganography and steganalysis. Considering that statistical feature perturbations caused by steganography in an image are always nondeterministic and that an image is considered nonstationary, in this paper, the steganography is regarded as a fuzzy process. Here a steganographic security measure is proposed. This security measure evaluates the similarity between two vague sets of cover images and stego images in terms of n-order Markov chain to capture the interpixel correlation. The new security measure has proven to have the properties of boundedness, commutativity, and unity. Furthermore, the security measures of zero order, first order, second order, third order, and so forth are obtained by adjusting the order value of n-order Markov chain. Experimental results indicate that the larger n is, the better the measuring ability of the proposed security measure will be. The proposed security measure is more sensitive than other security measures defined under a deterministic distribution model, when the embedding is low. It is expected to provide a helpful guidance for designing secure steganographic algorithms or reliable steganalytic methods.
Comparison of the kinetics of different Markov models for ligand binding under varying conditions
International Nuclear Information System (INIS)
Martini, Johannes W. R.; Habeck, Michael
2015-01-01
We recently derived a Markov model for macromolecular ligand binding dynamics from few physical assumptions and showed that its stationary distribution is the grand canonical ensemble [J. W. R. Martini, M. Habeck, and M. Schlather, J. Math. Chem. 52, 665 (2014)]. The transition probabilities of the proposed Markov process define a particular Glauber dynamics and have some similarity to the Metropolis-Hastings algorithm. Here, we illustrate that this model is the stochastic analog of (pseudo) rate equations and the corresponding system of differential equations. Moreover, it can be viewed as a limiting case of general stochastic simulations of chemical kinetics. Thus, the model links stochastic and deterministic approaches as well as kinetics and equilibrium described by the grand canonical ensemble. We demonstrate that the family of transition matrices of our model, parameterized by temperature and ligand activity, generates ligand binding kinetics that respond to changes in these parameters in a qualitatively similar way as experimentally observed kinetics. In contrast, neither the Metropolis-Hastings algorithm nor the Glauber heat bath reflects changes in the external conditions correctly. Both converge rapidly to the stationary distribution, which is advantageous when the major interest is in the equilibrium state, but fail to describe the kinetics of ligand binding realistically. To simulate cellular processes that involve the reversible stochastic binding of multiple factors, our pseudo rate equation model should therefore be preferred to the Metropolis-Hastings algorithm and the Glauber heat bath, if the stationary distribution is not of only interest
Comparison of the kinetics of different Markov models for ligand binding under varying conditions
Energy Technology Data Exchange (ETDEWEB)
Martini, Johannes W. R., E-mail: jmartin2@gwdg.de [Max Planck Institute for Developmental Biology, Tübingen (Germany); Felix Bernstein Institute for Mathematical Statistics in the Biosciences, University of Göttingen, Göttingen (Germany); Habeck, Michael, E-mail: mhabeck@gwdg.de [Felix Bernstein Institute for Mathematical Statistics in the Biosciences, University of Göttingen, Göttingen (Germany); Max Planck Institute for Biophysical Chemistry, Göttingen (Germany)
2015-03-07
We recently derived a Markov model for macromolecular ligand binding dynamics from few physical assumptions and showed that its stationary distribution is the grand canonical ensemble [J. W. R. Martini, M. Habeck, and M. Schlather, J. Math. Chem. 52, 665 (2014)]. The transition probabilities of the proposed Markov process define a particular Glauber dynamics and have some similarity to the Metropolis-Hastings algorithm. Here, we illustrate that this model is the stochastic analog of (pseudo) rate equations and the corresponding system of differential equations. Moreover, it can be viewed as a limiting case of general stochastic simulations of chemical kinetics. Thus, the model links stochastic and deterministic approaches as well as kinetics and equilibrium described by the grand canonical ensemble. We demonstrate that the family of transition matrices of our model, parameterized by temperature and ligand activity, generates ligand binding kinetics that respond to changes in these parameters in a qualitatively similar way as experimentally observed kinetics. In contrast, neither the Metropolis-Hastings algorithm nor the Glauber heat bath reflects changes in the external conditions correctly. Both converge rapidly to the stationary distribution, which is advantageous when the major interest is in the equilibrium state, but fail to describe the kinetics of ligand binding realistically. To simulate cellular processes that involve the reversible stochastic binding of multiple factors, our pseudo rate equation model should therefore be preferred to the Metropolis-Hastings algorithm and the Glauber heat bath, if the stationary distribution is not of only interest.
Deterministic Echo State Networks Based Stock Price Forecasting
Directory of Open Access Journals (Sweden)
Jingpei Dan
2014-01-01
Full Text Available Echo state networks (ESNs, as efficient and powerful computational models for approximating nonlinear dynamical systems, have been successfully applied in financial time series forecasting. Reservoir constructions in standard ESNs rely on trials and errors in real applications due to a series of randomized model building stages. A novel form of ESN with deterministically constructed reservoir is competitive with standard ESN by minimal complexity and possibility of optimizations for ESN specifications. In this paper, forecasting performances of deterministic ESNs are investigated in stock price prediction applications. The experiment results on two benchmark datasets (Shanghai Composite Index and S&P500 demonstrate that deterministic ESNs outperform standard ESN in both accuracy and efficiency, which indicate the prospect of deterministic ESNs for financial prediction.
The cointegrated vector autoregressive model with general deterministic terms
DEFF Research Database (Denmark)
Johansen, Søren; Nielsen, Morten Ørregaard
2017-01-01
In the cointegrated vector autoregression (CVAR) literature, deterministic terms have until now been analyzed on a case-by-case, or as-needed basis. We give a comprehensive unified treatment of deterministic terms in the additive model X(t)=Z(t) Y(t), where Z(t) belongs to a large class...... of deterministic regressors and Y(t) is a zero-mean CVAR. We suggest an extended model that can be estimated by reduced rank regression and give a condition for when the additive and extended models are asymptotically equivalent, as well as an algorithm for deriving the additive model parameters from the extended...... model parameters. We derive asymptotic properties of the maximum likelihood estimators and discuss tests for rank and tests on the deterministic terms. In particular, we give conditions under which the estimators are asymptotically (mixed) Gaussian, such that associated tests are X 2 -distributed....
The cointegrated vector autoregressive model with general deterministic terms
DEFF Research Database (Denmark)
Johansen, Søren; Nielsen, Morten Ørregaard
In the cointegrated vector autoregression (CVAR) literature, deterministic terms have until now been analyzed on a case-by-case, or as-needed basis. We give a comprehensive unified treatment of deterministic terms in the additive model X(t)= Z(t) + Y(t), where Z(t) belongs to a large class...... of deterministic regressors and Y(t) is a zero-mean CVAR. We suggest an extended model that can be estimated by reduced rank regression and give a condition for when the additive and extended models are asymptotically equivalent, as well as an algorithm for deriving the additive model parameters from the extended...... model parameters. We derive asymptotic properties of the maximum likelihood estimators and discuss tests for rank and tests on the deterministic terms. In particular, we give conditions under which the estimators are asymptotically (mixed) Gaussian, such that associated tests are khi squared distributed....
Method to deterministically study photonic nanostructures in different experimental instruments
Husken, B.H.; Woldering, L.A.; Blum, Christian; Tjerkstra, R.W.; Vos, Willem L.
2009-01-01
We describe an experimental method to recover a single, deterministically fabricated nanostructure in various experimental instruments without the use of artificially fabricated markers, with the aim to study photonic structures. Therefore, a detailed map of the spatial surroundings of the
Non deterministic finite automata for power systems fault diagnostics
Directory of Open Access Journals (Sweden)
LINDEN, R.
2009-06-01
Full Text Available This paper introduces an application based on finite non-deterministic automata for power systems diagnosis. Automata for the simpler faults are presented and the proposed system is compared with an established expert system.
Transmission power control in WSNs : from deterministic to cognitive methods
Chincoli, M.; Liotta, A.; Gravina, R.; Palau, C.E.; Manso, M.; Liotta, A.; Fortino, G.
2018-01-01
Communications in Wireless Sensor Networks (WSNs) are affected by dynamic environments, variable signal fluctuations and interference. Thus, prompt actions are necessary to achieve dependable communications and meet Quality of Service (QoS) requirements. To this end, the deterministic algorithms
The probabilistic approach and the deterministic licensing procedure
International Nuclear Information System (INIS)
Fabian, H.; Feigel, A.; Gremm, O.
1984-01-01
If safety goals are given, the creativity of the engineers is necessary to transform the goals into actual safety measures. That is, safety goals are not sufficient for the derivation of a safety concept; the licensing process asks ''What does a safe plant look like.'' The answer connot be given by a probabilistic procedure, but need definite deterministic statements; the conclusion is, that the licensing process needs a deterministic approach. The probabilistic approach should be used in a complementary role in cases where deterministic criteria are not complete, not detailed enough or not consistent and additional arguments for decision making in connection with the adequacy of a specific measure are necessary. But also in these cases the probabilistic answer has to be transformed into a clear deterministic statement. (orig.)
Nuclear security assessment with Markov model approach
International Nuclear Information System (INIS)
Suzuki, Mitsutoshi; Terao, Norichika
2013-01-01
Nuclear security risk assessment with the Markov model based on random event is performed to explore evaluation methodology for physical protection in nuclear facilities. Because the security incidences are initiated by malicious and intentional acts, expert judgment and Bayes updating are used to estimate scenario and initiation likelihood, and it is assumed that the Markov model derived from stochastic process can be applied to incidence sequence. Both an unauthorized intrusion as Design Based Threat (DBT) and a stand-off attack as beyond-DBT are assumed to hypothetical facilities, and performance of physical protection and mitigation and minimization of consequence are investigated to develop the assessment methodology in a semi-quantitative manner. It is shown that cooperation between facility operator and security authority is important to respond to the beyond-DBT incidence. (author)
MARKOV CHAIN PORTFOLIO LIQUIDITY OPTIMIZATION MODEL
Directory of Open Access Journals (Sweden)
Eder Oliveira Abensur
2014-05-01
Full Text Available The international financial crisis of September 2008 and May 2010 showed the importance of liquidity as an attribute to be considered in portfolio decisions. This study proposes an optimization model based on available public data, using Markov chain and Genetic Algorithms concepts as it considers the classic duality of risk versus return and incorporating liquidity costs. The work intends to propose a multi-criterion non-linear optimization model using liquidity based on a Markov chain. The non-linear model was tested using Genetic Algorithms with twenty five Brazilian stocks from 2007 to 2009. The results suggest that this is an innovative development methodology and useful for developing an efficient and realistic financial portfolio, as it considers many attributes such as risk, return and liquidity.
