DEFF Research Database (Denmark)
Silvennoinen, Annastiina; Teräsvirta, Timo
This article contains a review of multivariate GARCH models. Most common GARCH models are presented and their properties considered. This also includes nonparametric and semiparametric models. Existing specification and misspecification tests are discussed. Finally, there is an empirical example...
GARCH Modelling of Cryptocurrencies
Jeffrey Chu; Stephen Chan; Saralees Nadarajah; Joerg Osterrieder
2017-01-01
With the exception of Bitcoin, there appears to be little or no literature on GARCH modelling of cryptocurrencies. This paper provides the first GARCH modelling of the seven most popular cryptocurrencies. Twelve GARCH models are fitted to each cryptocurrency, and their fits are assessed in terms of five criteria. Conclusions are drawn on the best fitting models, forecasts and acceptability of value at risk estimates.
GARCH Modelling of Cryptocurrencies
Directory of Open Access Journals (Sweden)
Jeffrey Chu
2017-10-01
Full Text Available With the exception of Bitcoin, there appears to be little or no literature on GARCH modelling of cryptocurrencies. This paper provides the first GARCH modelling of the seven most popular cryptocurrencies. Twelve GARCH models are fitted to each cryptocurrency, and their fits are assessed in terms of five criteria. Conclusions are drawn on the best fitting models, forecasts and acceptability of value at risk estimates.
Quadratic Term Structure Models in Discrete Time
Marco Realdon
2006-01-01
This paper extends the results on quadratic term structure models in continuos time to the discrete time setting. The continuos time setting can be seen as a special case of the discrete time one. Recursive closed form solutions for zero coupon bonds are provided even in the presence of multiple correlated underlying factors. Pricing bond options requires simple integration. Model parameters may well be time dependent without scuppering such tractability. Model estimation does not require a r...
Discrete-time rewards model-checked
Larsen, K.G.; Andova, S.; Niebert, Peter; Hermanns, H.; Katoen, Joost P.
2003-01-01
This paper presents a model-checking approach for analyzing discrete-time Markov reward models. For this purpose, the temporal logic probabilistic CTL is extended with reward constraints. This allows to formulate complex measures – involving expected as well as accumulated rewards – in a precise and
DEFF Research Database (Denmark)
Pedersen, Rasmus Søndergaard; Rahbek, Anders
2017-01-01
We present novel theory for testing for reduction of GARCH-X type models with an exogenous (X) covariate to standard GARCH type models. To deal with the problems of potential nuisance parameters on the boundary of the parameter space as well as lack of identification under the null, we exploit...... a noticeable property of specific zero-entries in the inverse information of the GARCH-X type models. Specifically, we consider sequential testing based on two likelihood ratio tests and as demonstrated the structure of the inverse information implies that the proposed test neither depends on whether...... the nuisance parameters lie on the boundary of the parameter space, nor on lack of identification. Our general results on GARCH-X type models are applied to Gaussian based GARCH-X models, GARCH-X models with Student's t-distributed innovations as well as the integer-valued GARCH-X (PAR-X) models....
Volatility estimation using a rational GARCH model
Directory of Open Access Journals (Sweden)
Tetsuya Takaishi
2018-03-01
Full Text Available The rational GARCH (RGARCH model has been proposed as an alternative GARCHmodel that captures the asymmetric property of volatility. In addition to the previously proposedRGARCH model, we propose an alternative RGARCH model called the RGARCH-Exp model thatis more stable when dealing with outliers. We measure the performance of the volatility estimationby a loss function calculated using realized volatility as a proxy for true volatility and compare theRGARCH-type models with other asymmetric type models such as the EGARCH and GJR models.We conduct empirical studies of six stocks on the Tokyo Stock Exchange and find that a volatilityestimation using the RGARCH-type models outperforms the GARCH model and is comparable toother asymmetric GARCH models.
Discrete-time modelling of musical instruments
International Nuclear Information System (INIS)
Vaelimaeki, Vesa; Pakarinen, Jyri; Erkut, Cumhur; Karjalainen, Matti
2006-01-01
This article describes physical modelling techniques that can be used for simulating musical instruments. The methods are closely related to digital signal processing. They discretize the system with respect to time, because the aim is to run the simulation using a computer. The physics-based modelling methods can be classified as mass-spring, modal, wave digital, finite difference, digital waveguide and source-filter models. We present the basic theory and a discussion on possible extensions for each modelling technique. For some methods, a simple model example is chosen from the existing literature demonstrating a typical use of the method. For instance, in the case of the digital waveguide modelling technique a vibrating string model is discussed, and in the case of the wave digital filter technique we present a classical piano hammer model. We tackle some nonlinear and time-varying models and include new results on the digital waveguide modelling of a nonlinear string. Current trends and future directions in physical modelling of musical instruments are discussed
Nonlinear GARCH model and 1 / f noise
Kononovicius, A.; Ruseckas, J.
2015-06-01
Auto-regressive conditionally heteroskedastic (ARCH) family models are still used, by practitioners in business and economic policy making, as a conditional volatility forecasting models. Furthermore ARCH models still are attracting an interest of the researchers. In this contribution we consider the well known GARCH(1,1) process and its nonlinear modifications, reminiscent of NGARCH model. We investigate the possibility to reproduce power law statistics, probability density function and power spectral density, using ARCH family models. For this purpose we derive stochastic differential equations from the GARCH processes in consideration. We find the obtained equations to be similar to a general class of stochastic differential equations known to reproduce power law statistics. We show that linear GARCH(1,1) process has power law distribution, but its power spectral density is Brownian noise-like. However, the nonlinear modifications exhibit both power law distribution and power spectral density of the 1 /fβ form, including 1 / f noise.
Modeling discrete time-to-event data
Tutz, Gerhard
2016-01-01
This book focuses on statistical methods for the analysis of discrete failure times. Failure time analysis is one of the most important fields in statistical research, with applications affecting a wide range of disciplines, in particular, demography, econometrics, epidemiology and clinical research. Although there are a large variety of statistical methods for failure time analysis, many techniques are designed for failure times that are measured on a continuous scale. In empirical studies, however, failure times are often discrete, either because they have been measured in intervals (e.g., quarterly or yearly) or because they have been rounded or grouped. The book covers well-established methods like life-table analysis and discrete hazard regression models, but also introduces state-of-the art techniques for model evaluation, nonparametric estimation and variable selection. Throughout, the methods are illustrated by real life applications, and relationships to survival analysis in continuous time are expla...
Discrete time modelization of human pilot behavior
Cavalli, D.; Soulatges, D.
1975-01-01
This modelization starts from the following hypotheses: pilot's behavior is a time discrete process, he can perform only one task at a time and his operating mode depends on the considered flight subphase. Pilot's behavior was observed using an electro oculometer and a simulator cockpit. A FORTRAN program has been elaborated using two strategies. The first one is a Markovian process in which the successive instrument readings are governed by a matrix of conditional probabilities. In the second one, strategy is an heuristic process and the concepts of mental load and performance are described. The results of the two aspects have been compared with simulation data.
Heston, Steven L.; Nandi, Saikat
1999-01-01
This paper develops a discrete-time two-factor model of interest rates with analytical solutions for bonds and many interest rate derivatives when the volatility of the short rate follows a GARCH process that can be correlated with the level of the short rate itself. Besides bond and bond futures, the model yields analytical solutions for prices of European options on discount bonds (and futures) as well as other interest rate derivatives such as caps, floors, average rate options, yield curv...
Ranking multivariate GARCH models by problem dimension
M. Caporin (Massimiliano); M.J. McAleer (Michael)
2010-01-01
textabstractIn the last 15 years, several Multivariate GARCH (MGARCH) models have appeared in the literature. The two most widely known and used are the Scalar BEKK model of Engle and Kroner (1995) and Ding and Engle (2001), and the DCC model of Engle (2002). Some recent research has begun to
Conditional density estimation using fuzzy GARCH models
Almeida, R.J.; Bastürk, N.; Kaymak, U.; Costa Sousa, da J.M.; Kruse, R.; Berthold, M.R.; Moewes, C.; Gil, M.A.; Grzegorzewski, P.; Hryniewicz, O.
2013-01-01
Abstract. Time series data exhibits complex behavior including non-linearity and path-dependency. This paper proposes a flexible fuzzy GARCH model that can capture different properties of data, such as skewness, fat tails and multimodality in one single model. Furthermore, additional information and
Nonparametric volatility density estimation for discrete time models
Es, van Bert; Spreij, P.J.C.; Zanten, van J.H.
2005-01-01
We consider discrete time models for asset prices with a stationary volatility process. We aim at estimating the multivariate density of this process at a set of consecutive time instants. A Fourier-type deconvolution kernel density estimator based on the logarithm of the squared process is proposed
Stable cycling in discrete-time genetic models.
Hastings, A
1981-01-01
Examples of stable cycling are discussed for two-locus, two-allele, deterministic, discrete-time models with constant fitnesses. The cases that cycle were found by using numerical techniques to search for stable Hopf bifurcations. One consequence of the results is that apparent cases of directional selection may be due to stable cycling.
Stable cycling in discrete-time genetic models.
Hastings, A
1981-11-01
Examples of stable cycling are discussed for two-locus, two-allele, deterministic, discrete-time models with constant fitnesses. The cases that cycle were found by using numerical techniques to search for stable Hopf bifurcations. One consequence of the results is that apparent cases of directional selection may be due to stable cycling.
Modeling Covariance Breakdowns in Multivariate GARCH
Jin, Xin; Maheu, John M
2014-01-01
This paper proposes a flexible way of modeling dynamic heterogeneous covariance breakdowns in multivariate GARCH (MGARCH) models. During periods of normal market activity, volatility dynamics are governed by an MGARCH specification. A covariance breakdown is any significant temporary deviation of the conditional covariance matrix from its implied MGARCH dynamics. This is captured through a flexible stochastic component that allows for changes in the conditional variances, covariances and impl...
Disease Extinction Versus Persistence in Discrete-Time Epidemic Models.
van den Driessche, P; Yakubu, Abdul-Aziz
2018-04-12
We focus on discrete-time infectious disease models in populations that are governed by constant, geometric, Beverton-Holt or Ricker demographic equations, and give a method for computing the basic reproduction number, [Formula: see text]. When [Formula: see text] and the demographic population dynamics are asymptotically constant or under geometric growth (non-oscillatory), we prove global asymptotic stability of the disease-free equilibrium of the disease models. Under the same demographic assumption, when [Formula: see text], we prove uniform persistence of the disease. We apply our theoretical results to specific discrete-time epidemic models that are formulated for SEIR infections, cholera in humans and anthrax in animals. Our simulations show that a unique endemic equilibrium of each of the three specific disease models is asymptotically stable whenever [Formula: see text].
Option valuation with the simplified component GARCH model
DEFF Research Database (Denmark)
Dziubinski, Matt P.
We introduce the Simplified Component GARCH (SC-GARCH) option pricing model, show and discuss sufficient conditions for non-negativity of the conditional variance, apply it to low-frequency and high-frequency financial data, and consider the option valuation, comparing the model performance...
Hopf Bifurcation in a Cobweb Model with Discrete Time Delays
Directory of Open Access Journals (Sweden)
Luca Gori
2014-01-01
Full Text Available We develop a cobweb model with discrete time delays that characterise the length of production cycle. We assume a market comprised of homogeneous producers that operate as adapters by taking the (expected profit-maximising quantity as a target to adjust production and consumers with a marginal willingness to pay captured by an isoelastic demand. The dynamics of the economy is characterised by a one-dimensional delay differential equation. In this context, we show that (1 if the elasticity of market demand is sufficiently high, the steady-state equilibrium is locally asymptotically stable and (2 if the elasticity of market demand is sufficiently low, quasiperiodic oscillations emerge when the time lag (that represents the length of production cycle is high enough.
DEFF Research Database (Denmark)
Hansen, Peter Reinhard; Lunde, Asger; Voev, Valeri
We introduce a multivariate GARCH model that utilizes and models realized measures of volatility and covolatility. The realized measures extract information contained in high-frequency data that is particularly beneficial during periods with variation in volatility and covolatility. Applying the ...
Modeling energy price dynamics: GARCH versus stochastic volatility
International Nuclear Information System (INIS)
Chan, Joshua C.C.; Grant, Angelia L.