An interlacing theorem for reversible Markov chains
International Nuclear Information System (INIS)
Grone, Robert; Salamon, Peter; Hoffmann, Karl Heinz
2008-01-01
Reversible Markov chains are an indispensable tool in the modeling of a vast class of physical, chemical, biological and statistical problems. Examples include the master equation descriptions of relaxing physical systems, stochastic optimization algorithms such as simulated annealing, chemical dynamics of protein folding and Markov chain Monte Carlo statistical estimation. Very often the large size of the state spaces requires the coarse graining or lumping of microstates into fewer mesoscopic states, and a question of utmost importance for the validity of the physical model is how the eigenvalues of the corresponding stochastic matrix change under this operation. In this paper we prove an interlacing theorem which gives explicit bounds on the eigenvalues of the lumped stochastic matrix. (fast track communication)
An interlacing theorem for reversible Markov chains
Energy Technology Data Exchange (ETDEWEB)
Grone, Robert; Salamon, Peter [Department of Mathematics and Statistics, San Diego State University, San Diego, CA 92182-7720 (United States); Hoffmann, Karl Heinz [Institut fuer Physik, Technische Universitaet Chemnitz, D-09107 Chemnitz (Germany)
2008-05-30
Reversible Markov chains are an indispensable tool in the modeling of a vast class of physical, chemical, biological and statistical problems. Examples include the master equation descriptions of relaxing physical systems, stochastic optimization algorithms such as simulated annealing, chemical dynamics of protein folding and Markov chain Monte Carlo statistical estimation. Very often the large size of the state spaces requires the coarse graining or lumping of microstates into fewer mesoscopic states, and a question of utmost importance for the validity of the physical model is how the eigenvalues of the corresponding stochastic matrix change under this operation. In this paper we prove an interlacing theorem which gives explicit bounds on the eigenvalues of the lumped stochastic matrix. (fast track communication)
Stochastic Dynamics through Hierarchically Embedded Markov Chains.
Vasconcelos, Vítor V; Santos, Fernando P; Santos, Francisco C; Pacheco, Jorge M
2017-02-03
Studying dynamical phenomena in finite populations often involves Markov processes of significant mathematical and/or computational complexity, which rapidly becomes prohibitive with increasing population size or an increasing number of individual configuration states. Here, we develop a framework that allows us to define a hierarchy of approximations to the stationary distribution of general systems that can be described as discrete Markov processes with time invariant transition probabilities and (possibly) a large number of states. This results in an efficient method for studying social and biological communities in the presence of stochastic effects-such as mutations in evolutionary dynamics and a random exploration of choices in social systems-including situations where the dynamics encompasses the existence of stable polymorphic configurations, thus overcoming the limitations of existing methods. The present formalism is shown to be general in scope, widely applicable, and of relevance to a variety of interdisciplinary problems.
Exact solution of the hidden Markov processes
Saakian, David B.
2017-11-01
We write a master equation for the distributions related to hidden Markov processes (HMPs) and solve it using a functional equation. Thus the solution of HMPs is mapped exactly to the solution of the functional equation. For a general case the latter can be solved only numerically. We derive an exact expression for the entropy of HMPs. Our expression for the entropy is an alternative to the ones given before by the solution of integral equations. The exact solution is possible because actually the model can be considered as a generalized random walk on a one-dimensional strip. While we give the solution for the two second-order matrices, our solution can be easily generalized for the L values of the Markov process and M values of observables: We should be able to solve a system of L functional equations in the space of dimension M -1 .
Local deterministic theory surviving the violation of Bell's inequalities
International Nuclear Information System (INIS)
Cormier-Delanoue, C.
1984-01-01
Bell's theorem which asserts that no deterministic theory with hidden variables can give the same predictions as quantum theory, is questioned. Such a deterministic theory is presented and carefully applied to real experiments performed on pairs of correlated photons, derived from the EPR thought experiment. The ensuing predictions violate Bell's inequalities just as quantum mechanics does, and it is further shown that this discrepancy originates in the very nature of radiations. Complete locality is therefore restored while separability remains more limited [fr
Deterministic operations research models and methods in linear optimization
Rader, David J
2013-01-01
Uniquely blends mathematical theory and algorithm design for understanding and modeling real-world problems Optimization modeling and algorithms are key components to problem-solving across various fields of research, from operations research and mathematics to computer science and engineering. Addressing the importance of the algorithm design process. Deterministic Operations Research focuses on the design of solution methods for both continuous and discrete linear optimization problems. The result is a clear-cut resource for understanding three cornerstones of deterministic operations resear
Handbook of Markov chain Monte Carlo
Brooks, Steve
2011-01-01
""Handbook of Markov Chain Monte Carlo"" brings together the major advances that have occurred in recent years while incorporating enough introductory material for new users of MCMC. Along with thorough coverage of the theoretical foundations and algorithmic and computational methodology, this comprehensive handbook includes substantial realistic case studies from a variety of disciplines. These case studies demonstrate the application of MCMC methods and serve as a series of templates for the construction, implementation, and choice of MCMC methodology.
Second Order Optimality in Markov Decision Chains
Czech Academy of Sciences Publication Activity Database
Sladký, Karel
2017-01-01
Roč. 53, č. 6 (2017), s. 1086-1099 ISSN 0023-5954 R&D Projects: GA ČR GA15-10331S Institutional support: RVO:67985556 Keywords : Markov decision chains * second order optimality * optimalilty conditions for transient, discounted and average models * policy and value iterations Subject RIV: BB - Applied Statistics, Operational Research OBOR OECD: Statistics and probability Impact factor: 0.379, year: 2016 http://library.utia.cas.cz/separaty/2017/E/sladky-0485146.pdf
Dynamical fluctuations for semi-Markov processes
Czech Academy of Sciences Publication Activity Database
Maes, C.; Netočný, Karel; Wynants, B.
2009-01-01
Roč. 42, č. 36 (2009), 365002/1-365002/21 ISSN 1751-8113 R&D Projects: GA ČR GC202/07/J051 Institutional research plan: CEZ:AV0Z10100520 Keywords : nonequilibrium fluctuations * semi-Markov processes Subject RIV: BM - Solid Matter Physics ; Magnetism Impact factor: 1.577, year: 2009 http://www.iop.org/EJ/abstract/1751-8121/42/36/365002
Analysis of a quantum Markov chain
International Nuclear Information System (INIS)
Marbeau, J.; Gudder, S.
1990-01-01
A quantum chain is analogous to a classical stationary Markov chain except that the probability measure is replaced by a complex amplitude measure and the transition probability matrix is replaced by a transition amplitude matrix. After considering the general situation, we study a particular example of a quantum chain whose transition amplitude matrix has the form of a Dirichlet matrix. Such matrices generate a discrete analog of the usual continuum Feynman amplitude. We then compute the probability distribution for these quantum chains
Modelling of cyclical stratigraphy using Markov chains
Energy Technology Data Exchange (ETDEWEB)
Kulatilake, P.H.S.W.
1987-07-01
State-of-the-art on modelling of cyclical stratigraphy using first-order Markov chains is reviewed. Shortcomings of the presently available procedures are identified. A procedure which eliminates all the identified shortcomings is presented. Required statistical tests to perform this modelling are given in detail. An example (the Oficina formation in eastern Venezuela) is given to illustrate the presented procedure. 12 refs., 3 tabs. 1 fig.
Markov Chains For Testing Redundant Software
White, Allan L.; Sjogren, Jon A.
1990-01-01
Preliminary design developed for validation experiment that addresses problems unique to assuring extremely high quality of multiple-version programs in process-control software. Approach takes into account inertia of controlled system in sense it takes more than one failure of control program to cause controlled system to fail. Verification procedure consists of two steps: experimentation (numerical simulation) and computation, with Markov model for each step.
Operational Markov Condition for Quantum Processes
Pollock, Felix A.; Rodríguez-Rosario, César; Frauenheim, Thomas; Paternostro, Mauro; Modi, Kavan
2018-01-01
We derive a necessary and sufficient condition for a quantum process to be Markovian which coincides with the classical one in the relevant limit. Our condition unifies all previously known definitions for quantum Markov processes by accounting for all potentially detectable memory effects. We then derive a family of measures of non-Markovianity with clear operational interpretations, such as the size of the memory required to simulate a process or the experimental falsifiability of a Markovian hypothesis.
Markov and semi-Markov switching linear mixed models used to identify forest tree growth components.
Chaubert-Pereira, Florence; Guédon, Yann; Lavergne, Christian; Trottier, Catherine
2010-09-01
Tree growth is assumed to be mainly the result of three components: (i) an endogenous component assumed to be structured as a succession of roughly stationary phases separated by marked change points that are asynchronous among individuals, (ii) a time-varying environmental component assumed to take the form of synchronous fluctuations among individuals, and (iii) an individual component corresponding mainly to the local environment of each tree. To identify and characterize these three components, we propose to use semi-Markov switching linear mixed models, i.e., models that combine linear mixed models in a semi-Markovian manner. The underlying semi-Markov chain represents the succession of growth phases and their lengths (endogenous component) whereas the linear mixed models attached to each state of the underlying semi-Markov chain represent-in the corresponding growth phase-both the influence of time-varying climatic covariates (environmental component) as fixed effects, and interindividual heterogeneity (individual component) as random effects. In this article, we address the estimation of Markov and semi-Markov switching linear mixed models in a general framework. We propose a Monte Carlo expectation-maximization like algorithm whose iterations decompose into three steps: (i) sampling of state sequences given random effects, (ii) prediction of random effects given state sequences, and (iii) maximization. The proposed statistical modeling approach is illustrated by the analysis of successive annual shoots along Corsican pine trunks influenced by climatic covariates. © 2009, The International Biometric Society.
Temperature scaling method for Markov chains.
Crosby, Lonnie D; Windus, Theresa L
2009-01-22
The use of ab initio potentials in Monte Carlo simulations aimed at investigating the nucleation kinetics of water clusters is complicated by the computational expense of the potential energy determinations. Furthermore, the common desire to investigate the temperature dependence of kinetic properties leads to an urgent need to reduce the expense of performing simulations at many different temperatures. A method is detailed that allows a Markov chain (obtained via Monte Carlo) at one temperature to be scaled to other temperatures of interest without the need to perform additional large simulations. This Markov chain temperature-scaling (TeS) can be generally applied to simulations geared for numerous applications. This paper shows the quality of results which can be obtained by TeS and the possible quantities which may be extracted from scaled Markov chains. Results are obtained for a 1-D analytical potential for which the exact solutions are known. Also, this method is applied to water clusters consisting of between 2 and 5 monomers, using Dynamical Nucleation Theory to determine the evaporation rate constant for monomer loss. Although ab initio potentials are not utilized in this paper, the benefit of this method is made apparent by using the Dang-Chang polarizable classical potential for water to obtain statistical properties at various temperatures.
Deterministic chaos in the pitting phenomena of passivable alloys
International Nuclear Information System (INIS)
Hoerle, Stephane
1998-01-01
It was shown that electrochemical noise recorded in stable pitting conditions exhibits deterministic (even chaotic) features. The occurrence of deterministic behaviors depend on the material/solution severity. Thus, electrolyte composition ([Cl - ]/[NO 3 - ] ratio, pH), passive film thickness or alloy composition can change the deterministic features. Only one pit is sufficient to observe deterministic behaviors. The electrochemical noise signals are non-stationary, which is a hint of a change with time in the pit behavior (propagation speed or mean). Modifications of electrolyte composition reveals transitions between random and deterministic behaviors. Spontaneous transitions between deterministic behaviors of different features (bifurcation) are also evidenced. Such bifurcations enlighten various routes to chaos. The routes to chaos and the features of chaotic signals allow to suggest the modeling (continuous and discontinuous models are proposed) of the electrochemical mechanisms inside a pit, that describe quite well the experimental behaviors and the effect of the various parameters. The analysis of the chaotic behaviors of a pit leads to a better understanding of propagation mechanisms and give tools for pit monitoring. (author) [fr
Stencil method: a Markov model for transport in porous media
Delgoshaie, A. H.; Tchelepi, H.; Jenny, P.