2016-01-01
We compare a number of GARCH and stochastic volatility (SV) models using nine series of oil, petroleum product and natural gas prices in a formal Bayesian model comparison exercise. The competing models include the standard models of GARCH(1,1) and SV with an AR(1) log-volatility process, as well as more flexible models with jumps, volatility in mean, leverage effects, and t distributed and moving average innovations. We find that: (1) SV models generally compare favorably to their GARCH counterparts; (2) the jump component and t distributed innovations substantially improve the performance of the standard GARCH, but are unimportant for the SV model; (3) the volatility feedback channel seems to be superfluous; (4) the moving average component markedly improves the fit of both GARCH and SV models; and (5) the leverage effect is important for modeling crude oil prices—West Texas Intermediate and Brent—but not for other energy prices. Overall, the SV model with moving average innovations is the best model for all nine series. - Highlights: • We compare a variety of GARCH and SV models for fitting nine series of energy prices. • We find that SV models generally compare favorably to their GARCH counterparts. • The SV model with moving average innovations is the best model for all nine series.
Empirical study of the GARCH model with rational errors
International Nuclear Information System (INIS)
Chen, Ting Ting; Takaishi, Tetsuya
2013-01-01
We use the GARCH model with a fat-tailed error distribution described by a rational function and apply it to stock price data on the Tokyo Stock Exchange. To determine the model parameters we perform Bayesian inference to the model. Bayesian inference is implemented by the Metropolis-Hastings algorithm with an adaptive multi-dimensional Student's t-proposal density. In order to compare our model with the GARCH model with the standard normal errors, we calculate the information criteria AIC and DIC, and find that both criteria favor the GARCH model with a rational error distribution. We also calculate the accuracy of the volatility by using the realized volatility and find that a good accuracy is obtained for the GARCH model with a rational error distribution. Thus we conclude that the GARCH model with a rational error distribution is superior to the GARCH model with the normal errors and it can be used as an alternative GARCH model to those with other fat-tailed distributions
Forecasting Performance of Asymmetric GARCH Stock Market Volatility Models
Directory of Open Access Journals (Sweden)
Hojin Lee
2009-12-01
Full Text Available We investigate the asymmetry between positive and negative returns in their effect on conditional variance of the stock market index and incorporate the characteristics to form an out-of-sample volatility forecast. Contrary to prior evidence, however, the results in this paper suggest that no asymmetric GARCH model is superior to basic GARCH(1,1 model. It is our prior knowledge that, for equity returns, it is unlikely that positive and negative shocks have the same impact on the volatility. In order to reflect this intuition, we implement three diagnostic tests for volatility models: the Sign Bias Test, the Negative Size Bias Test, and the Positive Size Bias Test and the tests against the alternatives of QGARCH and GJR-GARCH. The asymmetry test results indicate that the sign and the size of the unexpected return shock do not influence current volatility differently which contradicts our presumption that there are asymmetric effects in the stock market volatility. This result is in line with various diagnostic tests which are designed to determine whether the GARCH(1,1 volatility estimates adequately represent the data. The diagnostic tests in section 2 indicate that the GARCH(1,1 model for weekly KOSPI returns is robust to the misspecification test. We also investigate two representative asymmetric GARCH models, QGARCH and GJR-GARCH model, for our out-of-sample forecasting performance. The out-of-sample forecasting ability test reveals that no single model is clearly outperforming. It is seen that the GJR-GARCH and QGARCH model give mixed results in forecasting ability on all four criteria across all forecast horizons considered. Also, the predictive accuracy test of Diebold and Mariano based on both absolute and squared prediction errors suggest that the forecasts from the linear and asymmetric GARCH models need not be significantly different from each other.
Analysis of Spin Financial Market by GARCH Model
International Nuclear Information System (INIS)
Takaishi, Tetsuya
2013-01-01
A spin model is used for simulations of financial markets. To determine return volatility in the spin financial market we use the GARCH model often used for volatility estimation in empirical finance. We apply the Bayesian inference performed by the Markov Chain Monte Carlo method to the parameter estimation of the GARCH model. It is found that volatility determined by the GARCH model exhibits ''volatility clustering'' also observed in the real financial markets. Using volatility determined by the GARCH model we examine the mixture-of-distribution hypothesis (MDH) suggested for the asset return dynamics. We find that the returns standardized by volatility are approximately standard normal random variables. Moreover we find that the absolute standardized returns show no significant autocorrelation. These findings are consistent with the view of the MDH for the return dynamics
Empirical investigation on modeling solar radiation series with ARMA–GARCH models
International Nuclear Information System (INIS)
Sun, Huaiwei; Yan, Dong; Zhao, Na; Zhou, Jianzhong
2015-01-01
Highlights: • Apply 6 ARMA–GARCH(-M) models to model and forecast solar radiation. • The ARMA–GARCH(-M) models produce more accurate radiation forecasting than conventional methods. • Show that ARMA–GARCH-M models are more effective for forecasting solar radiation mean and volatility. • The ARMA–EGARCH-M is robust and the ARMA–sGARCH-M is very competitive. - Abstract: Simulation of radiation is one of the most important issues in solar utilization. Time series models are useful tools in the estimation and forecasting of solar radiation series and their changes. In this paper, the effectiveness of autoregressive moving average (ARMA) models with various generalized autoregressive conditional heteroskedasticity (GARCH) processes, namely ARMA–GARCH models are evaluated for their effectiveness in radiation series. Six different GARCH approaches, which contain three different ARMA–GARCH models and corresponded GARCH in mean (ARMA–GARCH-M) models, are applied in radiation data sets from two representative climate stations in China. Multiple evaluation metrics of modeling sufficiency are used for evaluating the performances of models. The results show that the ARMA–GARCH(-M) models are effective in radiation series estimation. Both in fitting and prediction of radiation series, the ARMA–GARCH(-M) models show better modeling sufficiency than traditional models, while ARMA–EGARCH-M models are robustness in two sites and the ARMA–sGARCH-M models appear very competitive. Comparisons of statistical diagnostics and model performance clearly show that the ARMA–GARCH-M models make the mean radiation equations become more sufficient. It is recommended the ARMA–GARCH(-M) models to be the preferred method to use in the modeling of solar radiation series
Performance analysis of chi models using discrete-time probabilistic reward graphs
Trcka, N.; Georgievska, S.; Markovski, J.; Andova, S.; Vink, de E.P.
2008-01-01
We propose the model of discrete-time probabilistic reward graphs (DTPRGs) for performance analysis of systems exhibiting discrete deterministic time delays and probabilistic behavior, via their interpretation as discrete-time Markov reward chains, full-fledged platform for qualitative and
Volatility in GARCH Models of Business Tendency Index
Wahyuni, Dwi A. S.; Wage, Sutarman; Hartono, Ateng
2018-01-01
This paper aims to obtain a model of business tendency index by considering volatility factor. Volatility factor detected by ARCH (Autoregressive Conditional Heteroscedasticity). The ARCH checking was performed using the Lagrange multiplier test. The modeling is Generalized Autoregressive Conditional Heteroscedasticity (GARCH) are able to overcome volatility problems by incorporating past residual elements and residual variants.
Robust Ranking of Multivariate GARCH Models by Problem Dimension
M. Caporin (Massimiliano); M.J. McAleer (Michael)
2012-01-01
textabstractDuring the last 15 years, several Multivariate GARCH (MGARCH) models have appeared in the literature. Recent research has begun to examine MGARCH specifications in terms of their out-of-sample forecasting performance. We provide an empirical comparison of alternative MGARCH models,
Ranking Multivariate GARCH Models by Problem Dimension: An Empirical Evaluation
M. Caporin (Massimiliano); M.J. McAleer (Michael)
2011-01-01
textabstractIn the last 15 years, several Multivariate GARCH (MGARCH) models have appeared in the literature. Recent research has begun to examine MGARCH specifications in terms of their out-of-sample forecasting performance. In this paper, we provide an empirical comparison of a set of models,
From discrete-time models to continuous-time, asynchronous modeling of financial markets
Boer, Katalin; Kaymak, Uzay; Spiering, Jaap
2007-01-01
Most agent-based simulation models of financial markets are discrete-time in nature. In this paper, we investigate to what degree such models are extensible to continuous-time, asynchronous modeling of financial markets. We study the behavior of a learning market maker in a market with information
From Discrete-Time Models to Continuous-Time, Asynchronous Models of Financial Markets
K. Boer-Sorban (Katalin); U. Kaymak (Uzay); J. Spiering (Jaap)
2006-01-01
textabstractMost agent-based simulation models of financial markets are discrete-time in nature. In this paper, we investigate to what degree such models are extensible to continuous-time, asynchronous modelling of financial markets. We study the behaviour of a learning market maker in a market with
Discrete time duration models with group-level heterogeneity
DEFF Research Database (Denmark)
Frederiksen, Anders; Honoré, Bo; Hu, Loujia
2007-01-01
Dynamic discrete choice panel data models have received a great deal of attention. In those models, the dynamics is usually handled by including the lagged outcome as an explanatory variable. In this paper we consider an alternative model in which the dynamics is handled by using the duration...
A Dynamic Economic Model with Discrete Time and Consumer Sentiment
Directory of Open Access Journals (Sweden)
L. I. Dobrescu
2009-01-01
is replaced by a (quasi periodic motion. We associate the difference stochastic equation to the model by randomizing the control parameter d and by adding one stochastic control. Numerical simulations are made for the deterministic and stochastic models, for different values of the control parameter d.
Modeling returns volatility: Realized GARCH incorporating realized risk measure
Jiang, Wei; Ruan, Qingsong; Li, Jianfeng; Li, Ye
2018-06-01
This study applies realized GARCH models by introducing several risk measures of intraday returns into the measurement equation, to model the daily volatility of E-mini S&P 500 index futures returns. Besides using the conventional realized measures, realized volatility and realized kernel as our benchmarks, we also use generalized realized risk measures, realized absolute deviation, and two realized tail risk measures, realized value-at-risk and realized expected shortfall. The empirical results show that realized GARCH models using the generalized realized risk measures provide better volatility estimation for the in-sample and substantial improvement in volatility forecasting for the out-of-sample. In particular, the realized expected shortfall performs best for all of the alternative realized measures. Our empirical results reveal that future volatility may be more attributable to present losses (risk measures). The results are robust to different sample estimation windows.
Semiparametric Inference in a GARCH-in-Mean Model
DEFF Research Database (Denmark)
Christensen, Bent Jesper; Dahl, Christian Møller; Iglesias, Emma M.
A new semiparametric estimator for an empirical asset pricing model with general nonpara- metric risk-return tradeoff and a GARCH process for the underlying volatility is introduced. The estimator does not rely on any initial parametric estimator of the conditional mean func- tion, and this feature...... facilitates the derivation of asymptotic theory under possible nonlinearity of unspecified form of the risk-return tradeoff. Besides the nonlinear GARCH-in-mean effect, our specification accommodates exogenous regressors that are typically used as conditioning variables entering linearly in the mean equation...... with the fully parametric approach and the iterative semiparametric approach using a parametric initial esti- mate proposed by Conrad and Mammen (2008). An empirical application to the daily S&P 500 stock market returns suggests that the linear relation between conditional expected return and conditional...
Directory of Open Access Journals (Sweden)
Chellaboina Vijaysekhar
2005-01-01
Full Text Available We develop thermodynamic models for discrete-time large-scale dynamical systems. Specifically, using compartmental dynamical system theory, we develop energy flow models possessing energy conservation, energy equipartition, temperature equipartition, and entropy nonconservation principles for discrete-time, large-scale dynamical systems. Furthermore, we introduce a new and dual notion to entropy; namely, ectropy, as a measure of the tendency of a dynamical system to do useful work and grow more organized, and show that conservation of energy in an isolated thermodynamic system necessarily leads to nonconservation of ectropy and entropy. In addition, using the system ectropy as a Lyapunov function candidate, we show that our discrete-time, large-scale thermodynamic energy flow model has convergent trajectories to Lyapunov stable equilibria determined by the system initial subsystem energies.
Modeling rainfall-runoff relationship using multivariate GARCH model
Modarres, R.; Ouarda, T. B. M. J.
2013-08-01
The traditional hydrologic time series approaches are used for modeling, simulating and forecasting conditional mean of hydrologic variables but neglect their time varying variance or the second order moment. This paper introduces the multivariate Generalized Autoregressive Conditional Heteroscedasticity (MGARCH) modeling approach to show how the variance-covariance relationship between hydrologic variables varies in time. These approaches are also useful to estimate the dynamic conditional correlation between hydrologic variables. To illustrate the novelty and usefulness of MGARCH models in hydrology, two major types of MGARCH models, the bivariate diagonal VECH and constant conditional correlation (CCC) models are applied to show the variance-covariance structure and cdynamic correlation in a rainfall-runoff process. The bivariate diagonal VECH-GARCH(1,1) and CCC-GARCH(1,1) models indicated both short-run and long-run persistency in the conditional variance-covariance matrix of the rainfall-runoff process. The conditional variance of rainfall appears to have a stronger persistency, especially long-run persistency, than the conditional variance of streamflow which shows a short-lived drastic increasing pattern and a stronger short-run persistency. The conditional covariance and conditional correlation coefficients have different features for each bivariate rainfall-runoff process with different degrees of stationarity and dynamic nonlinearity. The spatial and temporal pattern of variance-covariance features may reflect the signature of different physical and hydrological variables such as drainage area, topography, soil moisture and ground water fluctuations on the strength, stationarity and nonlinearity of the conditional variance-covariance for a rainfall-runoff process.
Modeling the Volatility of Exchange Rates: GARCH Models
Directory of Open Access Journals (Sweden)
Fahima Charef
2017-03-01
Full Text Available The modeling of the dynamics of the exchange rate at a long time remains a financial and economic research center. In our research we tried to study the relationship between the evolution of exchange rates and macroeconomic fundamentals. Our empirical study is based on a series of exchange rates for the Tunisian dinar against three currencies of major trading partners (dollar, euro, yen and fundamentals (the terms of trade, the inflation rate, the interest rate differential, of monthly data, from jan 2000 to dec-2014, for the case of the Tunisia. We have adopted models of conditional heteroscedasticity (ARCH, GARCH, EGARCH, TGARCH. The results indicate that there is a partial relationship between the evolution of the Tunisian dinar exchange rates and macroeconomic variables.
Exponential GARCH Modeling with Realized Measures of Volatility
DEFF Research Database (Denmark)
Hansen, Peter Reinhard; Huang, Zhuo
returns and volatility. We apply the model to DJIA stocks and an exchange traded fund that tracks the S&P 500 index and find that specifications with multiple realized measures dominate those that rely on a single realized measure. The empirical analysis suggests some convenient simplifications......We introduce the Realized Exponential GARCH model that can utilize multiple realized volatility measures for the modeling of a return series. The model specifies the dynamic properties of both returns and realized measures, and is characterized by a flexible modeling of the dependence between...
Directory of Open Access Journals (Sweden)
Melike Bildirici
2014-01-01
Full Text Available The study has two aims. The first aim is to propose a family of nonlinear GARCH models that incorporate fractional integration and asymmetric power properties to MS-GARCH processes. The second purpose of the study is to augment the MS-GARCH type models with artificial neural networks to benefit from the universal approximation properties to achieve improved forecasting accuracy. Therefore, the proposed Markov-switching MS-ARMA-FIGARCH, APGARCH, and FIAPGARCH processes are further augmented with MLP, Recurrent NN, and Hybrid NN type neural networks. The MS-ARMA-GARCH family and MS-ARMA-GARCH-NN family are utilized for modeling the daily stock returns in an emerging market, the Istanbul Stock Index (ISE100. Forecast accuracy is evaluated in terms of MAE, MSE, and RMSE error criteria and Diebold-Mariano equal forecast accuracy tests. The results suggest that the fractionally integrated and asymmetric power counterparts of Gray’s MS-GARCH model provided promising results, while the best results are obtained for their neural network based counterparts. Further, among the models analyzed, the models based on the Hybrid-MLP and Recurrent-NN, the MS-ARMA-FIAPGARCH-HybridMLP, and MS-ARMA-FIAPGARCH-RNN provided the best forecast performances over the baseline single regime GARCH models and further, over the Gray’s MS-GARCH model. Therefore, the models are promising for various economic applications.
The problem with time in mixed continuous/discrete time modelling
Rovers, K.C.; Kuper, Jan; Smit, Gerardus Johannes Maria
The design of cyber-physical systems requires the use of mixed continuous time and discrete time models. Current modelling tools have problems with time transformations (such as a time delay) or multi-rate systems. We will present a novel approach that implements signals as functions of time,
DEFF Research Database (Denmark)
Silvennoinen, Annastiina; Teräsvirta, Timo
In this paper we propose a multivariate GARCH model with a time-varying conditional correlation structure. The new Double Smooth Transition Conditional Correlation GARCH model extends the Smooth Transition Conditional Correlation GARCH model of Silvennoinen and Ter¨asvirta (2005) by including...... another variable according to which the correlations change smoothly between states of constant correlations. A Lagrange multiplier test is derived to test the constancy of correlations against the DSTCC-GARCH model, and another one to test for another transition in the STCC-GARCH framework. In addition......, other specification tests, with the aim of aiding the model building procedure, are considered. Analytical expressions for the test statistics and the required derivatives are provided. The model is applied to a selection of world stock indices, and it is found that time is an important factor affecting...
Realized GARCH: A Complete Model of Returns and Realized Measures of Volatility
DEFF Research Database (Denmark)
Hansen, Peter Reinhard; Huang, Zhuo (Albert); Shek, Howard Howan
GARCH models have been successful in modeling financial returns. Still, much is to be gained by incorporating a realized measure of volatility in these models. In this paper we introduce a new framework for the joint modeling of returns and realized measures of volatility. The Realized GARCH...... framework nests most GARCH models as special cases and is, in many ways, a natural extension of standard GARCH models. We pay special attention to linear and log-linear Realized GARCH specifications. This class of models has several attractive features. It retains the simplicity and tractability...... to latent volatility. This equation facilitates a simple modeling of the dependence between returns and future volatility that is commonly referred to as the leverage effect. An empirical application with DJIA stocks and an exchange traded index fund shows that a simple Realized GARCH structure leads...
Directory of Open Access Journals (Sweden)
Mohd Tahir Ismail
2016-06-01
Full Text Available The daily returns of four African countries' stock market indices for the period January 2, 2000, to December 31, 2014, were employed to compare the GARCH(1,1 model and a newly proposed Maximal Overlap Discreet Wavelet Transform (MODWT-GARCH(1,1 model. The results showed that although both models fit the returns data well, the forecast produced by the GARCH(1,1 model underestimates the observed returns whereas the newly proposed MODWT-GARCH(1,1 model generates an accurate forecast value of the observed returns. The results generally showed that the newly proposed MODWT-GARCH(1,1 model best fits returns series for these African countries. Hence the proposed MODWT-GARCH should be applied on other context to further verify its validity.
The ruin probability of a discrete time risk model under constant interest rate with heavy tails
Tang, Q.
2004-01-01
This paper investigates the ultimate ruin probability of a discrete time risk model with a positive constant interest rate. Under the assumption that the gross loss of the company within one year is subexponentially distributed, a simple asymptotic relation for the ruin probability is derived and
Ecological monitoring in a discrete-time prey-predator model.
Gámez, M; López, I; Rodríguez, C; Varga, Z; Garay, J
2017-09-21
The paper is aimed at the methodological development of ecological monitoring in discrete-time dynamic models. In earlier papers, in the framework of continuous-time models, we have shown how a systems-theoretical methodology can be applied to the monitoring of the state process of a system of interacting populations, also estimating certain abiotic environmental changes such as pollution, climatic or seasonal changes. In practice, however, there may be good reasons to use discrete-time models. (For instance, there may be discrete cycles in the development of the populations, or observations can be made only at discrete time steps.) Therefore the present paper is devoted to the development of the monitoring methodology in the framework of discrete-time models of population ecology. By monitoring we mean that, observing only certain component(s) of the system, we reconstruct the whole state process. This may be necessary, e.g., when in a complex ecosystem the observation of the densities of certain species is impossible, or too expensive. For the first presentation of the offered methodology, we have chosen a discrete-time version of the classical Lotka-Volterra prey-predator model. This is a minimal but not trivial system where the methodology can still be presented. We also show how this methodology can be applied to estimate the effect of an abiotic environmental change, using a component of the population system as an environmental indicator. Although this approach is illustrated in a simplest possible case, it can be easily extended to larger ecosystems with several interacting populations and different types of abiotic environmental effects. Copyright © 2017 Elsevier Ltd. All rights reserved.
Discrete time motion model for guiding people in urban areas using multiple robots
Garrell Zulueta, Anais; Sanfeliu Cortés, Alberto; Moreno-Noguer, Francesc
2009-01-01
We present a new model for people guidance in urban settings using several mobile robots, that overcomes the limitations of existing approaches, which are either tailored to tightly bounded environments, or based on unrealistic human behaviors. Although the robots motion is controlled by means of a standard particle filter formulation, the novelty of our approach resides in how the environment and human and robot motions are modeled. In particular we define a “Discrete-Time-Motion” model, whi...
Modelling world gold prices and USD foreign exchange relationship using multivariate GARCH model
Ping, Pung Yean; Ahmad, Maizah Hura Binti
2014-12-01
World gold price is a popular investment commodity. The series have often been modeled using univariate models. The objective of this paper is to show that there is a co-movement between gold price and USD foreign exchange rate. Using the effect of the USD foreign exchange rate on the gold price, a model that can be used to forecast future gold prices is developed. For this purpose, the current paper proposes a multivariate GARCH (Bivariate GARCH) model. Using daily prices of both series from 01.01.2000 to 05.05.2014, a causal relation between the two series understudied are found and a bivariate GARCH model is produced.
Reliable gain-scheduled control of discrete-time systems and its application to CSTR model
Sakthivel, R.; Selvi, S.; Mathiyalagan, K.; Shi, Y.
2016-10-01
This paper is focused on reliable gain-scheduled controller design for a class of discrete-time systems with randomly occurring nonlinearities and actuator fault. Further, the nonlinearity in the system model is assumed to occur randomly according to a Bernoulli distribution with measurable time-varying probability in real time. The main purpose of this paper is to design a gain-scheduled controller by implementing a probability-dependent Lyapunov function and linear matrix inequality (LMI) approach such that the closed-loop discrete-time system is stochastically stable for all admissible randomly occurring nonlinearities. The existence conditions for the reliable controller is formulated in terms of LMI constraints. Finally, the proposed reliable gain-scheduled control scheme is applied on continuously stirred tank reactor model to demonstrate the effectiveness and applicability of the proposed design technique.
Local and global dynamics of Ramsey model: From continuous to discrete time.
Guzowska, Malgorzata; Michetti, Elisabetta
2018-05-01
The choice of time as a discrete or continuous variable may radically affect equilibrium stability in an endogenous growth model with durable consumption. In the continuous-time Ramsey model [F. P. Ramsey, Econ. J. 38(152), 543-559 (1928)], the steady state is locally saddle-path stable with monotonic convergence. However, in the discrete-time version, the steady state may be unstable or saddle-path stable with monotonic or oscillatory convergence or periodic solutions [see R.-A. Dana et al., Handbook on Optimal Growth 1 (Springer, 2006) and G. Sorger, Working Paper No. 1505 (2015)]. When this occurs, the discrete-time counterpart of the continuous-time model is not consistent with the initial framework. In order to obtain a discrete-time Ramsey model preserving the main properties of the continuous-time counterpart, we use a general backward and forward discretisation as initially proposed by Bosi and Ragot [Theor. Econ. Lett. 2(1), 10-15 (2012)]. The main result of the study here presented is that, with this hybrid discretisation method, fixed points and local dynamics do not change. For what it concerns global dynamics, i.e., long-run behavior for initial conditions taken on the state space, we mainly perform numerical analysis with the main scope of comparing both qualitative and quantitative evolution of the two systems, also varying some parameters of interest.
Period-doubling bifurcation and chaos control in a discrete-time mosquito model
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Qamar Din
2017-12-01
Full Text Available This article deals with the study of some qualitative properties of a discrete-time mosquito Model. It is shown that there exists period-doubling bifurcation for wide range of bifurcation parameter for the unique positive steady-state of given system. In order to control the bifurcation we introduced a feedback strategy. For further confirmation of complexity and chaotic behavior largest Lyapunov exponents are plotted.
Evaluating Portfolio Value-At-Risk Using Semi-Parametric GARCH Models
J.V.K. Rombouts; M.J.C.M. Verbeek (Marno)
2009-01-01
textabstractIn this paper we examine the usefulness of multivariate semi-parametric GARCH models for evaluating the Value-at-Risk (VaR) of a portfolio with arbitrary weights. We specify and estimate several alternative multivariate GARCH models for daily returns on the S&P 500 and Nasdaq indexes.
Improving Garch Volatility Forecasts
Klaassen, F.J.G.M.
1998-01-01
Many researchers use GARCH models to generate volatility forecasts. We show, however, that such forecasts are too variable. To correct for this, we extend the GARCH model by distinguishing two regimes with different volatility levels. GARCH effects are allowed within each regime, so that our model
Directory of Open Access Journals (Sweden)
Yan-Ke Du
2013-09-01
Full Text Available We study a class of discrete-time bidirectional ring neural network model with delay. We discuss the asymptotic stability of the origin and the existence of Neimark-Sacker bifurcations, by analyzing the corresponding characteristic equation. Employing M-matrix theory and the Lyapunov functional method, global asymptotic stability of the origin is derived. Applying the normal form theory and the center manifold theorem, the direction of the Neimark-Sacker bifurcation and the stability of bifurcating periodic solutions are obtained. Numerical simulations are given to illustrate the main results.