2016-12-01
In porous media the transport of fluid is dominated by flow-field heterogeneity resulting from the underlying transmissibility field. Since the transmissibility is highly uncertain, many realizations of a geological model are used to describe the statistics of the transport phenomena in a Monte Carlo framework. One possible way to avoid the high computational cost of physics-based Monte Carlo simulations is to model the velocity field as a Markov process and use Markov Chain Monte Carlo. In previous works multiple Markov models for discrete velocity processes have been proposed. These models can be divided into two general classes of Markov models in time and Markov models in space. Both of these choices have been shown to be effective to some extent. However some studies have suggested that the Markov property cannot be confirmed for a temporal Markov process; Therefore there is not a consensus about the validity and value of Markov models in time. Moreover, previous spacial Markov models have only been used for modeling transport on structured networks and can not be readily applied to model transport in unstructured networks. In this work we propose a novel approach for constructing a Markov model in time (stencil method) for a discrete velocity process. The results form the stencil method are compared to previously proposed spacial Markov models for structured networks. The stencil method is also applied to unstructured networks and can successfully describe the dispersion of particles in this setting. Our conclusion is that both temporal Markov models and spacial Markov models for discrete velocity processes can be valid for a range of model parameters. Moreover, we show that the stencil model can be more efficient in many practical settings and is suited to model dispersion both on structured and unstructured networks.
Efficiency of transport in periodic potentials: dichotomous noise contra deterministic force
Spiechowicz, J.; Łuczka, J.; Machura, L.
2016-05-01
We study the transport of an inertial Brownian particle moving in a symmetric and periodic one-dimensional potential, and subjected to both a symmetric, unbiased external harmonic force as well as biased dichotomic noise η (t) also known as a random telegraph signal or a two state continuous-time Markov process. In doing so, we concentrate on the previously reported regime (Spiechowicz et al 2014 Phys. Rev. E 90 032104) for which non-negative biased noise η (t) in the form of generalized white Poissonian noise can induce anomalous transport processes similar to those generated by a deterministic constant force F= but significantly more effective than F, i.e. the particle moves much faster, the velocity fluctuations are noticeably reduced and the transport efficiency is enhanced several times. Here, we confirm this result for the case of dichotomous fluctuations which, in contrast to white Poissonian noise, can assume positive as well as negative values and examine the role of thermal noise in the observed phenomenon. We focus our attention on the impact of bidirectionality of dichotomous fluctuations and reveal that the effect of nonequilibrium noise enhanced efficiency is still detectable. This result may explain transport phenomena occurring in strongly fluctuating environments of both physical and biological origin. Our predictions can be corroborated experimentally by use of a setup that consists of a resistively and capacitively shunted Josephson junction.
Deterministic flows of order-parameters in stochastic processes of quantum Monte Carlo method
International Nuclear Information System (INIS)
Inoue, Jun-ichi
2010-01-01
In terms of the stochastic process of quantum-mechanical version of Markov chain Monte Carlo method (the MCMC), we analytically derive macroscopically deterministic flow equations of order parameters such as spontaneous magnetization in infinite-range (d(= ∞)-dimensional) quantum spin systems. By means of the Trotter decomposition, we consider the transition probability of Glauber-type dynamics of microscopic states for the corresponding (d + 1)-dimensional classical system. Under the static approximation, differential equations with respect to macroscopic order parameters are explicitly obtained from the master equation that describes the microscopic-law. In the steady state, we show that the equations are identical to the saddle point equations for the equilibrium state of the same system. The equation for the dynamical Ising model is recovered in the classical limit. We also check the validity of the static approximation by making use of computer simulations for finite size systems and discuss several possible extensions of our approach to disordered spin systems for statistical-mechanical informatics. Especially, we shall use our procedure to evaluate the decoding process of Bayesian image restoration. With the assistance of the concept of dynamical replica theory (the DRT), we derive the zero-temperature flow equation of image restoration measure showing some 'non-monotonic' behaviour in its time evolution.
Constructing Dynamic Event Trees from Markov Models
International Nuclear Information System (INIS)
Paolo Bucci; Jason Kirschenbaum; Tunc Aldemir; Curtis Smith; Ted Wood
2006-01-01
In the probabilistic risk assessment (PRA) of process plants, Markov models can be used to model accurately the complex dynamic interactions between plant physical process variables (e.g., temperature, pressure, etc.) and the instrumentation and control system that monitors and manages the process. One limitation of this approach that has prevented its use in nuclear power plant PRAs is the difficulty of integrating the results of a Markov analysis into an existing PRA. In this paper, we explore a new approach to the generation of failure scenarios and their compilation into dynamic event trees from a Markov model of the system. These event trees can be integrated into an existing PRA using software tools such as SAPHIRE. To implement our approach, we first construct a discrete-time Markov chain modeling the system of interest by: (a) partitioning the process variable state space into magnitude intervals (cells), (b) using analytical equations or a system simulator to determine the transition probabilities between the cells through the cell-to-cell mapping technique, and, (c) using given failure/repair data for all the components of interest. The Markov transition matrix thus generated can be thought of as a process model describing the stochastic dynamic behavior of the finite-state system. We can therefore search the state space starting from a set of initial states to explore all possible paths to failure (scenarios) with associated probabilities. We can also construct event trees of arbitrary depth by tracing paths from a chosen initiating event and recording the following events while keeping track of the probabilities associated with each branch in the tree. As an example of our approach, we use the simple level control system often used as benchmark in the literature with one process variable (liquid level in a tank), and three control units: a drain unit and two supply units. Each unit includes a separate level sensor to observe the liquid level in the tank
Deterministic effects of the ionizing radiation
International Nuclear Information System (INIS)
Raslawski, Elsa C.
2001-01-01
Full text: The deterministic effect is the somatic damage that appears when radiation dose is superior to the minimum value or 'threshold dose'. Over this threshold dose, the frequency and seriousness of the damage increases with the amount given. Sixteen percent of patients younger than 15 years of age with the diagnosis of cancer have the possibility of a cure. The consequences of cancer treatment in children are very serious, as they are physically and emotionally developing. The seriousness of the delayed effects of radiation therapy depends on three factors: a)- The treatment ( dose of radiation, schedule of treatment, time of treatment, beam energy, treatment volume, distribution of the dose, simultaneous chemotherapy, etc.); b)- The patient (state of development, patient predisposition, inherent sensitivity of tissue, the present of other alterations, etc.); c)- The tumor (degree of extension or infiltration, mechanical effects, etc.). The effect of radiation on normal tissue is related to cellular activity and the maturity of the tissue irradiated. Children have a mosaic of tissues in different stages of maturity at different moments in time. On the other hand, each tissue has a different pattern of development, so that sequelae are different in different irradiated tissues of the same patient. We should keep in mind that all the tissues are affected in some degree. Bone tissue evidences damage with growth delay and degree of calcification. Damage is small at 10 Gy; between 10 and 20 Gy growth arrest is partial, whereas at doses larger than 20 Gy growth arrest is complete. The central nervous system is the most affected because the radiation injuries produce demyelination with or without focal or diffuse areas of necrosis in the white matter causing character alterations, lower IQ and functional level, neuro cognitive impairment,etc. The skin is also affected, showing different degrees of erythema such as ulceration and necrosis, different degrees of
Markov chains and semi-Markov models in time-to-event analysis.
Abner, Erin L; Charnigo, Richard J; Kryscio, Richard J
2013-10-25
A variety of statistical methods are available to investigators for analysis of time-to-event data, often referred to as survival analysis. Kaplan-Meier estimation and Cox proportional hazards regression are commonly employed tools but are not appropriate for all studies, particularly in the presence of competing risks and when multiple or recurrent outcomes are of interest. Markov chain models can accommodate censored data, competing risks (informative censoring), multiple outcomes, recurrent outcomes, frailty, and non-constant survival probabilities. Markov chain models, though often overlooked by investigators in time-to-event analysis, have long been used in clinical studies and have widespread application in other fields.
Derivation of Markov processes that violate detailed balance
Lee, Julian
2018-03-01
Time-reversal symmetry of the microscopic laws dictates that the equilibrium distribution of a stochastic process must obey the condition of detailed balance. However, cyclic Markov processes that do not admit equilibrium distributions with detailed balance are often used to model systems driven out of equilibrium by external agents. I show that for a Markov model without detailed balance, an extended Markov model can be constructed, which explicitly includes the degrees of freedom for the driving agent and satisfies the detailed balance condition. The original cyclic Markov model for the driven system is then recovered as an approximation at early times by summing over the degrees of freedom for the driving agent. I also show that the widely accepted expression for the entropy production in a cyclic Markov model is actually a time derivative of an entropy component in the extended model. Further, I present an analytic expression for the entropy component that is hidden in the cyclic Markov model.
English, Thomas
2005-01-01
A standard tool of reliability analysis used at NASA-JSC is the event tree. An event tree is simply a probability tree, with the probabilities determining the next step through the tree specified at each node. The nodal probabilities are determined by a reliability study of the physical system at work for a particular node. The reliability study performed at a node is typically referred to as a fault tree analysis, with the potential of a fault tree existing.for each node on the event tree. When examining an event tree it is obvious why the event tree/fault tree approach has been adopted. Typical event trees are quite complex in nature, and the event tree/fault tree approach provides a systematic and organized approach to reliability analysis. The purpose of this study was two fold. Firstly, we wanted to explore the possibility that a semi-Markov process can create dependencies between sojourn times (the times it takes to transition from one state to the next) that can decrease the uncertainty when estimating time to failures. Using a generalized semi-Markov model, we studied a four element reliability model and were able to demonstrate such sojourn time dependencies. Secondly, we wanted to study the use of semi-Markov processes to introduce a time variable into the event tree diagrams that are commonly developed in PRA (Probabilistic Risk Assessment) analyses. Event tree end states which change with time are more representative of failure scenarios than are the usual static probability-derived end states.
On the Convergence of Piecewise Linear Strategic Interaction Dynamics on Networks
Gharesifard, Bahman
2015-09-11
We prove that the piecewise linear best-response dynamical systems of strategic interactions are asymptotically convergent to their set of equilibria on any weighted undirected graph. We study various features of these dynamical systems, including the uniqueness and abundance properties of the set of equilibria and the emergence of unstable equilibria. We also introduce the novel notions of social equivalence and social dominance on directed graphs, and demonstrate some of their interesting implications, including their correspondence to consensus and chromatic number of partite graphs. Examples illustrate our results.
Dynamics and bifurcations of a three-dimensional piecewise-linear integrable map
International Nuclear Information System (INIS)
Tuwankotta, J M; Quispel, G R W; Tamizhmani, K M
2004-01-01
In this paper, we consider a four-parameter family of piecewise-linear ordinary difference equations (OΔEs) in R 3 . This system is obtained as a limit of another family of three-dimensional integrable systems of OΔEs. We prove that the limiting procedure sends integrals of the original system to integrals of the limiting system. We derive some results for the solutions such as boundedness of solutions and the existence of periodic solutions. We describe all topologically different shapes of the integral manifolds and present all possible scenarios of transitions as we vary the natural parameters in the system, i.e. the values of the integrals
Directory of Open Access Journals (Sweden)
Xuefeng Wei
2016-12-01
Full Text Available This article concerns the wave interaction problem for a strictly hyperbolic system of conservation laws whose Riemann solutions involve delta shock waves. To cover all situations, the global solutions are constructed when the initial data are taken as three piecewise constant states. It is shown that the Riemann solutions are stable with respect to a specific small perturbation of the Riemann initial data. In addition, some interesting nonlinear phenomena are captured during the process of constructing the solutions, such as the generation and decomposition of delta shock waves.
International Nuclear Information System (INIS)
Huang Zhenkun; Wang Xinghua; Xia Yonghui
2009-01-01
In this paper, we investigate qualitative behavior of nonlinear differential equations with piecewise constant argument (PCA). A topological approach of Wazewski-type which gives sufficient conditions to guarantee that the graph of at least one solution stays in a given domain is formulated. Moreover, our results are also suitable for a class of general system of discrete equations. By using a regular polyfacial set, we apply our developed topological approach to cellular neural networks (CNNs) with PCA. Some new results are attained to reveal dynamic behavior of CNNs with PCA and discrete-time CNNs. Finally, an illustrative example of CNNs with PCA shows usefulness and effectiveness of our results.
On the existence of tunneling bounce solutions in piecewise linear potentials
International Nuclear Information System (INIS)
Dutta, Koushik; Hector, Cecelie; Konstandin, Thomas; Vaudrevange, Pascal M.; Westphal, Alexander
2012-02-01
Coleman tunneling in a general scalar potential with two non-degenerate minima is known to have an approximation in terms of a piecewise linear triangular-shaped potential with sharp 'kinks' at the place of the local minima. This approximate potential has a regime where the existence of the bounce solution needs the scalar field to 'wait' for some amount of Euclidean time at one of the 'kinks'. We discuss under which circumstances the correct bounce action can be consistently obtained as the limiting case of a regular scalar potential where 'kinks' are resolved as locally smooth 'cap' regions. (orig.)
A Markov Process Inspired Cellular Automata Model of Road Traffic
Wang, Fa; Li, Li; Hu, Jianming; Ji, Yan; Yao, Danya; Zhang, Yi; Jin, Xuexiang; Su, Yuelong; Wei, Zheng
2008-01-01
To provide a more accurate description of the driving behaviors in vehicle queues, a namely Markov-Gap cellular automata model is proposed in this paper. It views the variation of the gap between two consequent vehicles as a Markov process whose stationary distribution corresponds to the observed distribution of practical gaps. The multiformity of this Markov process provides the model enough flexibility to describe various driving behaviors. Two examples are given to show how to specialize i...
A New GMRES(m Method for Markov Chains
Directory of Open Access Journals (Sweden)
Bing-Yuan Pu
2013-01-01
Full Text Available This paper presents a class of new accelerated restarted GMRES method for calculating the stationary probability vector of an irreducible Markov chain. We focus on the mechanism of this new hybrid method by showing how to periodically combine the GMRES and vector extrapolation method into a much efficient one for improving the convergence rate in Markov chain problems. Numerical experiments are carried out to demonstrate the efficiency of our new algorithm on several typical Markov chain problems.
Context Tree Estimation in Variable Length Hidden Markov Models
Dumont, Thierry
2011-01-01
We address the issue of context tree estimation in variable length hidden Markov models. We propose an estimator of the context tree of the hidden Markov process which needs no prior upper bound on the depth of the context tree. We prove that the estimator is strongly consistent. This uses information-theoretic mixture inequalities in the spirit of Finesso and Lorenzo(Consistent estimation of the order for Markov and hidden Markov chains(1990)) and E.Gassiat and S.Boucheron (Optimal error exp...
Deteksi Fraud Menggunakan Metode Model Markov Tersembunyi Pada Proses Bisnis
Directory of Open Access Journals (Sweden)
Andrean Hutama Koosasi
2017-03-01
Full Text Available Model Markov Tersembunyi merupakan sebuah metode statistik berdasarkan Model Markov sederhana yang memodelkan sistem serta membaginya dalam 2 (dua state, state tersembunyi dan state observasi. Dalam pengerjaan tugas akhir ini, penulis mengusulkan penggunaan metode Model Markov Tersembunyi untuk menemukan fraud didalam sebuah pelaksanaan proses bisnis. Dengan penggunaan metode Model Markov Tersembunyi ini, maka pengamatan terhadap elemen penyusun sebuah kasus/kejadian, yakni beberapa aktivitas, akan diperoleh sebuah nilai peluang, yang sekaligus memberikan prediksi terhadap kasus/kejadian tersebut, sebuah fraud atau tidak. Hasil ekpserimen ini menunjukkan bahwa metode yang diusulkan mampu memberikan prediksi akhir dengan evaluasi TPR sebesar 87,5% dan TNR sebesar 99,4%.
The dialectical thinking about deterministic and probabilistic safety analysis
International Nuclear Information System (INIS)
Qian Yongbai; Tong Jiejuan; Zhang Zuoyi; He Xuhong
2005-01-01
There are two methods in designing and analysing the safety performance of a nuclear power plant, the traditional deterministic method and the probabilistic method. To date, the design of nuclear power plant is based on the deterministic method. It has been proved in practice that the deterministic method is effective on current nuclear power plant. However, the probabilistic method (Probabilistic Safety Assessment - PSA) considers a much wider range of faults, takes an integrated look at the plant as a whole, and uses realistic criteria for the performance of the systems and constructions of the plant. PSA can be seen, in principle, to provide a broader and realistic perspective on safety issues than the deterministic approaches. In this paper, the historical origins and development trend of above two methods are reviewed and summarized in brief. Based on the discussion of two application cases - one is the changes to specific design provisions of the general design criteria (GDC) and the other is the risk-informed categorization of structure, system and component, it can be concluded that the deterministic method and probabilistic method are dialectical and unified, and that they are being merged into each other gradually, and being used in coordination. (authors)
An Analysis of Piecewise-Linear and Convex Value Functions for Active Perception POMDPs
Satsangi, Y.; Whiteson, S.; Spaan, M.T.J.
2015-01-01
In active perception tasks, an agent aims to select actions that reduce its uncertainty about a hidden state. While partially observable Markov decision processes (POMDPs) are a natural model for such problems, reward functions that directly penalize uncertainty in the agent's belief can remove the
Markov Chain Analysis of Musical Dice Games
Volchenkov, D.; Dawin, J. R.
2012-07-01
A system for using dice to compose music randomly is known as the musical dice game. The discrete time MIDI models of 804 pieces of classical music written by 29 composers have been encoded into the transition matrices and studied by Markov chains. Contrary to human languages, entropy dominates over redundancy, in the musical dice games based on the compositions of classical music. The maximum complexity is achieved on the blocks consisting of just a few notes (8 notes, for the musical dice games generated over Bach's compositions). First passage times to notes can be used to resolve tonality and feature a composer.
Pruning Boltzmann networks and hidden Markov models
DEFF Research Database (Denmark)
Pedersen, Morten With; Stork, D.
1996-01-01
We present sensitivity-based pruning algorithms for general Boltzmann networks. Central to our methods is the efficient calculation of a second-order approximation to the true weight saliencies in a cross-entropy error. Building upon previous work which shows a formal correspondence between linear...... Boltzmann chains and hidden Markov models (HMMs), we argue that our method can be applied to HMMs as well. We illustrate pruning on Boltzmann zippers, which are equivalent to two HMMs with cross-connection links. We verify that our second-order approximation preserves the rank ordering of weight saliencies...
Decoding LDPC Convolutional Codes on Markov Channels
Directory of Open Access Journals (Sweden)
Kashyap Manohar
2008-01-01
Full Text Available Abstract This paper describes a pipelined iterative technique for joint decoding and channel state estimation of LDPC convolutional codes over Markov channels. Example designs are presented for the Gilbert-Elliott discrete channel model. We also compare the performance and complexity of our algorithm against joint decoding and state estimation of conventional LDPC block codes. Complexity analysis reveals that our pipelined algorithm reduces the number of operations per time step compared to LDPC block codes, at the expense of increased memory and latency. This tradeoff is favorable for low-power applications.
Decoding LDPC Convolutional Codes on Markov Channels
Directory of Open Access Journals (Sweden)
Chris Winstead
2008-04-01
Full Text Available This paper describes a pipelined iterative technique for joint decoding and channel state estimation of LDPC convolutional codes over Markov channels. Example designs are presented for the Gilbert-Elliott discrete channel model. We also compare the performance and complexity of our algorithm against joint decoding and state estimation of conventional LDPC block codes. Complexity analysis reveals that our pipelined algorithm reduces the number of operations per time step compared to LDPC block codes, at the expense of increased memory and latency. This tradeoff is favorable for low-power applications.
Evolving the structure of hidden Markov Models
DEFF Research Database (Denmark)
won, K. J.; Prugel-Bennett, A.; Krogh, A.
2006-01-01
A genetic algorithm (GA) is proposed for finding the structure of hidden Markov Models (HMMs) used for biological sequence analysis. The GA is designed to preserve biologically meaningful building blocks. The search through the space of HMM structures is combined with optimization of the emission...... and transition probabilities using the classic Baum-Welch algorithm. The system is tested on the problem of finding the promoter and coding region of C. jejuni. The resulting HMM has a superior discrimination ability to a handcrafted model that has been published in the literature....
Honest Importance Sampling with Multiple Markov Chains.
Tan, Aixin; Doss, Hani; Hobert, James P
2015-01-01
Importance sampling is a classical Monte Carlo technique in which a random sample from one probability density, π 1 , is used to estimate an expectation with respect to another, π . The importance sampling estimator is strongly consistent and, as long as two simple moment conditions are satisfied, it obeys a central limit theorem (CLT). Moreover, there is a simple consistent estimator for the asymptotic variance in the CLT, which makes for routine computation of standard errors. Importance sampling can also be used in the Markov chain Monte Carlo (MCMC) context. Indeed, if the random sample from π 1 is replaced by a Harris ergodic Markov chain with invariant density π 1 , then the resulting estimator remains strongly consistent. There is a price to be paid however, as the computation of standard errors becomes more complicated. First, the two simple moment conditions that guarantee a CLT in the iid case are not enough in the MCMC context. Second, even when a CLT does hold, the asymptotic variance has a complex form and is difficult to estimate consistently. In this paper, we explain how to use regenerative simulation to overcome these problems. Actually, we consider a more general set up, where we assume that Markov chain samples from several probability densities, π 1 , …, π k , are available. We construct multiple-chain importance sampling estimators for which we obtain a CLT based on regeneration. We show that if the Markov chains converge to their respective target distributions at a geometric rate, then under moment conditions similar to those required in the iid case, the MCMC-based importance sampling estimator obeys a CLT. Furthermore, because the CLT is based on a regenerative process, there is a simple consistent estimator of the asymptotic variance. We illustrate the method with two applications in Bayesian sensitivity analysis. The first concerns one-way random effects models under different priors. The second involves Bayesian variable
ANALYSING ACCEPTANCE SAMPLING PLANS BY MARKOV CHAINS
Directory of Open Access Journals (Sweden)
Mohammad Mirabi
2012-01-01
Full Text Available
ENGLISH ABSTRACT: In this research, a Markov analysis of acceptance sampling plans in a single stage and in two stages is proposed, based on the quality of the items inspected. In a stage of this policy, if the number of defective items in a sample of inspected items is more than the upper threshold, the batch is rejected. However, the batch is accepted if the number of defective items is less than the lower threshold. Nonetheless, when the number of defective items falls between the upper and lower thresholds, the decision-making process continues to inspect the items and collect further samples. The primary objective is to determine the optimal values of the upper and lower thresholds using a Markov process to minimise the total cost associated with a batch acceptance policy. A solution method is presented, along with a numerical demonstration of the application of the proposed methodology.