Discrete-Time Domain Modelling of Voltage Source Inverters in Standalone Applications
DEFF Research Database (Denmark)
Federico, de Bosio; de Sousa Ribeiro, Luiz Antonio; Freijedo Fernandez, Francisco Daniel
2017-01-01
modelling of the LC plant with consideration of delay and sample-and-hold effects on the state feedback cross-coupling decoupling is derived. From this plant formulation, current controllers with wide bandwidth and good relative stability properties are developed. Two controllers based on lead compensation......The decoupling of the capacitor voltage and inductor current has been shown to improve significantly the dynamic performance of voltage source inverters in standalone applications. However, the computation and PWM delays still limit the achievable bandwidth. In this paper a discrete-time domain...
Frasca, Mattia; Sharkey, Kieran J
2016-06-21
Understanding the dynamics of spread of infectious diseases between individuals is essential for forecasting the evolution of an epidemic outbreak or for defining intervention policies. The problem is addressed by many approaches including stochastic and deterministic models formulated at diverse scales (individuals, populations) and different levels of detail. Here we consider discrete-time SIR (susceptible-infectious-removed) dynamics propagated on contact networks. We derive a novel set of 'discrete-time moment equations' for the probability of the system states at the level of individual nodes and pairs of nodes. These equations form a set which we close by introducing appropriate approximations of the joint probabilities appearing in them. For the example case of SIR processes, we formulate two types of model, one assuming statistical independence at the level of individuals and one at the level of pairs. From the pair-based model we then derive a model at the level of the population which captures the behavior of epidemics on homogeneous random networks. With respect to their continuous-time counterparts, the models include a larger number of possible transitions from one state to another and joint probabilities with a larger number of individuals. The approach is validated through numerical simulation over different network topologies. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.
Models for discrete-time self-similar vector processes with application to network traffic
Lee, Seungsin; Rao, Raghuveer M.; Narasimha, Rajesh
2003-07-01
The paper defines self-similarity for vector processes by employing the discrete-time continuous-dilation operation which has successfully been used previously by the authors to define 1-D discrete-time stochastic self-similar processes. To define self-similarity of vector processes, it is required to consider the cross-correlation functions between different 1-D processes as well as the autocorrelation function of each constituent 1-D process in it. System models to synthesize self-similar vector processes are constructed based on the definition. With these systems, it is possible to generate self-similar vector processes from white noise inputs. An important aspect of the proposed models is that they can be used to synthesize various types of self-similar vector processes by choosing proper parameters. Additionally, the paper presents evidence of vector self-similarity in two-channel wireless LAN data and applies the aforementioned systems to simulate the corresponding network traffic traces.
Bifurcations in a discrete time model composed of Beverton-Holt function and Ricker function.
Shang, Jin; Li, Bingtuan; Barnard, Michael R
2015-05-01
We provide rigorous analysis for a discrete-time model composed of the Ricker function and Beverton-Holt function. This model was proposed by Lewis and Li [Bull. Math. Biol. 74 (2012) 2383-2402] in the study of a population in which reproduction occurs at a discrete instant of time whereas death and competition take place continuously during the season. We show analytically that there exists a period-doubling bifurcation curve in the model. The bifurcation curve divides the parameter space into the region of stability and the region of instability. We demonstrate through numerical bifurcation diagrams that the regions of periodic cycles are intermixed with the regions of chaos. We also study the global stability of the model. Copyright © 2015 Elsevier Inc. All rights reserved.
Stability Analysis and H∞ Model Reduction for Switched Discrete-Time Time-Delay Systems
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Zheng-Fan Liu
2014-01-01
Full Text Available This paper is concerned with the problem of exponential stability and H∞ model reduction of a class of switched discrete-time systems with state time-varying delay. Some subsystems can be unstable. Based on the average dwell time technique and Lyapunov-Krasovskii functional (LKF approach, sufficient conditions for exponential stability with H∞ performance of such systems are derived in terms of linear matrix inequalities (LMIs. For the high-order systems, sufficient conditions for the existence of reduced-order model are derived in terms of LMIs. Moreover, the error system is guaranteed to be exponentially stable and an H∞ error performance is guaranteed. Numerical examples are also given to demonstrate the effectiveness and reduced conservatism of the obtained results.
Multiple periodic solutions for a discrete time model of plankton allelopathy
Zhang Jianbao; Fang Hui
2006-01-01
We study a discrete time model of the growth of two species of plankton with competitive and allelopathic effects on each other N1(k+1) = N1(k)exp{r1(k)-a11(k)N1(k)-a12(k)N2(k)-b1(k)N1(k)N2(k)}, N2(k+1) = N2(k)exp{r2(k)-a21(k)N2(k)-b2(k)N1(k)N1(k)N2(k)}. A set of sufficient conditions is obtained for the existence of multiple positive periodic solutions for this model. The approach is based on Mawhin's continuation theorem of coincidence degree theory as well as some a priori estimates. Some...
Arnold tongues and the Devil's Staircase in a discrete-time Hindmarsh–Rose neuron model
International Nuclear Information System (INIS)
Felicio, Carolini C.; Rech, Paulo C.
2015-01-01
We investigate a three-dimensional discrete-time dynamical system, described by a three-dimensional map derived from a continuous-time Hindmarsh–Rose neuron model by the forward Euler method. For a fixed integration step size, we report a two-dimensional parameter-space for this system, where periodic structures, the so-called Arnold tongues, can be seen with periods organized in a Farey tree sequence. We also report possible modifications in this parameter-space, as a function of the integration step size. - Highlights: • We investigate the parameter-space of a particular 3D map. • Periodic structures, namely Arnold tongues, can be seen there. • They are organized in a Farey tree sequence. • The map was derived from a continuous-time Hindmarsh–Rose neuron model. • The forward Euler method was used for such purpose.
Identification of a parametric, discrete-time model of ankle stiffness.
Guarin, Diego L; Jalaleddini, Kian; Kearney, Robert E
2013-01-01
Dynamic ankle joint stiffness defines the relationship between the position of the ankle and the torque acting about it and can be separated into intrinsic and reflex components. Under stationary conditions, intrinsic stiffness can described by a linear second order system while reflex stiffness is described by Hammerstein system whose input is delayed velocity. Given that reflex and intrinsic torque cannot be measured separately, there has been much interest in the development of system identification techniques to separate them analytically. To date, most methods have been nonparametric and as a result there is no direct link between the estimated parameters and those of the stiffness model. This paper presents a novel algorithm for identification of a discrete-time model of ankle stiffness. Through simulations we show that the algorithm gives unbiased results even in the presence of large, non-white noise. Application of the method to experimental data demonstrates that it produces results consistent with previous findings.
Bayesian Non-Parametric Mixtures of GARCH(1,1 Models
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John W. Lau
2012-01-01
Full Text Available Traditional GARCH models describe volatility levels that evolve smoothly over time, generated by a single GARCH regime. However, nonstationary time series data may exhibit abrupt changes in volatility, suggesting changes in the underlying GARCH regimes. Further, the number and times of regime changes are not always obvious. This article outlines a nonparametric mixture of GARCH models that is able to estimate the number and time of volatility regime changes by mixing over the Poisson-Kingman process. The process is a generalisation of the Dirichlet process typically used in nonparametric models for time-dependent data provides a richer clustering structure, and its application to time series data is novel. Inference is Bayesian, and a Markov chain Monte Carlo algorithm to explore the posterior distribution is described. The methodology is illustrated on the Standard and Poor's 500 financial index.
Mode locking and quasiperiodicity in a discrete-time Chialvo neuron model
Wang, Fengjuan; Cao, Hongjun
2018-03-01
The two-dimensional parameter spaces of a discrete-time Chialvo neuron model are investigated. Our studies demonstrate that for all our choice of two parameters (i) the fixed point is destabilized via Neimark-Sacker bifurcation; (ii) there exist mode locking structures like Arnold tongues and shrimps, with periods organized in a Farey tree sequence, embedded in quasiperiodic/chaotic region. We determine analytically the location of the parameter sets where Neimark-Sacker bifurcation occurs, and the location on this curve where Arnold tongues of arbitrary period are born. Properties of the transition that follows the so-called two-torus from quasiperiodicity to chaos are presented clearly and proved strictly by using numerical simulations such as bifurcation diagrams, the largest Lyapunov exponent diagram on MATLAB and C++.
Estimation of value-at-risk for energy commodities via fat-tailed GARCH models
International Nuclear Information System (INIS)
Hung, Jui-Cheng; Lee, Ming-Chih; Liu, Hung-Chun
2008-01-01
The choice of an appropriate distribution for return innovations is important in VaR applications owing to its ability to directly affect the estimation quality of the required quantiles. This study investigates the influence of fat-tailed innovation process on the performance of one-day-ahead VaR estimates using three GARCH models (GARCH-N, GARCH-t and GARCH-HT). Daily spot prices of five energy commodities (WTI crude oil, Brent crude oil, heating oil 2, propane and New York Harbor Conventional Gasoline Regular) are used to compare the accuracy and efficiency of the VaR models. Empirical results suggest that for asset returns that exhibit leptokurtic and fat-tailed features, the VaR estimates generated by the GARCH-HT models have good accuracy at both low and high confidence levels. Additionally, MRSB indicates that the GARCH-HT model is more efficient than alternatives for most cases at high confidence levels. These findings suggest that the heavy-tailed distribution is more suitable for energy commodities, particularly VaR calculation. (author)
Determining the Best Arch/Garch Model and Comparing JKSE with Stock Index in Developed Countries
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Kharisya Ayu Effendi
2015-09-01
Full Text Available The slow movement of Indonesia economic growth in 2014 due to several factors, in internal factors; due to the high interest rates in Indonesia and external factors from the US which will raise the fed rate this year. However, JKSE shows a sharp increase trend from the beginning of 2014 until the second quarter of 2015 although it remains fluctuate but insignificant. The purpose of this research is to determine the best ARCH/ GARCH model in JKSE and stock index in developed countries (FTSE, Nasdaq and STI and then compare the JKSE with the stock index in developed countries (FTSE, Nasdaq and STI. The results obtained in this study is to determine the best model of ARCH / GARCH, it is obtained that JKSE is GARCH (1,2, while the FTSE obtains GARCH (2,2, NASDAQ produces the best model which is GARCH (1,1 and STI with GARCH (2,1, and the results of the comparison of JKSE with FTSE, NASDAQ and STI are that even though JKSE fluctuates with moderate levels but the trend shown upward trend. This is different with other stock indexes fluctuated highly and tends to have a downward trend.
PERBANDINGAN MODEL OPSI BLACKSCHOLES DAN MODEL OPSI GARCH DI BURSA EFEK INDONESIA
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Riko Hendrawan
2017-03-01
Full Text Available The purpose of this research was to compare the accuracy of Black-Scholes Opt ionModel and GARCH opt ion models for Stock opt ion ut ilizing data f rom Ast ra, BCA, Indofoodand Telkom at the Indonesian Stock Exchange. The intraday stock return of Astra, BCA, Indofoodand Telkom exhibited an overwhelming presence of volat ilit y cluster, suggesting that GARCHmodel had an ef fect which best corresponded with the actual price. The best model wasconst ructed using ARIMA model and the best lag in GARCH model was ext racted. The findingf rom this research showed that by comparing the average percentage mean squared errors ofthe GARCH Opt ion Model and the Black-Scholes Opt ion Model, the former was found moreaccurate than the lat ter. GARCH Model relat ively improved average percentage mean squarederrors of Black-Scholes Model; one month opt ion showed a twent y eight point ten percentimprovement , two month option showed twenty three point thirt y percent and three monthopt ion showed twent y percent .
A discrete-time Bayesian network reliability modeling and analysis framework
International Nuclear Information System (INIS)
Boudali, H.; Dugan, J.B.