AFRIKAANSE OPSOMMING: In hierdie navorsing word ’n Markov-ontleding gedoen van aannamemonsternemingsplanne wat plaasvind in ’n enkele stap of in twee stappe na gelang van die kwaliteit van die items wat geïnspekteer word. Indien die eerste monster toon dat die aantal defektiewe items ’n boonste grens oorskry, word die lot afgekeur. Indien die eerste monster toon dat die aantal defektiewe items minder is as ’n onderste grens, word die lot aanvaar. Indien die eerste monster toon dat die aantal defektiewe items in die gebied tussen die boonste en onderste grense lê, word die besluitnemingsproses voortgesit en verdere monsters word geneem. Die primêre doel is om die optimale waardes van die booonste en onderste grense te bepaal deur gebruik te maak van ’n Markov-proses sodat die totale koste verbonde aan die proses geminimiseer kan word. ’n Oplossing word daarna voorgehou tesame met ’n numeriese voorbeeld van die toepassing van die voorgestelde oplossing.
Vulnerability of networks of interacting Markov chains.
Kocarev, L; Zlatanov, N; Trajanov, D
2010-05-13
The concept of vulnerability is introduced for a model of random, dynamical interactions on networks. In this model, known as the influence model, the nodes are arranged in an arbitrary network, while the evolution of the status at a node is according to an internal Markov chain, but with transition probabilities that depend not only on the current status of that node but also on the statuses of the neighbouring nodes. Vulnerability is treated analytically and numerically for several networks with different topological structures, as well as for two real networks--the network of infrastructures and the EU power grid--identifying the most vulnerable nodes of these networks.
Genetic Algorithms Principles Towards Hidden Markov Model
Directory of Open Access Journals (Sweden)
Nabil M. Hewahi
2011-10-01
Full Text Available In this paper we propose a general approach based on Genetic Algorithms (GAs to evolve Hidden Markov Models (HMM. The problem appears when experts assign probability values for HMM, they use only some limited inputs. The assigned probability values might not be accurate to serve in other cases related to the same domain. We introduce an approach based on GAs to find
out the suitable probability values for the HMM to be mostly correct in more cases than what have been used to assign the probability values.
Energy Technology Data Exchange (ETDEWEB)
Calloo, A.; Vidal, J.F.; Le Tellier, R.; Rimpault, G., E-mail: ansar.calloo@cea.fr, E-mail: jean-francois.vidal@cea.fr, E-mail: romain.le-tellier@cea.fr, E-mail: gerald.rimpault@cea.fr [CEA, DEN, DER/SPRC/LEPh, Saint-Paul-lez-Durance (France)
2011-07-01
This paper deals with the solving of the multigroup integro-differential form of the transport equation for fine energy group structure. In that case, multigroup transfer cross sections display strongly peaked shape for light scatterers and the current Legendre polynomial expansion is not well-suited to represent them. Furthermore, even if considering an exact scattering cross sections representation, the scattering source in the discrete ordinates method (also known as the Sn method) being calculated by sampling the angular flux at given directions, may be wrongly computed due to lack of angular support for the angular flux. Hence, following the work of Gerts and Matthews, an angular finite volume solver has been developed for 2D Cartesian geometries. It integrates the multigroup transport equation over discrete volume elements obtained by meshing the unit sphere with a product grid over the polar and azimuthal coordinates and by considering the integrated flux per solid angle element. The convergence of this method has been compared to the S{sub n} method for a highly anisotropic benchmark. Besides, piecewise-average scattering cross sections have been produced for non-bound Hydrogen atoms using a free gas model for thermal neutrons. LWR lattice calculations comparing Legendre representations of the Hydrogen scattering multigroup cross section at various orders and piecewise-average cross sections for this same atom are carried out (while keeping a Legendre representation for all other isotopes). (author)
Directory of Open Access Journals (Sweden)
Wei Wei
2013-01-01
Full Text Available Since Wireless sensor networks (WSNs are dramatically being arranged in mission-critical applications,it changes into necessary that we consider application requirements in Internet of Things. We try to use WSNs to assist information query and navigation within a practical parking spaces environment. Integrated with high-performance OFDM by piece-wise polynomial approximation, we present a new method that is based on a diffusion equation and a position equation to accomplish the navigation process conveniently and efficiently. From the point of view of theoretical analysis, our jobs hold the lower constraint condition and several inappropriate navigation can be amended. Information diffusion and potential field are introduced to reach the goal of accurate navigation and gradient descent method is applied in the algorithm. Formula derivations and simulations manifest that the method facilitates the solution of typical sensor network configuration information navigation. Concurrently, we also treat channel estimation and ICI mitigation for very high mobility OFDM systems, and the communication is between a BS and mobile target at a terrible scenario. The scheme proposed here combines the piece-wise polynomial expansion to approximate timevariations of multipath channels. Two near symbols are applied to estimate the first-and second-order parameters. So as to improve the estimation accuracy and mitigate the ICI caused by pilot-aided estimation, the multipath channel parameters were reestimated in timedomain employing the decided OFDM symbol. Simulation results show that this method would improve system performance in a complex environment.
Three-Dimensional Piecewise-Continuous Class-Shape Transformation of Wings
Olson, Erik D.
2015-01-01
Class-Shape Transformation (CST) is a popular method for creating analytical representations of the surface coordinates of various components of aerospace vehicles. A wide variety of two- and three-dimensional shapes can be represented analytically using only a modest number of parameters, and the surface representation is smooth and continuous to as fine a degree as desired. This paper expands upon the original two-dimensional representation of airfoils to develop a generalized three-dimensional CST parametrization scheme that is suitable for a wider range of aircraft wings than previous formulations, including wings with significant non-planar shapes such as blended winglets and box wings. The method uses individual functions for the spanwise variation of airfoil shape, chord, thickness, twist, and reference axis coordinates to build up the complete wing shape. An alternative formulation parameterizes the slopes of the reference axis coordinates in order to relate the spanwise variation to the tangents of the sweep and dihedral angles. Also discussed are methods for fitting existing wing surface coordinates, including the use of piecewise equations to handle discontinuities, and mathematical formulations of geometric continuity constraints. A subsonic transport wing model is used as an example problem to illustrate the application of the methodology and to quantify the effects of piecewise representation and curvature constraints.
A piecewise-integration method for simulating the influence of external forcing on climate
Institute of Scientific and Technical Information of China (English)
Zhifu Zhang; Chongjian Qiu; Chenghai Wang
2008-01-01
Climate drift occurs in most general circulation models (GCMs) as a result of incomplete physical and numerical representation of the complex climate system,which may cause large uncertainty in sensitivity experiments evaluating climate response to changes in external forcing.To solve this problem,we propose a piecewise-integration method to reduce the systematic error in climate sensitivity studies.The observations are firstly assimilated into a numerical model by using the dynamic relaxation technique to relax to the current state of atmosphere,and then the assimilated fields are continuously used to reinitialize the simulation to reduce the error of climate simulation.When the numerical model is integrated with changed external forcing,the results can be split into two parts,background and perturbation fields,and the background is the state before the external forcing is changed.The piecewise-integration method is used to continuously reinitialize the model with the assimilated field,instead of the background.Therefore,the simulation error of the model with the external forcing can be reduced.In this way,the accuracy of climate sensitivity experiments is greatly improved.Tests with a simple low-order spectral model show that this approach can significantly reduce the uncertainty of climate sensitivity experiments.
Forced vibration of nonlinear system with symmetrical piecewise-linear characteristics
International Nuclear Information System (INIS)
Watanabe, Takeshi
1983-01-01
It is fairly difficult to treat exactly the analysis of a vibrating system including some play because it is accompanied by a strong nonlinear phenomenon of collision. The author attempted the theoretical analysis by the exact solution using series solution and the approximate solution, treating the forced vibration of a system having some play as the forced vibration of a continuous system with nonlinear boundary condition or the colliding vibration of a continuum. In this report, the problem of such system with play is treated as a nonlinear system having the symmetrical, piecewise linear characteristics of one degree of freedom. That is, it is considered that at the time of collision due to play, the collided body causes the deformation accompanied by triangular hystersis elastically and plastically, and the spring characteristics of restitution force change piecewise by the collision. The exact solution using series solution and the approximate solution are performed, and the effectiveness of these theoretical solutions is confirmed by comparing with the solution using an analog computer. The relation between the accuracy of two analysis methods and nonlinear parameters is shown by the examples of numerical calculation. (Kako, I.)
International Nuclear Information System (INIS)
Calloo, A.; Vidal, J.F.; Le Tellier, R.; Rimpault, G.
2011-01-01
This paper deals with the solving of the multigroup integro-differential form of the transport equation for fine energy group structure. In that case, multigroup transfer cross sections display strongly peaked shape for light scatterers and the current Legendre polynomial expansion is not well-suited to represent them. Furthermore, even if considering an exact scattering cross sections representation, the scattering source in the discrete ordinates method (also known as the Sn method) being calculated by sampling the angular flux at given directions, may be wrongly computed due to lack of angular support for the angular flux. Hence, following the work of Gerts and Matthews, an angular finite volume solver has been developed for 2D Cartesian geometries. It integrates the multigroup transport equation over discrete volume elements obtained by meshing the unit sphere with a product grid over the polar and azimuthal coordinates and by considering the integrated flux per solid angle element. The convergence of this method has been compared to the S_n method for a highly anisotropic benchmark. Besides, piecewise-average scattering cross sections have been produced for non-bound Hydrogen atoms using a free gas model for thermal neutrons. LWR lattice calculations comparing Legendre representations of the Hydrogen scattering multigroup cross section at various orders and piecewise-average cross sections for this same atom are carried out (while keeping a Legendre representation for all other isotopes). (author)
Piecewise nonlinear dynamic characteristics study of the control rod drive mechanism
International Nuclear Information System (INIS)
Shen Xiaoyao; Wang Feng
2011-01-01
Piecewise nonlinear dynamics of the control rod mechanism (CRDM), one of the critical components in PWR nuclear power plants, are studied for its lifting process in this paper. Firstly, equations of the electric circuit and the magnetic circuit are set up. Then based on the dynamic lifting process analysis of CRDM, its motion procedure is divided into three stages, and the coupled magnetic-electric-mechanical equation for each stage is derived. By combining the analytical solution method and the numerical simulation method, the piecewise nonlinear governing equations are solved. Finally, parameters which can illustrate the dynamic characteristics of CRDM, such as the magnetic force, the coil current, the armature displacement, the armature velocity and the acceleration are obtained and corresponding curves with the time are drawn and analyzed. The analysis results are confirmed by the test which proves the validity of our method. Work in this paper can be used for design and analysis as well as the site fault diagnosis of CRDM. (author)
Learning to Act: Qualitative Learning of Deterministic Action Models
DEFF Research Database (Denmark)
Bolander, Thomas; Gierasimczuk, Nina
2017-01-01
In this article we study learnability of fully observable, universally applicable action models of dynamic epistemic logic. We introduce a framework for actions seen as sets of transitions between propositional states and we relate them to their dynamic epistemic logic representations as action...... in the limit (inconclusive convergence to the right action model). We show that deterministic actions are finitely identifiable, while arbitrary (non-deterministic) actions require more learning power—they are identifiable in the limit. We then move on to a particular learning method, i.e. learning via update......, which proceeds via restriction of a space of events within a learning-specific action model. We show how this method can be adapted to learn conditional and unconditional deterministic action models. We propose update learning mechanisms for the afore mentioned classes of actions and analyse...
Inherent Conservatism in Deterministic Quasi-Static Structural Analysis
Verderaime, V.
1997-01-01
The cause of the long-suspected excessive conservatism in the prevailing structural deterministic safety factor has been identified as an inherent violation of the error propagation laws when reducing statistical data to deterministic values and then combining them algebraically through successive structural computational processes. These errors are restricted to the applied stress computations, and because mean and variations of the tolerance limit format are added, the errors are positive, serially cumulative, and excessively conservative. Reliability methods circumvent these errors and provide more efficient and uniform safe structures. The document is a tutorial on the deficiencies and nature of the current safety factor and of its improvement and transition to absolute reliability.
Towards deterministic optical quantum computation with coherently driven atomic ensembles
International Nuclear Information System (INIS)
Petrosyan, David
2005-01-01
Scalable and efficient quantum computation with photonic qubits requires (i) deterministic sources of single photons, (ii) giant nonlinearities capable of entangling pairs of photons, and (iii) reliable single-photon detectors. In addition, an optical quantum computer would need a robust reversible photon storage device. Here we discuss several related techniques, based on the coherent manipulation of atomic ensembles in the regime of electromagnetically induced transparency, that are capable of implementing all of the above prerequisites for deterministic optical quantum computation with single photons
Deterministic and efficient quantum cryptography based on Bell's theorem
International Nuclear Information System (INIS)
Chen Zengbing; Pan Jianwei; Zhang Qiang; Bao Xiaohui; Schmiedmayer, Joerg
2006-01-01
We propose a double-entanglement-based quantum cryptography protocol that is both efficient and deterministic. The proposal uses photon pairs with entanglement both in polarization and in time degrees of freedom; each measurement in which both of the two communicating parties register a photon can establish one and only one perfect correlation, and thus deterministically create a key bit. Eavesdropping can be detected by violation of local realism. A variation of the protocol shows a higher security, similar to the six-state protocol, under individual attacks. Our scheme allows a robust implementation under the current technology
Epitope discovery with phylogenetic hidden Markov models.
LENUS (Irish Health Repository)
Lacerda, Miguel
2010-05-01
Existing methods for the prediction of immunologically active T-cell epitopes are based on the amino acid sequence or structure of pathogen proteins. Additional information regarding the locations of epitopes may be acquired by considering the evolution of viruses in hosts with different immune backgrounds. In particular, immune-dependent evolutionary patterns at sites within or near T-cell epitopes can be used to enhance epitope identification. We have developed a mutation-selection model of T-cell epitope evolution that allows the human leukocyte antigen (HLA) genotype of the host to influence the evolutionary process. This is one of the first examples of the incorporation of environmental parameters into a phylogenetic model and has many other potential applications where the selection pressures exerted on an organism can be related directly to environmental factors. We combine this novel evolutionary model with a hidden Markov model to identify contiguous amino acid positions that appear to evolve under immune pressure in the presence of specific host immune alleles and that therefore represent potential epitopes. This phylogenetic hidden Markov model provides a rigorous probabilistic framework that can be combined with sequence or structural information to improve epitope prediction. As a demonstration, we apply the model to a data set of HIV-1 protein-coding sequences and host HLA genotypes.
Neyman, Markov processes and survival analysis.
Yang, Grace
2013-07-01
J. Neyman used stochastic processes extensively in his applied work. One example is the Fix and Neyman (F-N) competing risks model (1951) that uses finite homogeneous Markov processes to analyse clinical trials with breast cancer patients. We revisit the F-N model, and compare it with the Kaplan-Meier (K-M) formulation for right censored data. The comparison offers a way to generalize the K-M formulation to include risks of recovery and relapses in the calculation of a patient's survival probability. The generalization is to extend the F-N model to a nonhomogeneous Markov process. Closed-form solutions of the survival probability are available in special cases of the nonhomogeneous processes, like the popular multiple decrement model (including the K-M model) and Chiang's staging model, but these models do not consider recovery and relapses while the F-N model does. An analysis of sero-epidemiology current status data with recurrent events is illustrated. Fix and Neyman used Neyman's RBAN (regular best asymptotic normal) estimates for the risks, and provided a numerical example showing the importance of considering both the survival probability and the length of time of a patient living a normal life in the evaluation of clinical trials. The said extension would result in a complicated model and it is unlikely to find analytical closed-form solutions for survival analysis. With ever increasing computing power, numerical methods offer a viable way of investigating the problem.
Unmixing hyperspectral images using Markov random fields
International Nuclear Information System (INIS)
Eches, Olivier; Dobigeon, Nicolas; Tourneret, Jean-Yves
2011-01-01
This paper proposes a new spectral unmixing strategy based on the normal compositional model that exploits the spatial correlations between the image pixels. The pure materials (referred to as endmembers) contained in the image are assumed to be available (they can be obtained by using an appropriate endmember extraction algorithm), while the corresponding fractions (referred to as abundances) are estimated by the proposed algorithm. Due to physical constraints, the abundances have to satisfy positivity and sum-to-one constraints. The image is divided into homogeneous distinct regions having the same statistical properties for the abundance coefficients. The spatial dependencies within each class are modeled thanks to Potts-Markov random fields. Within a Bayesian framework, prior distributions for the abundances and the associated hyperparameters are introduced. A reparametrization of the abundance coefficients is proposed to handle the physical constraints (positivity and sum-to-one) inherent to hyperspectral imagery. The parameters (abundances), hyperparameters (abundance mean and variance for each class) and the classification map indicating the classes of all pixels in the image are inferred from the resulting joint posterior distribution. To overcome the complexity of the joint posterior distribution, Markov chain Monte Carlo methods are used to generate samples asymptotically distributed according to the joint posterior of interest. Simulations conducted on synthetic and real data are presented to illustrate the performance of the proposed algorithm.
Markov transitions and the propagation of chaos
International Nuclear Information System (INIS)
Gottlieb, A.
1998-01-01
The propagation of chaos is a central concept of kinetic theory that serves to relate the equations of Boltzmann and Vlasov to the dynamics of many-particle systems. Propagation of chaos means that molecular chaos, i.e., the stochastic independence of two random particles in a many-particle system, persists in time, as the number of particles tends to infinity. We establish a necessary and sufficient condition for a family of general n-particle Markov processes to propagate chaos. This condition is expressed in terms of the Markov transition functions associated to the n-particle processes, and it amounts to saying that chaos of random initial states propagates if it propagates for pure initial states. Our proof of this result relies on the weak convergence approach to the study of chaos due to Sztitman and Tanaka. We assume that the space in which the particles live is homomorphic to a complete and separable metric space so that we may invoke Prohorov's theorem in our proof. We also show that, if the particles can be in only finitely many states, then molecular chaos implies that the specific entropies in the n-particle distributions converge to the entropy of the limiting single-particle distribution
Asymptotic evolution of quantum Markov chains
Energy Technology Data Exchange (ETDEWEB)
Novotny, Jaroslav [FNSPE, CTU in Prague, 115 19 Praha 1 - Stare Mesto (Czech Republic); Alber, Gernot [Institut fuer Angewandte Physik, Technische Universitaet Darmstadt, D-64289 Darmstadt (Germany)
2012-07-01
The iterated quantum operations, so called quantum Markov chains, play an important role in various branches of physics. They constitute basis for many discrete models capable to explore fundamental physical problems, such as the approach to thermal equilibrium, or the asymptotic dynamics of macroscopic physical systems far from thermal equilibrium. On the other hand, in the more applied area of quantum technology they also describe general characteristic properties of quantum networks or they can describe different quantum protocols in the presence of decoherence. A particularly, an interesting aspect of these quantum Markov chains is their asymptotic dynamics and its characteristic features. We demonstrate there is always a vector subspace (typically low-dimensional) of so-called attractors on which the resulting superoperator governing the iterative time evolution of quantum states can be diagonalized and in which the asymptotic quantum dynamics takes place. As the main result interesting algebraic relations are presented for this set of attractors which allow to specify their dual basis and to determine them in a convenient way. Based on this general theory we show some generalizations concerning the theory of fixed points or asymptotic evolution of random quantum operations.
Monotone measures of ergodicity for Markov chains
Directory of Open Access Journals (Sweden)
J. Keilson
1998-01-01
Full Text Available The following paper, first written in 1974, was never published other than as part of an internal research series. Its lack of publication is unrelated to the merits of the paper and the paper is of current importance by virtue of its relation to the relaxation time. A systematic discussion is provided of the approach of a finite Markov chain to ergodicity by proving the monotonicity of an important set of norms, each measures of egodicity, whether or not time reversibility is present. The paper is of particular interest because the discussion of the relaxation time of a finite Markov chain [2] has only been clean for time reversible chains, a small subset of the chains of interest. This restriction is not present here. Indeed, a new relaxation time quoted quantifies the relaxation time for all finite ergodic chains (cf. the discussion of Q1(t below Equation (1.7]. This relaxation time was developed by Keilson with A. Roy in his thesis [6], yet to be published.
Approximating Markov Chains: What and why
International Nuclear Information System (INIS)
Pincus, S.
1996-01-01
Much of the current study of dynamical systems is focused on geometry (e.g., chaos and bifurcations) and ergodic theory. Yet dynamical systems were originally motivated by an attempt to open-quote open-quote solve,close-quote close-quote or at least understand, a discrete-time analogue of differential equations. As such, numerical, analytical solution techniques for dynamical systems would seem desirable. We discuss an approach that provides such techniques, the approximation of dynamical systems by suitable finite state Markov Chains. Steady state distributions for these Markov Chains, a straightforward calculation, will converge to the true dynamical system steady state distribution, with appropriate limit theorems indicated. Thus (i) approximation by a computable, linear map holds the promise of vastly faster steady state solutions for nonlinear, multidimensional differential equations; (ii) the solution procedure is unaffected by the presence or absence of a probability density function for the attractor, entirely skirting singularity, fractal/multifractal, and renormalization considerations. The theoretical machinery underpinning this development also implies that under very general conditions, steady state measures are weakly continuous with control parameter evolution. This means that even though a system may change periodicity, or become chaotic in its limiting behavior, such statistical parameters as the mean, standard deviation, and tail probabilities change continuously, not abruptly with system evolution. copyright 1996 American Institute of Physics
Pathwise duals of monotone and additive Markov processes
Czech Academy of Sciences Publication Activity Database
Sturm, A.; Swart, Jan M.