2005-01-01
Dependability tools are becoming an indispensable tool for modeling and analyzing (critical) systems. However the growing complexity of such systems calls for increasing sophistication of these tools. Dependability tools need to not only capture the complex dynamic behavior of the system components, but they must be also easy to use, intuitive, and computationally efficient. In general, current tools have a number of shortcomings including lack of modeling power, incapacity to efficiently handle general component failure distributions, and ineffectiveness in solving large models that exhibit complex dependencies between their components. We propose a novel reliability modeling and analysis framework based on the Bayesian network (BN) formalism. The overall approach is to investigate timed Bayesian networks and to find a suitable reliability framework for dynamic systems. We have applied our methodology to two example systems and preliminary results are promising. We have defined a discrete-time BN reliability formalism and demonstrated its capabilities from a modeling and analysis point of view. This research shows that a BN based reliability formalism is a powerful potential solution to modeling and analyzing various kinds of system components behaviors and interactions. Moreover, being based on the BN formalism, the framework is easy to use and intuitive for non-experts, and provides a basis for more advanced and useful analyses such as system diagnosis
Modeling the exchange rate of the euro against the dollar using the ARCH/GARCH models
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Kovačević Radovan
2016-01-01
Full Text Available The analysis of time series with conditional heteroskedasticity (changeable time variability, conditional variance instability, the phenomenon called volatility is the main task of ARCH and GARCH models. The aim of these models is to calculate some of the volatility indicators needed for financial decisions. This paper examines the performance of generalized autoregressive conditional heteroscedasticity (GARCH model in modeling the daily changes of the log exchange rate of the euro against the dollar. Several GARCH models have been applied for modeling the daily log exchange rate returns of the euro, with a different number of parameters. The characteristic of estimated GARCH models is that the obtained coefficients of lagged squared residuals and the conditional variance parameters in the equation of conditional variance have a strong statistical significance. The sum of these two coefficients' estimates is close to a unit, which is typical for GARCH models that are applied on the data of financial assets returns. This means that the shocks in the conditional variance equation will be long lasting. The great value of the sum of these two coefficients shows that the high rates of positive or negative returns leads to a large forecasted value of the variance in the prolonged period. The asymmetrical EGARCH (1,1 model has showed the best results in modeling the euro exchange rate returns. The asymmetry term in the conditional variance equation of this model is negative and statistically significant. A negative value of this term suggests that the positive shock has less impact on the conditional variance than the negative shocks. The asymmetric EGARCH (1,1 model provides evidence of a leverage effect.
International Nuclear Information System (INIS)
Brianzoni, Serena; Mammana, Cristiana; Michetti, Elisabetta
2012-01-01
Highlights: ► One dimensional piecewise smooth map: border collision bifurcations. ► Numerical simulations: complex dynamics. ► Ves production function in the solow–swan growth model and comparison with the ces production function. - Abstract: We study the dynamics shown by the discrete time neoclassical one-sector growth model with differential savings as in Bohm and Kaas while assuming VES production function in the form given by Revankar . It is shown that the model can exhibit unbounded endogenous growth despite the absence of exogenous technical change and the presence of non-reproducible factors if the elasticity of substitution is greater than one. We then consider parameters range related to non-trivial dynamics (i.e. the elasticity of substitution in less than one and shareholders save more than workers) and we focus on local and global bifurcations causing the transition to more and more complex asymptotic dynamics. In particular, as our map is non-differentiable in a subset of the states space, we show that border collision bifurcations occur. Several numerical simulations support the analysis.
Financial Distress Prediction Using Discrete-time Hazard Model and Rating Transition Matrix Approach
Tsai, Bi-Huei; Chang, Chih-Huei
2009-08-01
Previous studies used constant cut-off indicator to distinguish distressed firms from non-distressed ones in the one-stage prediction models. However, distressed cut-off indicator must shift according to economic prosperity, rather than remains fixed all the time. This study focuses on Taiwanese listed firms and develops financial distress prediction models based upon the two-stage method. First, this study employs the firm-specific financial ratio and market factors to measure the probability of financial distress based on the discrete-time hazard models. Second, this paper further focuses on macroeconomic factors and applies rating transition matrix approach to determine the distressed cut-off indicator. The prediction models are developed by using the training sample from 1987 to 2004, and their levels of accuracy are compared with the test sample from 2005 to 2007. As for the one-stage prediction model, the model in incorporation with macroeconomic factors does not perform better than that without macroeconomic factors. This suggests that the accuracy is not improved for one-stage models which pool the firm-specific and macroeconomic factors together. In regards to the two stage models, the negative credit cycle index implies the worse economic status during the test period, so the distressed cut-off point is adjusted to increase based on such negative credit cycle index. After the two-stage models employ such adjusted cut-off point to discriminate the distressed firms from non-distressed ones, their error of misclassification becomes lower than that of one-stage ones. The two-stage models presented in this paper have incremental usefulness in predicting financial distress.
Persistence versus extinction for a class of discrete-time structured population models.
Jin, Wen; Smith, Hal L; Thieme, Horst R
2016-03-01
We provide sharp conditions distinguishing persistence and extinction for a class of discrete-time dynamical systems on the positive cone of an ordered Banach space generated by a map which is the sum of a positive linear contraction A and a nonlinear perturbation G that is compact and differentiable at zero in the direction of the cone. Such maps arise as year-to-year projections of population age, stage, or size-structure distributions in population biology where typically A has to do with survival and individual development and G captures the effects of reproduction. The threshold distinguishing persistence and extinction is the principal eigenvalue of (II−A)(−1)G'(0) provided by the Krein-Rutman Theorem, and persistence is described in terms of associated eigenfunctionals. Our results significantly extend earlier persistence results of the last two authors which required more restrictive conditions on G. They are illustrated by application of the results to a plant model with a seed bank.
Warren, Joshua L; Gordon-Larsen, Penny
2018-06-01
While there is a literature on the distribution of food stores across geographic and social space, much of this research uses cross-sectional data. Analyses attempting to understand whether the availability of stores across neighborhoods is associated with diet and/or health outcomes are limited by a lack of understanding of factors that shape the emergence of new stores and the closure of others. We used quarterly data on supermarket and convenience store locations spanning seven years (2006-2012) and tract-level census data in four US cities: Birmingham, Alabama; Chicago, Illinois; Minneapolis, Minnesota; San Francisco, California. A spatial discrete-time survival model was used to identify factors associated with an earlier and/or later closure time of a store. Sales volume was typically the strongest indicator of store survival. We identified heterogeneity in the association between tract-level poverty and racial composition with respect to store survival. Stores in high poverty, non-White tracts were often at a disadvantage in terms of survival length. The observed patterns of store survival varied by some of the same neighborhood sociodemographic factors associated with lifestyle and health outcomes, which could lead to confusion in interpretation in studies of the estimated effects of introduction of food stores into neighborhoods on health.
Dynamics of a two-dimensional discrete-time SIS model
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Jaime H. Barrera
2012-04-01
Full Text Available We analyze a two-dimensional discrete-time SIS model with a non-constant total population. Our goal is to determine the interaction between the total population, the susceptible class and the infective class, and the implications this may have for the disease dynamics. Utilizing a constant recruitment rate in the susceptible class, it is possible to assume the existence of an asymptotic limiting equation, which enables us to reduce the system of, two-equations into a single, dynamically equivalent equation. In this case, we are able to demonstrate the global stability of the disease-free and the endemic equilibria when the basic reproductive number (Ro is less than one and greater than one, respectively. When we consider a non-constant recruitment rate, the total population bifurcates as we vary the birth rate and the death rate. Using computer simulations, we observe different behavior among the infective class and the total population, and possibly, the occurrence of a strange attractor.
Examining School-Based Bullying Interventions Using Multilevel Discrete Time Hazard Modeling
Wagaman, M. Alex; Geiger, Jennifer Mullins; Bermudez-Parsai, Monica; Hedberg, E. C.
2014-01-01
Although schools have been trying to address bulling by utilizing different approaches that stop or reduce the incidence of bullying, little remains known about what specific intervention strategies are most successful in reducing bullying in the school setting. Using the social-ecological framework, this paper examines school-based disciplinary interventions often used to deliver consequences to deter the reoccurrence of bullying and aggressive behaviors among school-aged children. Data for this study are drawn from the School-Wide Information System (SWIS) with the final analytic sample consisting of 1,221 students in grades K – 12 who received an office disciplinary referral for bullying during the first semester. Using Kaplan-Meier Failure Functions and Multi-level discrete time hazard models, determinants of the probability of a student receiving a second referral over time were examined. Of the seven interventions tested, only Parent-Teacher Conference (AOR=0.65, pbullying and aggressive behaviors. By using a social-ecological framework, schools can develop strategies that deter the reoccurrence of bullying by identifying key factors that enhance a sense of connection between the students’ mesosystems as well as utilizing disciplinary strategies that take into consideration student’s microsystem roles. PMID:22878779
Estimating the Volatility of Cocoa Price Return with ARCH and GARCH Models
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Lya Aklimawati
2013-08-01
Full Text Available Dynamics of market changing as a result of market liberalization have an impact on agricultural commodities price fluctuation. High volatility on cocoa price movement reflect its price and market risk. Because of price and market uncertainty, the market players face some difficulties to make a decision in determining business development. This research was conducted to 1 understand the characteristics of cocoa price movement in cocoa futures trading, and 2analyze cocoa price volatility using ARCH and GARCH type model. Research was carried out by direct observation on the pattern of cocoa price movement in the futures trading and volatility analysis based on secondary data. The data was derived from Intercontinental Exchange ( ICE Futures U.S. Reports. The analysis result showed that GARCH is the best model to predict the value of average cocoa price return volatility, because it meets criteria of three diagnostic checking, which are ARCH-LM test, residual autocorrelation test and residual normality test. Based on the ARCH-LM test, GARCH (1,1did not have heteroscedasticity, because p-value 2 (0.640139and F-statistic (0.640449 were greater than 0.05. Results of residual autocorrelation test indicated that residual value of GARCH (1,1 was random, because the statistic value of Ljung-Box (LBon the 36 th lag is smaller than the statistic value of 2. Whereas, residual normality test concluded the residual of GARCH (1,1 were normally distributed, because AR (29, MA (29, RESID (-1^2, and GARCH (-1 were significant at 5% significance level. Increasing volatility value indicate high potential risk. Price risk can be reduced by managing financial instrument in futures trading such as forward and futures contract, and hedging. The research result also give an insight to the market player for decision making and determining time of hedging. Key words: Volatility, price, cocoa, GARCH, risk, futures trading
International evidence on crude oil price dynamics. Applications of ARIMA-GARCH models
International Nuclear Information System (INIS)
Mohammadi, Hassan; Su, Lixian
2010-01-01
We examine the usefulness of several ARIMA-GARCH models for modeling and forecasting the conditional mean and volatility of weekly crude oil spot prices in eleven international markets over the 1/2/1997-10/3/2009 period. In particular, we investigate the out-of-sample forecasting performance of four volatility models - GARCH, EGARCH and APARCH and FIGARCH over January 2009 to October 2009. Forecasting results are somewhat mixed, but in most cases, the APARCH model outperforms the others. Also, conditional standard deviation captures the volatility in oil returns better than the traditional conditional variance. Finally, shocks to conditional volatility dissipate at an exponential rate, which is consistent with the covariance-stationary GARCH models than the slow hyperbolic rate implied by the FIGARCH alternative. (author)
Aydiner, E.; Brunner, F.D.; Heemels, W.P.M.H.; Allgower, F.
2015-01-01
In this paper we present a robust self-triggered model predictive control (MPC) scheme for discrete-time linear time-invariant systems subject to input and state constraints and additive disturbances. In self-triggered model predictive control, at every sampling instant an optimization problem based
Preliminary analysis on hybrid Box-Jenkins - GARCH modeling in forecasting gold price
Yaziz, Siti Roslindar; Azizan, Noor Azlinna; Ahmad, Maizah Hura; Zakaria, Roslinazairimah; Agrawal, Manju; Boland, John
2015-02-01
Gold has been regarded as a valuable precious metal and the most popular commodity as a healthy return investment. Hence, the analysis and prediction of gold price become very significant to investors. This study is a preliminary analysis on gold price and its volatility that focuses on the performance of hybrid Box-Jenkins models together with GARCH in analyzing and forecasting gold price. The Box-Cox formula is used as the data transformation method due to its potential best practice in normalizing data, stabilizing variance and reduces heteroscedasticity using 41-year daily gold price data series starting 2nd January 1973. Our study indicates that the proposed hybrid model ARIMA-GARCH with t-innovation can be a new potential approach in forecasting gold price. This finding proves the strength of GARCH in handling volatility in the gold price as well as overcomes the non-linear limitation in the Box-Jenkins modeling.
Adaptive interpolation of discrete-time signals that can be modeled as autoregressive processes
Janssen, A.J.E.M.; Veldhuis, R.N.J.; Vries, L.B.
1986-01-01
The authors present an adaptive algorithm for the restoration of lost sample values in discrete-time signals that can locally be described by means of autoregressive processes. The only restrictions are that the positions of the unknown samples should be known and that they should be embedded in a
Adaptive interpolation of discrete-time signals that can be modeled as autoregressive processes
Janssen, A.J.E.M.; Veldhuis, Raymond N.J.; Vries, Lodewijk B.