-, - (2018) ISSN 0894-9840 R&D Projects: GA ČR GAP201/12/2613 Institutional support: RVO:67985556 Keywords : pathwise duality * monotone Markov process * additive Markov process * interacting particle system Subject RIV: BA - General Mathematics Impact factor: 0.854, year: 2016 http://library.utia.cas.cz/separaty/2016/SI/swart-0465436.pdf
An introduction to hidden Markov models for biological sequences
DEFF Research Database (Denmark)
Krogh, Anders Stærmose
1998-01-01
A non-matematical tutorial on hidden Markov models (HMMs) plus a description of one of the applications of HMMs: gene finding.......A non-matematical tutorial on hidden Markov models (HMMs) plus a description of one of the applications of HMMs: gene finding....
Asymptotics for Estimating Equations in Hidden Markov Models
DEFF Research Database (Denmark)
Hansen, Jørgen Vinsløv; Jensen, Jens Ledet
Results on asymptotic normality for the maximum likelihood estimate in hidden Markov models are extended in two directions. The stationarity assumption is relaxed, which allows for a covariate process influencing the hidden Markov process. Furthermore a class of estimating equations is considered...
Efficient Incorporation of Markov Random Fields in Change Detection
DEFF Research Database (Denmark)
Aanæs, Henrik; Nielsen, Allan Aasbjerg; Carstensen, Jens Michael
2009-01-01
of noise, implying that the pixel-wise classifier is also noisy. There is thus a need for incorporating local homogeneity constraints into such a change detection framework. For this modelling task Markov Random Fields are suitable. Markov Random Fields have, however, previously been plagued by lack...
Markov trace on the Yokonuma-Hecke algebra
International Nuclear Information System (INIS)
Juyumaya, J.
2002-11-01
The objective of this note is to prove that there exists a Markov trace on the Yokonuma-Hecke algebra. A motivation to define a Markov trace is to get polynomial invariants for knots in the sense of Jones construction. (author)
Compositionality for Markov reward chains with fast and silent transitions
Markovski, J.; Sokolova, A.; Trcka, N.; Vink, de E.P.
2009-01-01
A parallel composition is defined for Markov reward chains with stochastic discontinuity, and with fast and silent transitions. In this setting, compositionality with respect to the relevant aggregation preorders is established. For Markov reward chains with fast transitions the preorders are
Model Checking Markov Reward Models with Impulse Rewards
Cloth, Lucia; Katoen, Joost-Pieter; Khattri, Maneesh; Pulungan, Reza; Bondavalli, Andrea; Haverkort, Boudewijn; Tang, Dong
This paper considers model checking of Markov reward models (MRMs), continuous-time Markov chains with state rewards as well as impulse rewards. The reward extension of the logic CSL (Continuous Stochastic Logic) is interpreted over such MRMs, and two numerical algorithms are provided to check the
Recursive smoothers for hidden discrete-time Markov chains
Directory of Open Access Journals (Sweden)
Lakhdar Aggoun
2005-01-01
Full Text Available We consider a discrete-time Markov chain observed through another Markov chain. The proposed model extends models discussed by Elliott et al. (1995. We propose improved recursive formulae to update smoothed estimates of processes related to the model. These recursive estimates are used to update the parameter of the model via the expectation maximization (EM algorithm.
First hitting probabilities for semi markov chains and estimation
DEFF Research Database (Denmark)
Georgiadis, Stylianos
2017-01-01
We first consider a stochastic system described by an absorbing semi-Markov chain with finite state space and we introduce the absorption probability to a class of recurrent states. Afterwards, we study the first hitting probability to a subset of states for an irreducible semi-Markov chain...
ANALYTIC WORD RECOGNITION WITHOUT SEGMENTATION BASED ON MARKOV RANDOM FIELDS
Coisy, C.; Belaid, A.
2004-01-01
In this paper, a method for analytic handwritten word recognition based on causal Markov random fields is described. The words models are HMMs where each state corresponds to a letter; each letter is modelled by a NSHPHMM (Markov field). Global models are build dynamically, and used for recognition
A Markov decision model for optimising economic production lot size ...
African Journals Online (AJOL)
Adopting such a Markov decision process approach, the states of a Markov chain represent possible states of demand. The decision of whether or not to produce additional inventory units is made using dynamic programming. This approach demonstrates the existence of an optimal state-dependent EPL size, and produces ...
Portfolio allocation under the vendor managed inventory: A Markov ...
African Journals Online (AJOL)
Portfolio allocation under the vendor managed inventory: A Markov decision process. ... Journal of Applied Sciences and Environmental Management ... This study provides a review of Markov decision processes and investigates its suitability for solutions to portfolio allocation problems under vendor managed inventory in ...
Logics and Models for Stochastic Analysis Beyond Markov Chains
DEFF Research Database (Denmark)
Zeng, Kebin
, because of the generality of ME distributions, we have to leave the world of Markov chains. To support ME distributions with multiple exits, we introduce a multi-exits ME distribution together with a process algebra MEME to express the systems having the semantics as Markov renewal processes with ME...
Introduction to the numerical solutions of Markov chains
Stewart, Williams J
1994-01-01
A cornerstone of applied probability, Markov chains can be used to help model how plants grow, chemicals react, and atoms diffuse - and applications are increasingly being found in such areas as engineering, computer science, economics, and education. To apply the techniques to real problems, however, it is necessary to understand how Markov chains can be solved numerically. In this book, the first to offer a systematic and detailed treatment of the numerical solution of Markov chains, William Stewart provides scientists on many levels with the power to put this theory to use in the actual world, where it has applications in areas as diverse as engineering, economics, and education. His efforts make for essential reading in a rapidly growing field. Here, Stewart explores all aspects of numerically computing solutions of Markov chains, especially when the state is huge. He provides extensive background to both discrete-time and continuous-time Markov chains and examines many different numerical computing metho...
Deterministic Predictions of Vessel Responses Based on Past Measurements
DEFF Research Database (Denmark)
Nielsen, Ulrik Dam; Jensen, Jørgen Juncher
2017-01-01
The paper deals with a prediction procedure from which global wave-induced responses can be deterministically predicted a short time, 10-50 s, ahead of current time. The procedure relies on the autocorrelation function and takes into account prior measurements only; i.e. knowledge about wave...
About the Possibility of Creation of a Deterministic Unified Mechanics
International Nuclear Information System (INIS)
Khomyakov, G.K.
2005-01-01
The possibility of creation of a unified deterministic scheme of classical and quantum mechanics, allowing to preserve their achievements is discussed. It is shown that the canonical system of ordinary differential equation of Hamilton classical mechanics can be added with the vector system of ordinary differential equation for the variables of equations. The interpretational problems of quantum mechanics are considered
Deterministic Versus Stochastic Interpretation of Continuously Monitored Sewer Systems
DEFF Research Database (Denmark)
Harremoës, Poul; Carstensen, Niels Jacob
1994-01-01
An analysis has been made of the uncertainty of input parameters to deterministic models for sewer systems. The analysis reveals a very significant uncertainty, which can be decreased, but not eliminated and has to be considered for engineering application. Stochastic models have a potential for ...
The State of Deterministic Thinking among Mothers of Autistic Children
Directory of Open Access Journals (Sweden)
Mehrnoush Esbati
2011-10-01
Full Text Available Objectives: The purpose of the present study was to investigate the effectiveness of cognitive-behavior education on decreasing deterministic thinking in mothers of children with autism spectrum disorders. Methods: Participants were 24 mothers of autistic children who were referred to counseling centers of Tehran and their children’s disorder had been diagnosed at least by a psychiatrist and a counselor. They were randomly selected and assigned into control and experimental groups. Measurement tool was Deterministic Thinking Questionnaire and both groups answered it before and after education and the answers were analyzed by analysis of covariance. Results: The results indicated that cognitive-behavior education decreased deterministic thinking among mothers of autistic children, it decreased four sub scale of deterministic thinking: interaction with others, absolute thinking, prediction of future, and negative events (P<0.05 as well. Discussions: By learning cognitive and behavioral techniques, parents of children with autism can reach higher level of psychological well-being and it is likely that these cognitive-behavioral skills would have a positive impact on general life satisfaction of mothers of children with autism.
Deterministic multimode photonic device for quantum-information processing
DEFF Research Database (Denmark)
Nielsen, Anne E. B.; Mølmer, Klaus
2010-01-01
We propose the implementation of a light source that can deterministically generate a rich variety of multimode quantum states. The desired states are encoded in the collective population of different ground hyperfine states of an atomic ensemble and converted to multimode photonic states by exci...
Deterministic Chaos - Complex Chance out of Simple Necessity ...
Indian Academy of Sciences (India)
This is a very lucid and lively book on deterministic chaos. Chaos is very common in nature. However, the understanding and realisation of its potential applications is very recent. Thus this book is a timely addition to the subject. There are several books on chaos and several more are being added every day. In spite of this ...
Nonlinear deterministic structures and the randomness of protein sequences
Huang Yan Zhao
2003-01-01
To clarify the randomness of protein sequences, we make a detailed analysis of a set of typical protein sequences representing each structural classes by using nonlinear prediction method. No deterministic structures are found in these protein sequences and this implies that they behave as random sequences. We also give an explanation to the controversial results obtained in previous investigations.
Line and lattice networks under deterministic interference models
Goseling, Jasper; Gastpar, Michael; Weber, Jos H.
Capacity bounds are compared for four different deterministic models of wireless networks, representing four different ways of handling broadcast and superposition in the physical layer. In particular, the transport capacity under a multiple unicast traffic pattern is studied for a 1-D network of
Comparison of deterministic and Monte Carlo methods in shielding design.
Oliveira, A D; Oliveira, C
2005-01-01
In shielding calculation, deterministic methods have some advantages and also some disadvantages relative to other kind of codes, such as Monte Carlo. The main advantage is the short computer time needed to find solutions while the disadvantages are related to the often-used build-up factor that is extrapolated from high to low energies or with unknown geometrical conditions, which can lead to significant errors in shielding results. The aim of this work is to investigate how good are some deterministic methods to calculating low-energy shielding, using attenuation coefficients and build-up factor corrections. Commercial software MicroShield 5.05 has been used as the deterministic code while MCNP has been used as the Monte Carlo code. Point and cylindrical sources with slab shield have been defined allowing comparison between the capability of both Monte Carlo and deterministic methods in a day-by-day shielding calculation using sensitivity analysis of significant parameters, such as energy and geometrical conditions.
Comparison of deterministic and Monte Carlo methods in shielding design
International Nuclear Information System (INIS)
Oliveira, A. D.; Oliveira, C.
2005-01-01
In shielding calculation, deterministic methods have some advantages and also some disadvantages relative to other kind of codes, such as Monte Carlo. The main advantage is the short computer time needed to find solutions while the disadvantages are related to the often-used build-up factor that is extrapolated from high to low energies or with unknown geometrical conditions, which can lead to significant errors in shielding results. The aim of this work is to investigate how good are some deterministic methods to calculating low-energy shielding, using attenuation coefficients and build-up factor corrections. Commercial software MicroShield 5.05 has been used as the deterministic code while MCNP has been used as the Monte Carlo code. Point and cylindrical sources with slab shield have been defined allowing comparison between the capability of both Monte Carlo and deterministic methods in a day-by-day shielding calculation using sensitivity analysis of significant parameters, such as energy and geometrical conditions. (authors)
Deterministic teleportation using single-photon entanglement as a resource
DEFF Research Database (Denmark)
Björk, Gunnar; Laghaout, Amine; Andersen, Ulrik L.