1986-01-01
This paper presents an adaptive algorithm for the restoration of lost sample values in discrete-time signals that can locally be described by means of autoregressive processes. The only restrictions are that the positions of the unknown samples should be known and that they should be embedded in a
A Discrete-Time Model for Daily S&P500 Returns and Realized Variations: Jumps and Leverage Effects
DEFF Research Database (Denmark)
Bollerslev, Tim; Kretschmer, Uta; Pigorsch, Christian
We develop an empirically highly accurate discrete-time daily stochastic volatility model that explicitly distinguishes between the jump and continuoustime components of price movements using nonparametric realized variation and Bipower variation measures constructed from high-frequency intraday...... dependencies inherent in the high-frequency intraday data....
Hofstede, ter F.; Wedel, M.
1998-01-01
This study investigates the effects of time aggregation in discrete and continuous-time hazard models. A Monte Carlo study is conducted in which data are generated according to various continuous and discrete-time processes, and aggregated into daily, weekly and monthly intervals. These data are
International Nuclear Information System (INIS)
Merdan, H.; Duman, O.
2009-01-01
This paper presents the stability analysis of equilibrium points of a general discrete-time population dynamics involving predation with and without Allee effects which occur at low population density. The mathematical analysis and numerical simulations show that the Allee effect has a stabilizing role on the local stability of the positive equilibrium points of this model.
DEFF Research Database (Denmark)
Silvennoinen, Annestiina; Terasvirta, Timo
A new multivariate volatility model that belongs to the family of conditional correlation GARCH models is introduced. The GARCH equations of this model contain a multiplicative deterministic component to describe long-run movements in volatility and, in addition, the correlations...
Takaishi, Tetsuya; Chen, Ting Ting
2016-08-01
We examine the relationship between trading volumes, number of transactions, and volatility using daily stock data of the Tokyo Stock Exchange. Following the mixture of distributions hypothesis, we use trading volumes and the number of transactions as proxy for the rate of information arrivals affecting stock volatility. The impact of trading volumes or number of transactions on volatility is measured using the generalized autoregressive conditional heteroscedasticity (GARCH) model. We find that the GARCH effects, that is, persistence of volatility, is not always removed by adding trading volumes or number of transactions, indicating that trading volumes and number of transactions do not adequately represent the rate of information arrivals.
Output-Feedback Control for Discrete-Time Spreading Models in Complex Networks
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Luis A. Alarcón Ramos
2018-03-01
Full Text Available The problem of stabilizing the spreading process to a prescribed probability distribution over a complex network is considered, where the dynamics of the nodes in the network is given by discrete-time Markov-chain processes. Conditions for the positioning and identification of actuators and sensors are provided, and sufficient conditions for the exponential stability of the desired distribution are derived. Simulations results for a network of N = 10 6 corroborate our theoretical findings.
Inference and testing on the boundary in extended constant conditional correlation GARCH models
DEFF Research Database (Denmark)
Pedersen, Rasmus Søndergaard
2017-01-01
We consider inference and testing in extended constant conditional correlation GARCH models in the case where the true parameter vector is a boundary point of the parameter space. This is of particular importance when testing for volatility spillovers in the model. The large-sample properties...
Measuring the Effect of Exchange Rate Movements on Stock Market Returns Volatility: GARCH Model
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Abdelkadir BESSEBA
2017-06-01
Full Text Available This paper aims to investigate the dynamic links between exchange rate fluctuations and stock market return volatility. For this purpose, we have employed a Generalized Autoregressive Conditional Heteroscedasticity model (GARCH model. Stock market returns sensitivities are found to be stronger for exchange rates, implying that exchange rate change plays an important role in determining the dynamics of the stock market returns.
Lismawati, Eka; Respatiwulan; Widyaningsih, Purnami
2017-06-01
The SIS epidemic model describes the pattern of disease spread with characteristics that recovered individuals can be infected more than once. The number of susceptible and infected individuals every time follows the discrete time Markov process. It can be represented by the discrete time Markov chains (DTMC) SIS. The DTMC SIS epidemic model can be developed for two pathogens in two patches. The aims of this paper are to reconstruct and to apply the DTMC SIS epidemic model with two pathogens in two patches. The model was presented as transition probabilities. The application of the model obtain that the number of susceptible individuals decreases while the number of infected individuals increases for each pathogen in each patch.
On Diagnostic Checking of Vector ARMA-GARCH Models with Gaussian and Student-t Innovations
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Yongning Wang
2013-04-01
Full Text Available This paper focuses on the diagnostic checking of vector ARMA (VARMA models with multivariate GARCH errors. For a fitted VARMA-GARCH model with Gaussian or Student-t innovations, we derive the asymptotic distributions of autocorrelation matrices of the cross-product vector of standardized residuals. This is different from the traditional approach that employs only the squared series of standardized residuals. We then study two portmanteau statistics, called Q1(M and Q2(M, for model checking. A residual-based bootstrap method is provided and demonstrated as an effective way to approximate the diagnostic checking statistics. Simulations are used to compare the performance of the proposed statistics with other methods available in the literature. In addition, we also investigate the effect of GARCH shocks on checking a fitted VARMA model. Empirical sizes and powers of the proposed statistics are investigated and the results suggest a procedure of using jointly Q1(M and Q2(M in diagnostic checking. The bivariate time series of FTSE 100 and DAX index returns is used to illustrate the performance of the proposed portmanteau statistics. The results show that it is important to consider the cross-product series of standardized residuals and GARCH effects in model checking.
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Christopher D Hudson
Full Text Available The ever-growing volume of data routinely collected and stored in everyday life presents researchers with a number of opportunities to gain insight and make predictions. This study aimed to demonstrate the usefulness in a specific clinical context of a simulation-based technique called probabilistic sensitivity analysis (PSA in interpreting the results of a discrete time survival model based on a large dataset of routinely collected dairy herd management data. Data from 12,515 dairy cows (from 39 herds were used to construct a multilevel discrete time survival model in which the outcome was the probability of a cow becoming pregnant during a given two day period of risk, and presence or absence of a recorded lameness event during various time frames relative to the risk period amongst the potential explanatory variables. A separate simulation model was then constructed to evaluate the wider clinical implications of the model results (i.e. the potential for a herd's incidence rate of lameness to influence its overall reproductive performance using PSA. Although the discrete time survival analysis revealed some relatively large associations between lameness events and risk of pregnancy (for example, occurrence of a lameness case within 14 days of a risk period was associated with a 25% reduction in the risk of the cow becoming pregnant during that risk period, PSA revealed that, when viewed in the context of a realistic clinical situation, a herd's lameness incidence rate is highly unlikely to influence its overall reproductive performance to a meaningful extent in the vast majority of situations. Construction of a simulation model within a PSA framework proved to be a very useful additional step to aid contextualisation of the results from a discrete time survival model, especially where the research is designed to guide on-farm management decisions at population (i.e. herd rather than individual level.
Almeida, P.M.; Barbosa, P.G.; Duarte, J.L.; Ribeiro, P.F.
2017-01-01
This paper presents a novel comprehensive discrete-time model of a three-phase single stage grid-connected photovoltaic generation system. The detailed model is carried out on synchronous reference frame. It is shown that both converter's AC and DC-side discrete time model differs from the
Directory of Open Access Journals (Sweden)
Zongyan Li
2016-01-01
Full Text Available This paper describes an improved global harmony search (IGHS algorithm for identifying the nonlinear discrete-time systems based on second-order Volterra model. The IGHS is an improved version of the novel global harmony search (NGHS algorithm, and it makes two significant improvements on the NGHS. First, the genetic mutation operation is modified by combining normal distribution and Cauchy distribution, which enables the IGHS to fully explore and exploit the solution space. Second, an opposition-based learning (OBL is introduced and modified to improve the quality of harmony vectors. The IGHS algorithm is implemented on two numerical examples, and they are nonlinear discrete-time rational system and the real heat exchanger, respectively. The results of the IGHS are compared with those of the other three methods, and it has been verified to be more effective than the other three methods on solving the above two problems with different input signals and system memory sizes.
MODEL NON LINIER GARCH (NGARCH UNTUK MENGESTIMASI NILAI VALUE at RISK (VaR PADA IHSG
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I KOMANG TRY BAYU MAHENDRA
2015-06-01
Full Text Available In investment, risk measurement is important. One of risk measure is Value at Risk (VaR. There are many methods that can be used to estimate risk based on VaR framework. One of them Non Linier GARCH (NGARCH model. In this research, determination of VaR used NGARCH model. NGARCH model allowed for asymetric behaviour in the volatility such that “good news” or positive return and “bad news” or negative return. Based on calculations of VaR, the higher of the confidence level and the longer the investment period, the risk was greater. Determination of VaR using NGARCH model was less than GARCH model.
Alfa, Attahiru S
2016-01-01
This book introduces the theoretical fundamentals for modeling queues in discrete-time, and the basic procedures for developing queuing models in discrete-time. There is a focus on applications in modern telecommunication systems. It presents how most queueing models in discrete-time can be set up as discrete-time Markov chains. Techniques such as matrix-analytic methods (MAM) that can used to analyze the resulting Markov chains are included. This book covers single node systems, tandem system and queueing networks. It shows how queues with time-varying parameters can be analyzed, and illustrates numerical issues associated with computations for the discrete-time queueing systems. Optimal control of queues is also covered. Applied Discrete-Time Queues targets researchers, advanced-level students and analysts in the field of telecommunication networks. It is suitable as a reference book and can also be used as a secondary text book in computer engineering and computer science. Examples and exercises are includ...
Using Difference Equation to Model Discrete-time Behavior in System Dynamics Modeling
Hesan, R.; Ghorbani, A.; Dignum, M.V.
2014-01-01
In system dynamics modeling, differential equations have been used as the basic mathematical operator. Using difference equation to build system dynamics models instead of differential equation, can be insightful for studying small organizations or systems with micro behavior. In this paper we
Day-ahead electricity price forecasting using wavelet transform combined with ARIMA and GARCH models
International Nuclear Information System (INIS)
Tan, Zhongfu; Zhang, Jinliang; Xu, Jun; Wang, Jianhui
2010-01-01
This paper proposes a novel price forecasting method based on wavelet transform combined with ARIMA and GARCH models. By wavelet transform, the historical price series is decomposed and reconstructed into one approximation series and some detail series. Then each subseries can be separately predicted by a suitable time series model. The final forecast is obtained by composing the forecasted results of each subseries. This proposed method is examined on Spanish and PJM electricity markets and compared with some other forecasting methods. (author)
Modeling the stock price returns volatility using GARCH(1,1) in some Indonesia stock prices
Awalludin, S. A.; Ulfah, S.; Soro, S.
2018-01-01
In the financial field, volatility is one of the key variables to make an appropriate decision. Moreover, modeling volatility is needed in derivative pricing, risk management, and portfolio management. For this reason, this study presented a widely used volatility model so-called GARCH(1,1) for estimating the volatility of daily returns of stock prices of Indonesia from July 2007 to September 2015. The returns can be obtained from stock price by differencing log of the price from one day to the next. Parameters of the model were estimated by Maximum Likelihood Estimation. After obtaining the volatility, natural cubic spline was employed to study the behaviour of the volatility over the period. The result shows that GARCH(1,1) indicate evidence of volatility clustering in the returns of some Indonesia stock prices.
Bridge Structure Deformation Prediction Based on GNSS Data Using Kalman-ARIMA-GARCH Model.
Xin, Jingzhou; Zhou, Jianting; Yang, Simon X; Li, Xiaoqing; Wang, Yu
2018-01-19
Bridges are an essential part of the ground transportation system. Health monitoring is fundamentally important for the safety and service life of bridges. A large amount of structural information is obtained from various sensors using sensing technology, and the data processing has become a challenging issue. To improve the prediction accuracy of bridge structure deformation based on data mining and to accurately evaluate the time-varying characteristics of bridge structure performance evolution, this paper proposes a new method for bridge structure deformation prediction, which integrates the Kalman filter, autoregressive integrated moving average model (ARIMA), and generalized autoregressive conditional heteroskedasticity (GARCH). Firstly, the raw deformation data is directly pre-processed using the Kalman filter to reduce the noise. After that, the linear recursive ARIMA model is established to analyze and predict the structure deformation. Finally, the nonlinear recursive GARCH model is introduced to further improve the accuracy of the prediction. Simulation results based on measured sensor data from the Global Navigation Satellite System (GNSS) deformation monitoring system demonstrated that: (1) the Kalman filter is capable of denoising the bridge deformation monitoring data; (2) the prediction accuracy of the proposed Kalman-ARIMA-GARCH model is satisfactory, where the mean absolute error increases only from 3.402 mm to 5.847 mm with the increment of the prediction step; and (3) in comparision to the Kalman-ARIMA model, the Kalman-ARIMA-GARCH model results in superior prediction accuracy as it includes partial nonlinear characteristics (heteroscedasticity); the mean absolute error of five-step prediction using the proposed model is improved by 10.12%. This paper provides a new way for structural behavior prediction based on data processing, which can lay a foundation for the early warning of bridge health monitoring system based on sensor data using sensing
Bridge Structure Deformation Prediction Based on GNSS Data Using Kalman-ARIMA-GARCH Model
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Jingzhou Xin
2018-01-01
Full Text Available Bridges are an essential part of the ground transportation system. Health monitoring is fundamentally important for the safety and service life of bridges. A large amount of structural information is obtained from various sensors using sensing technology, and the data processing has become a challenging issue. To improve the prediction accuracy of bridge structure deformation based on data mining and to accurately evaluate the time-varying characteristics of bridge structure performance evolution, this paper proposes a new method for bridge structure deformation prediction, which integrates the Kalman filter, autoregressive integrated moving average model (ARIMA, and generalized autoregressive conditional heteroskedasticity (GARCH. Firstly, the raw deformation data is directly pre-processed using the Kalman filter to reduce the noise. After that, the linear recursive ARIMA model is established to analyze and predict the structure deformation. Finally, the nonlinear recursive GARCH model is introduced to further improve the accuracy of the prediction. Simulation results based on measured sensor data from the Global Navigation Satellite System (GNSS deformation monitoring system demonstrated that: (1 the Kalman filter is capable of denoising the bridge deformation monitoring data; (2 the prediction accuracy of the proposed Kalman-ARIMA-GARCH model is satisfactory, where the mean absolute error increases only from 3.402 mm to 5.847 mm with the increment of the prediction step; and (3 in comparision to the Kalman-ARIMA model, the Kalman-ARIMA-GARCH model results in superior prediction accuracy as it includes partial nonlinear characteristics (heteroscedasticity; the mean absolute error of five-step prediction using the proposed model is improved by 10.12%. This paper provides a new way for structural behavior prediction based on data processing, which can lay a foundation for the early warning of bridge health monitoring system based on sensor data
Estimating Price Volatility Structure in Iran’s Meat Market: Application of General GARCH Models
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Z. Rasouli Birami
2016-10-01
Full Text Available Introduction: Over the past few years, the price volatility of agricultural products and food markets has attracted attention of many researchers and policy makers. This growing attention was started from the food price crisis in 2007 and 2008 when major agricultural products faced accelerated price increases and then rapidly decreased. This paper focused on the price volatility of major commodities related to three market levels of Iran’s meat market, including hay (the input level, calf and sheep (the wholesale level and beef and mutton (the retail level. In particular, efforts will made to find more appropriate models for explaining the behavior of volatility of the return series and to identify which return series are more volatile. The effects of good and bad news on the volatility of prices in each return series will also be studied. Materials and Methods: Different GARCH type models have been considered the best for modeling volatility of return series. Nonlinear GARCH models were introduced to capture the effect of good and bad news separately. The paper uses some GARCH type models including GARCH, Exponential GARCH (EGARCH, GJR-GARCH, Threshold GARCH (TGARCH, Simple Asymmetric GARCH (SAGARCH, Power GARCH (PGARCH, Non-linear GARCH (NGARCH, Asymmetric Power GARCH (APGARCH and Non-linear Power GARCH (NPGARCH to model the volatility of hay, calf, sheep, beef and mutton return series. The data on hay, calf, sheep, and beef and mutton monthly prices are published by Iran’s livestock support firm. The paper uses monthly data over the sample period of the May 1992 to the March 2014. Results and Discussion: Descriptive statistics of the studied return series show evidence of skewness and kurtosis. The results here show that all the series has fat tails. The significant p-values for the Ljung-Box Q-statistics mean that the auto-correlation exists in the squared residuals. The presence of unit roots in the return series is confirmed by the
Directory of Open Access Journals (Sweden)
Sung Soo Kim
2016-02-01
Full Text Available We consider a discrete-time dependent Sparre Andersen risk model which incorporates multiple threshold levels characterizing an insurer’s minimal capital requirement, dividend paying situations, and external financial activities. We focus on the development of a recursive computational procedure to calculate the finite-time ruin probabilities and expected total discounted dividends paid prior to ruin associated with this model. We investigate several numerical examples and make some observations concerning the impact our threshold levels have on the finite-time ruin probabilities and expected total discounted dividends paid prior to ruin.
Forecasting the variance and return of Mexican financial series with symmetric GARCH models
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Fátima Irina VILLALBA PADILLA
2013-03-01
Full Text Available The present research shows the application of the generalized autoregresive conditional heteroskedasticity models (GARCH in order to forecast the variance and return of the IPC, the EMBI, the weighted-average government funding rate, the fix exchange rate and the Mexican oil reference, as important tools for investment decisions. Forecasts in-sample and out-of-sample are performed. The covered period involves from 2005 to 2011.
Specification and testing of Multiplicative Time-Varying GARCH models with applications
DEFF Research Database (Denmark)
Amado, Cristina; Teräsvirta, Timo
2017-01-01
In this article, we develop a specification technique for building multiplicative time-varying GARCH models of Amado and Teräsvirta (2008, 2013). The variance is decomposed into an unconditional and a conditional component such that the unconditional variance component is allowed to evolve smooth...... is illustrated in practice with two real examples: an empirical application to daily exchange rate returns and another one to daily coffee futures returns....
Hot money and China's stock market volatility: Further evidence using the GARCH-MIDAS model
Wei, Yu; Yu, Qianwen; Liu, Jing; Cao, Yang
2018-02-01
This paper investigates the influence of hot money on the return and volatility of the Chinese stock market using a nonlinear Granger causality test and a new GARCH-class model based on mixed data sampling regression (GARCH-MIDAS). The empirical results suggest that no linear or nonlinear causality exists between the growth rate of hot money and the Chinese stock market return, implying that the Chinese stock market is not driven by hot money and vice versa. However, hot money has a significant positive impact on the long-term volatility of the Chinese stock market. Furthermore, the dependence between the long-term volatility caused by hot money and the total volatility of the Chinese stock market is time-variant, indicating that huge volatilities in the stock market are not always triggered by international speculation capital flow and that Chinese authorities should further focus on more systemic reforms in the trading rules and on effectively regulating the stock market.
Modeling and forecasting the volatility of Islamic unit trust in Malaysia using GARCH model
Ismail, Nuraini; Ismail, Mohd Tahir; Karim, Samsul Ariffin Abdul; Hamzah, Firdaus Mohamad
2015-10-01
Due to the tremendous growth of Islamic unit trust in Malaysia since it was first introduced on 12th of January 1993 through the fund named Tabung Ittikal managed by Arab-Malaysian Securities, vast studies have been done to evaluate the performance of Islamic unit trust offered in Malaysia's capital market. Most of the studies found that one of the factors that affect the performance of the fund is the volatility level. Higher volatility produces better performance of the fund. Thus, we believe that a strategy must be set up by the fund managers in order for the fund to perform better. By using a series of net asset value (NAV) data of three different types of fund namely CIMB-IDEGF, CIMB-IBGF and CIMB-ISF from a fund management company named CIMB Principal Asset Management Berhad over a six years period from 1st January 2008 until 31st December 2013, we model and forecast the volatility of these Islamic unit trusts. The study found that the best fitting models for CIMB-IDEGF, CIMB-IBGF and CIMB-ISF are ARCH(4), GARCH(3,3) and GARCH(3,1) respectively. Meanwhile, the fund that is expected to be the least volatile is CIMB-IDEGF and the fund that is expected to be the most volatile is CIMB-IBGF.
Modarres, Reza; Ouarda, Taha B. M. J.; Vanasse, Alain; Orzanco, Maria Gabriela; Gosselin, Pierre
2014-07-01
Changes in extreme meteorological variables and the demographic shift towards an older population have made it important to investigate the association of climate variables and hip fracture by advanced methods in order to determine the climate variables that most affect hip fracture incidence. The nonlinear autoregressive moving average with exogenous variable-generalized autoregressive conditional heteroscedasticity (ARMA X-GARCH) and multivariate GARCH (MGARCH) time series approaches were applied to investigate the nonlinear association between hip fracture rate in female and male patients aged 40-74 and 75+ years and climate variables in the period of 1993-2004, in Montreal, Canada. The models describe 50-56 % of daily variation in hip fracture rate and identify snow depth, air temperature, day length and air pressure as the influencing variables on the time-varying mean and variance of the hip fracture rate. The conditional covariance between climate variables and hip fracture rate is increasing exponentially, showing that the effect of climate variables on hip fracture rate is most acute when rates are high and climate conditions are at their worst. In Montreal, climate variables, particularly snow depth and air temperature, appear to be important predictors of hip fracture incidence. The association of climate variables and hip fracture does not seem to change linearly with time, but increases exponentially under harsh climate conditions. The results of this study can be used to provide an adaptive climate-related public health program and ti guide allocation of services for avoiding hip fracture risk.
Disease-induced mortality in density-dependent discrete-time S-I-S epidemic models.
Franke, John E; Yakubu, Abdul-Aziz
2008-12-01
The dynamics of simple discrete-time epidemic models without disease-induced mortality are typically characterized by global transcritical bifurcation. We prove that in corresponding models with disease-induced mortality a tiny number of infectious individuals can drive an otherwise persistent population to extinction. Our model with disease-induced mortality supports multiple attractors. In addition, we use a Ricker recruitment function in an SIS model and obtained a three component discrete Hopf (Neimark-Sacker) cycle attractor coexisting with a fixed point attractor. The basin boundaries of the coexisting attractors are fractal in nature, and the example exhibits sensitive dependence of the long-term disease dynamics on initial conditions. Furthermore, we show that in contrast to corresponding models without disease-induced mortality, the disease-free state dynamics do not drive the disease dynamics.
Zakary, Omar; Rachik, Mostafa; Elmouki, Ilias
2017-08-01
First, we devise in this paper, a multi-regions discrete-time model which describes the spatial-temporal spread of an epidemic which starts from one region and enters to regions which are connected with their neighbors by any kind of anthropological movement. We suppose homogeneous Susceptible-Infected-Removed (SIR) populations, and we consider in our simulations, a grid of colored cells, which represents the whole domain affected by the epidemic while each cell can represent a sub-domain or region. Second, in order to minimize the number of infected individuals in one region, we propose an optimal control approach based on a travel-blocking vicinity strategy which aims to control only one cell by restricting movements of infected people coming from all neighboring cells. Thus, we show the influence of the optimal control approach on the controlled cell. We should also note that the cellular modeling approach we propose here, can also describes infection dynamics of regions which are not necessarily attached one to an other, even if no empty space can be viewed between cells. The theoretical method we follow for the characterization of the travel-locking optimal controls, is based on a discrete version of Pontryagin's maximum principle while the numerical approach applied to the multi-points boundary value problems we obtain here, is based on discrete progressive-regressive iterative schemes. We illustrate our modeling and control approaches by giving an example of 100 regions.
Kouramas, K.I.; Faí sca, N.P.; Panos, C.; Pistikopoulos, E.N.
2011-01-01
This work presents a new algorithm for solving the explicit/multi- parametric model predictive control (or mp-MPC) problem for linear, time-invariant discrete-time systems, based on dynamic programming and multi-parametric programming techniques
Global Risk Evolution and Diversification: a Copula-DCC-GARCH Model Approach
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Marcelo Brutti Righi
2012-12-01
Full Text Available In this paper we estimate a dynamic portfolio composed by the U.S., German, British, Brazilian, Hong Kong and Australian markets, the period considered started on September 2001 and finished in September 2011. We ran the Copula-DCC-GARCH model on the daily returns conditional covariance matrix. The results allow us to conclude that there were changes in portfolio composition, occasioned by modifications in volatility and dependence between markets. The dynamic approach significantly reduced the portfolio risk if compared to the traditional static approach, especially in turbulent periods. Furthermore, we verified that the estimated copula model outperformed the conventional DCC model for the sample studied.
American Option Pricing using GARCH models and the Normal Inverse Gaussian distribution
DEFF Research Database (Denmark)
Stentoft, Lars Peter
In this paper we propose a feasible way to price American options in a model with time varying volatility and conditional skewness and leptokurtosis using GARCH processes and the Normal Inverse Gaussian distribution. We show how the risk neutral dynamics can be obtained in this model, we interpret...... properties shows that there are important option pricing differences compared to the Gaussian case as well as to the symmetric special case. A large scale empirical examination shows that our model outperforms the Gaussian case for pricing options on three large US stocks as well as a major index...