2012-01-01
We outline a proof that teleportation with a single particle is, in principle, just as reliable as with two particles. We thereby hope to dispel the skepticism surrounding single-photon entanglement as a valid resource in quantum information. A deterministic Bell-state analyzer is proposed which...
Empirical and deterministic accuracies of across-population genomic prediction
Wientjes, Y.C.J.; Veerkamp, R.F.; Bijma, P.; Bovenhuis, H.; Schrooten, C.; Calus, M.P.L.
2015-01-01
Background: Differences in linkage disequilibrium and in allele substitution effects of QTL (quantitative trait loci) may hinder genomic prediction across populations. Our objective was to develop a deterministic formula to estimate the accuracy of across-population genomic prediction, for which
A Deterministic Approach to the Synchronization of Cellular Automata
Garcia, J.; Garcia, P.
2011-01-01
In this work we introduce a deterministic scheme of synchronization of linear and nonlinear cellular automata (CA) with complex behavior, connected through a master-slave coupling. By using a definition of Boolean derivative, we use the linear approximation of the automata to determine a function of coupling that promotes synchronization without perturbing all the sites of the slave system.
Deterministic and Stochastic Study of Wind Farm Harmonic Currents
DEFF Research Database (Denmark)
Sainz, Luis; Mesas, Juan Jose; Teodorescu, Remus
2010-01-01
Wind farm harmonic emissions are a well-known power quality problem, but little data based on actual wind farm measurements are available in literature. In this paper, harmonic emissions of an 18 MW wind farm are investigated using extensive measurements, and the deterministic and stochastic char...
Mixed motion in deterministic ratchets due to anisotropic permeability
Kulrattanarak, T.; Sman, van der R.G.M.; Lubbersen, Y.S.; Schroën, C.G.P.H.; Pham, H.T.M.; Sarro, P.M.; Boom, R.M.
2011-01-01
Nowadays microfluidic devices are becoming popular for cell/DNA sorting and fractionation. One class of these devices, namely deterministic ratchets, seems most promising for continuous fractionation applications of suspensions (Kulrattanarak et al., 2008 [1]). Next to the two main types of particle
Simulation of quantum computation : A deterministic event-based approach
Michielsen, K; De Raedt, K; De Raedt, H
We demonstrate that locally connected networks of machines that have primitive learning capabilities can be used to perform a deterministic, event-based simulation of quantum computation. We present simulation results for basic quantum operations such as the Hadamard and the controlled-NOT gate, and
Simulation of Quantum Computation : A Deterministic Event-Based Approach
Michielsen, K.; Raedt, K. De; Raedt, H. De
2005-01-01
We demonstrate that locally connected networks of machines that have primitive learning capabilities can be used to perform a deterministic, event-based simulation of quantum computation. We present simulation results for basic quantum operations such as the Hadamard and the controlled-NOT gate, and
Using a satisfiability solver to identify deterministic finite state automata
Heule, M.J.H.; Verwer, S.
2009-01-01
We present an exact algorithm for identification of deterministic finite automata (DFA) which is based on satisfiability (SAT) solvers. Despite the size of the low level SAT representation, our approach seems to be competitive with alternative techniques. Our contributions are threefold: First, we
Deterministic mean-variance-optimal consumption and investment
DEFF Research Database (Denmark)
Christiansen, Marcus; Steffensen, Mogens
2013-01-01
In dynamic optimal consumption–investment problems one typically aims to find an optimal control from the set of adapted processes. This is also the natural starting point in case of a mean-variance objective. In contrast, we solve the optimization problem with the special feature that the consum......In dynamic optimal consumption–investment problems one typically aims to find an optimal control from the set of adapted processes. This is also the natural starting point in case of a mean-variance objective. In contrast, we solve the optimization problem with the special feature...... that the consumption rate and the investment proportion are constrained to be deterministic processes. As a result we get rid of a series of unwanted features of the stochastic solution including diffusive consumption, satisfaction points and consistency problems. Deterministic strategies typically appear in unit......-linked life insurance contracts, where the life-cycle investment strategy is age dependent but wealth independent. We explain how optimal deterministic strategies can be found numerically and present an example from life insurance where we compare the optimal solution with suboptimal deterministic strategies...
Simulation of photonic waveguides with deterministic aperiodic nanostructures for biosensing
DEFF Research Database (Denmark)
Neustock, Lars Thorben; Paulsen, Moritz; Jahns, Sabrina
2016-01-01
Photonic waveguides with deterministic aperiodic corrugations offer rich spectral characteristics under surface-normal illumination. The finite-element method (FEM), the finite-difference time-domain (FDTD) method and a rigorous coupled wave algorithm (RCWA) are compared for computing the near...
Langevin equation with the deterministic algebraically correlated noise
International Nuclear Information System (INIS)
Ploszajczak, M.; Srokowski, T.
1995-01-01
Stochastic differential equations with the deterministic, algebraically correlated noise are solved for a few model problems. The chaotic force with both exponential and algebraic temporal correlations is generated by the adjoined extended Sinai billiard with periodic boundary conditions. The correspondence between the autocorrelation function for the chaotic force and both the survival probability and the asymptotic energy distribution of escaping particles is found. (author)
Deterministic dense coding and faithful teleportation with multipartite graph states
International Nuclear Information System (INIS)
Huang, C.-Y.; Yu, I-C.; Lin, F.-L.; Hsu, L.-Y.
2009-01-01
We propose schemes to perform the deterministic dense coding and faithful teleportation with multipartite graph states. We also find the sufficient and necessary condition of a viable graph state for the proposed schemes. That is, for the associated graph, the reduced adjacency matrix of the Tanner-type subgraph between senders and receivers should be invertible.
Deterministic algorithms for multi-criteria Max-TSP
Manthey, Bodo
2012-01-01
We present deterministic approximation algorithms for the multi-criteria maximum traveling salesman problem (Max-TSP). Our algorithms are faster and simpler than the existing randomized algorithms. We devise algorithms for the symmetric and asymmetric multi-criteria Max-TSP that achieve ratios of
A Deterministic Annealing Approach to Clustering AIRS Data
Guillaume, Alexandre; Braverman, Amy; Ruzmaikin, Alexander
2012-01-01
We will examine the validity of means and standard deviations as a basis for climate data products. We will explore the conditions under which these two simple statistics are inadequate summaries of the underlying empirical probability distributions by contrasting them with a nonparametric, method called Deterministic Annealing technique
Non-parametric Bayesian inference for inhomogeneous Markov point processes
DEFF Research Database (Denmark)
Berthelsen, Kasper Klitgaard; Møller, Jesper; Johansen, Per Michael
is a shot noise process, and the interaction function for a pair of points depends only on the distance between the two points and is a piecewise linear function modelled by a marked Poisson process. Simulation of the resulting posterior using a Metropolis-Hastings algorithm in the "conventional" way...
The Markov moment problem and extremal problems
Kreĭn, M G; Louvish, D
1977-01-01
In this book, an extensive circle of questions originating in the classical work of P. L. Chebyshev and A. A. Markov is considered from the more modern point of view. It is shown how results and methods of the generalized moment problem are interlaced with various questions of the geometry of convex bodies, algebra, and function theory. From this standpoint, the structure of convex and conical hulls of curves is studied in detail and isoperimetric inequalities for convex hulls are established; a theory of orthogonal and quasiorthogonal polynomials is constructed; problems on limiting values of integrals and on least deviating functions (in various metrics) are generalized and solved; problems in approximation theory and interpolation and extrapolation in various function classes (analytic, absolutely monotone, almost periodic, etc.) are solved, as well as certain problems in optimal control of linear objects.
Learning Markov models for stationary system behaviors
DEFF Research Database (Denmark)
Chen, Yingke; Mao, Hua; Jaeger, Manfred
2012-01-01
to a single long observation sequence, and in these situations existing automatic learning methods cannot be applied. In this paper, we adapt algorithms for learning variable order Markov chains from a single observation sequence of a target system, so that stationary system properties can be verified using......Establishing an accurate model for formal verification of an existing hardware or software system is often a manual process that is both time consuming and resource demanding. In order to ease the model construction phase, methods have recently been proposed for automatically learning accurate...... the learned model. Experiments demonstrate that system properties (formulated as stationary probabilities of LTL formulas) can be reliably identified using the learned model....
Neuroevolution Mechanism for Hidden Markov Model
Directory of Open Access Journals (Sweden)
Nabil M. Hewahi
2011-12-01
Full Text Available Hidden Markov Model (HMM is a statistical model based on probabilities. HMM is becoming one of the major models involved in many applications such as natural language
processing, handwritten recognition, image processing, prediction systems and many more. In this research we are concerned with finding out the best HMM for a certain application domain. We propose a neuroevolution process that is based first on converting the HMM to a neural network, then generating many neural networks at random where each represents a HMM. We proceed by
applying genetic operators to obtain new set of neural networks where each represents HMMs, and updating the population. Finally select the best neural network based on a fitness function.
Improved hidden Markov model for nosocomial infections.
Khader, Karim; Leecaster, Molly; Greene, Tom; Samore, Matthew; Thomas, Alun
2014-12-01
We propose a novel hidden Markov model (HMM) for parameter estimation in hospital transmission models, and show that commonly made simplifying assumptions can lead to severe model misspecification and poor parameter estimates. A standard HMM that embodies two commonly made simplifying assumptions, namely a fixed patient count and binomially distributed detections is compared with a new alternative HMM that does not require these simplifying assumptions. Using simulated data, we demonstrate how each of the simplifying assumptions used by the standard model leads to model misspecification, whereas the alternative model results in accurate parameter estimates. © The Authors 2013. Published by Oxford University Press on behalf of the Institute of Mathematics and its Applications. All rights reserved.
Estimation and uncertainty of reversible Markov models.
Trendelkamp-Schroer, Benjamin; Wu, Hao; Paul, Fabian; Noé, Frank
2015-11-07
Reversibility is a key concept in Markov models and master-equation models of molecular kinetics. The analysis and interpretation of the transition matrix encoding the kinetic properties of the model rely heavily on the reversibility property. The estimation of a reversible transition matrix from simulation data is, therefore, crucial to the successful application of the previously developed theory. In this work, we discuss methods for the maximum likelihood estimation of transition matrices from finite simulation data and present a new algorithm for the estimation if reversibility with respect to a given stationary vector is desired. We also develop new methods for the Bayesian posterior inference of reversible transition matrices with and without given stationary vector taking into account the need for a suitable prior distribution preserving the meta-stable features of the observed process during posterior inference. All algorithms here are implemented in the PyEMMA software--http://pyemma.org--as of version 2.0.
Monte Carlo simulation of Markov unreliability models
International Nuclear Information System (INIS)
Lewis, E.E.; Boehm, F.
1984-01-01
A Monte Carlo method is formulated for the evaluation of the unrealibility of complex systems with known component failure and repair rates. The formulation is in terms of a Markov process allowing dependences between components to be modeled and computational efficiencies to be achieved in the Monte Carlo simulation. Two variance reduction techniques, forced transition and failure biasing, are employed to increase computational efficiency of the random walk procedure. For an example problem these result in improved computational efficiency by more than three orders of magnitudes over analog Monte Carlo. The method is generalized to treat problems with distributed failure and repair rate data, and a batching technique is introduced and shown to result in substantial increases in computational efficiency for an example problem. A method for separating the variance due to the data uncertainty from that due to the finite number of random walks is presented. (orig.)