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Andreea – Cristina PETRICĂ
2017-03-01
Full Text Available The aim of this study consists in examining the changes in the volatility of daily returns of EUR/RON exchange rate using on the one hand symmetric GARCH models (ARCH and GARCH and on the other hand the asymmetric GARCH models (EGARCH, TARCH and PARCH, since the conditional variance is time-varying. The analysis takes into account daily quotations of EUR/RON exchange rate over the period of 04th January 1999 to 13th June 2016. Thus, we are modeling heteroscedasticity by applying different specifications of GARCH models followed by looking for significant parameters and low information criteria (minimum Akaike Information Criterion. All models are estimated using the maximum likelihood method under the assumption of several distributions of the innovation terms such as: Normal (Gaussian distribution, Student’s t distribution, Generalized Error distribution (GED, Student’s with fixed df. Distribution, and GED with fixed parameter distribution. The predominant models turned out to be EGARCH and PARCH models, and the empirical results point out that the best model for estimating daily returns of EUR/RON exchange rate is EGARCH(2,1 with Asymmetric order 2 under the assumption of Student’s t distributed innovation terms. This can be explained by the fact that in case of EGARCH model, the restriction regarding the positivity of the conditional variance is automatically satisfied.
Multivariate Variance Targeting in the BEKK-GARCH Model
DEFF Research Database (Denmark)
Pedersen, Rasmus Søndergaard; Rahbek, Anders
This paper considers asymptotic inference in the multivariate BEKK model based on (co-)variance targeting (VT). By de…nition the VT estimator is a two-step estimator and the theory presented is based on expansions of the modi…ed like- lihood function, or estimating function, corresponding...
Multivariate Variance Targeting in the BEKK-GARCH Model
DEFF Research Database (Denmark)
Pedersen, Rasmus Søndergaard; Rahbek, Anders
2014-01-01
This paper considers asymptotic inference in the multivariate BEKK model based on (co-)variance targeting (VT). By definition the VT estimator is a two-step estimator and the theory presented is based on expansions of the modified likelihood function, or estimating function, corresponding...
Multivariate Variance Targeting in the BEKK-GARCH Model
DEFF Research Database (Denmark)
Pedersen, Rasmus Søndergaard; Rahbek, Anders
This paper considers asymptotic inference in the multivariate BEKK model based on (co-)variance targeting (VT). By de…nition the VT estimator is a two-step estimator and the theory presented is based on expansions of the modi…ed likelihood function, or estimating function, corresponding...
Arnold tongues and the Devil's Staircase in a discrete-time Hindmarsh–Rose neuron model
Energy Technology Data Exchange (ETDEWEB)
Felicio, Carolini C., E-mail: carolini.cf@gmail.com; Rech, Paulo C., E-mail: paulo.rech@udesc.br
2015-11-06
We investigate a three-dimensional discrete-time dynamical system, described by a three-dimensional map derived from a continuous-time Hindmarsh–Rose neuron model by the forward Euler method. For a fixed integration step size, we report a two-dimensional parameter-space for this system, where periodic structures, the so-called Arnold tongues, can be seen with periods organized in a Farey tree sequence. We also report possible modifications in this parameter-space, as a function of the integration step size. - Highlights: • We investigate the parameter-space of a particular 3D map. • Periodic structures, namely Arnold tongues, can be seen there. • They are organized in a Farey tree sequence. • The map was derived from a continuous-time Hindmarsh–Rose neuron model. • The forward Euler method was used for such purpose.
Simulating Serious Games: A Discrete-Time Computational Model Based on Cognitive Flow Theory
Westera, Wim
2018-01-01
This paper presents a computational model for simulating how people learn from serious games. While avoiding the combinatorial explosion of a games micro-states, the model offers a meso-level pathfinding approach, which is guided by cognitive flow theory and various concepts from learning sciences. It extends a basic, existing model by exposing…
Ruin Probabilities in a Dependent Discrete-Time Risk Model With Gamma-Like Tailed Insurance Risks
Directory of Open Access Journals (Sweden)
Xing-Fang Huang
2017-03-01
Full Text Available This paper considered a dependent discrete-time risk model, in which the insurance risks are represented by a sequence of independent and identically distributed real-valued random variables with a common Gamma-like tailed distribution; the ﬁnancial risks are denoted by another sequence of independent and identically distributed positive random variables with a ﬁnite upper endpoint, but a general dependence structure exists between each pair of the insurance risks and the ﬁnancial risks. Following the works of Yang and Yuen in 2016, we derive some asymptotic relations for the ﬁnite-time and inﬁnite-time ruin probabilities. As a complement, we demonstrate our obtained result through a Crude Monte Carlo (CMC simulation with asymptotics.
Targeting estimation of CCC-GARCH models with infinite fourth moments
DEFF Research Database (Denmark)
Pedersen, Rasmus Søndergaard
. In this paper we consider the large-sample properties of the variance targeting estimator for the multivariate extended constant conditional correlation GARCH model when the distribution of the data generating process has infinite fourth moments. Using non-standard limit theory we derive new results...... for the estimator stating that its limiting distribution is multivariate stable. The rate of consistency of the estimator is slower than √Τ (as obtained by the quasi-maximum likelihood estimator) and depends on the tails of the data generating process....
Discrete-time semi-Markov modeling of human papillomavirus persistence
Mitchell, C. E.; Hudgens, M. G.; King, C. C.; Cu-Uvin, S.; Lo, Y.; Rompalo, A.; Sobel, J.; Smith, J. S.
2011-01-01
Multi-state modeling is often employed to describe the progression of a disease process. In epidemiological studies of certain diseases, the disease state is typically only observed at periodic clinical visits, producing incomplete longitudinal data. In this paper we consider fitting semi-Markov models to estimate the persistence of human papillomavirus (HPV) type-specific infection in studies where the status of HPV type(s) is assessed periodically. Simulation study results are presented indicating the semi-Markov estimator is more accurate than an estimator currently used in the HPV literature. The methods are illustrated using data from the HIV Epidemiology Research Study (HERS). PMID:21538985
Three-dimensional discrete-time Lotka-Volterra models with an application to industrial clusters
Bischi, G. I.; Tramontana, F.
2010-10-01
We consider a three-dimensional discrete dynamical system that describes an application to economics of a generalization of the Lotka-Volterra prey-predator model. The dynamic model proposed is used to describe the interactions among industrial clusters (or districts), following a suggestion given by [23]. After studying some local and global properties and bifurcations in bidimensional Lotka-Volterra maps, by numerical explorations we show how some of them can be extended to their three-dimensional counterparts, even if their analytic and geometric characterization becomes much more difficult and challenging. We also show a global bifurcation of the three-dimensional system that has no two-dimensional analogue. Besides the particular economic application considered, the study of the discrete version of Lotka-Volterra dynamical systems turns out to be a quite rich and interesting topic by itself, i.e. from a purely mathematical point of view.
Finite approximations in discrete-time stochastic control quantized models and asymptotic optimality
Saldi, Naci; Yüksel, Serdar
2018-01-01
In a unified form, this monograph presents fundamental results on the approximation of centralized and decentralized stochastic control problems, with uncountable state, measurement, and action spaces. It demonstrates how quantization provides a system-independent and constructive method for the reduction of a system with Borel spaces to one with finite state, measurement, and action spaces. In addition to this constructive view, the book considers both the information transmission approach for discretization of actions, and the computational approach for discretization of states and actions. Part I of the text discusses Markov decision processes and their finite-state or finite-action approximations, while Part II builds from there to finite approximations in decentralized stochastic control problems. This volume is perfect for researchers and graduate students interested in stochastic controls. With the tools presented, readers will be able to establish the convergence of approximation models to original mo...
Indian Academy of Sciences (India)
We also describe discrete-time systems in terms of difference ... A more modern alternative, especially for larger systems, is to convert ... In other words, ..... picture?) State-variable equations are also called state-space equations because the ...
Modelling of cayenne production in Central Java using ARIMA-GARCH
Tarno; Sudarno; Ispriyanti, Dwi; Suparti
2018-05-01
Some regencies/cities in Central Java Province are known as producers of horticultural crops in Indonesia, for example, Brebes which is the largest area of shallot producer in Central Java, while the others, such as Cilacap and Wonosobo are the areas of cayenne commodities production. Currently, cayenne is a strategic commodity and it has broad impact to Indonesian economic development. Modelling the cayenne production is necessary to predict about the commodity to meet the need for society. The needs fulfillment of society will affect stability of the concerned commodity price. Based on the reality, the decreasing of cayenne production will cause the increasing of society’s basic needs price, and finally it will affect the inflation level at that area. This research focused on autoregressive integrated moving average (ARIMA) modelling by considering the effect of autoregressive conditional heteroscedasticity (ARCH) to study about cayenne production in Central Java. The result of empirical study of ARIMA-GARCH modelling for cayenne production in Central Java from January 2003 to November 2015 is ARIMA([1,3],0,0)-GARCH(1,0) as the best model.
Estimating Risk of Natural Gas Portfolios by Using GARCH-EVT-Copula Model.
Tang, Jiechen; Zhou, Chao; Yuan, Xinyu; Sriboonchitta, Songsak
2015-01-01
This paper concentrates on estimating the risk of Title Transfer Facility (TTF) Hub natural gas portfolios by using the GARCH-EVT-copula model. We first use the univariate ARMA-GARCH model to model each natural gas return series. Second, the extreme value distribution (EVT) is fitted to the tails of the residuals to model marginal residual distributions. Third, multivariate Gaussian copula and Student t-copula are employed to describe the natural gas portfolio risk dependence structure. Finally, we simulate N portfolios and estimate value at risk (VaR) and conditional value at risk (CVaR). Our empirical results show that, for an equally weighted portfolio of five natural gases, the VaR and CVaR values obtained from the Student t-copula are larger than those obtained from the Gaussian copula. Moreover, when minimizing the portfolio risk, the optimal natural gas portfolio weights are found to be similar across the multivariate Gaussian copula and Student t-copula and different confidence levels.
Estimating Risk of Natural Gas Portfolios by Using GARCH-EVT-Copula Model
Directory of Open Access Journals (Sweden)
Jiechen Tang
2015-01-01
Full Text Available This paper concentrates on estimating the risk of Title Transfer Facility (TTF Hub natural gas portfolios by using the GARCH-EVT-copula model. We first use the univariate ARMA-GARCH model to model each natural gas return series. Second, the extreme value distribution (EVT is fitted to the tails of the residuals to model marginal residual distributions. Third, multivariate Gaussian copula and Student t-copula are employed to describe the natural gas portfolio risk dependence structure. Finally, we simulate N portfolios and estimate value at risk (VaR and conditional value at risk (CVaR. Our empirical results show that, for an equally weighted portfolio of five natural gases, the VaR and CVaR values obtained from the Student t-copula are larger than those obtained from the Gaussian copula. Moreover, when minimizing the portfolio risk, the optimal natural gas portfolio weights are found to be similar across the multivariate Gaussian copula and Student t-copula and different confidence levels.
Modeling inflation rates and exchange rates in Ghana: application of multivariate GARCH models.
Nortey, Ezekiel Nn; Ngoh, Delali D; Doku-Amponsah, Kwabena; Ofori-Boateng, Kenneth
2015-01-01
This paper was aimed at investigating the volatility and conditional relationship among inflation rates, exchange rates and interest rates as well as to construct a model using multivariate GARCH DCC and BEKK models using Ghana data from January 1990 to December 2013. The study revealed that the cumulative depreciation of the cedi to the US dollar from 1990 to 2013 is 7,010.2% and the yearly weighted depreciation of the cedi to the US dollar for the period is 20.4%. There was evidence that, the fact that inflation rate was stable, does not mean that exchange rates and interest rates are expected to be stable. Rather, when the cedi performs well on the forex, inflation rates and interest rates react positively and become stable in the long run. The BEKK model is robust to modelling and forecasting volatility of inflation rates, exchange rates and interest rates. The DCC model is robust to model the conditional and unconditional correlation among inflation rates, exchange rates and interest rates. The BEKK model, which forecasted high exchange rate volatility for the year 2014, is very robust for modelling the exchange rates in Ghana. The mean equation of the DCC model is also robust to forecast inflation rates in Ghana.
QR-GARCH-M Model for Risk-Return Tradeoff in U.S. Stock Returns and Business Cycles
Nyberg, Henri
2010-01-01
In the empirical finance literature findings on the risk return tradeoff in excess stock market returns are ambiguous. In this study, we develop a new QR-GARCH-M model combining a probit model for a binary business cycle indicator and a regime switching GARCH-in-mean model for excess stock market return with the business cycle indicator defining the regime. Estimation results show that there is statistically significant variation in the U.S. excess stock returns over the business cycle. Howev...
The effects of host-feeding on stability of discrete-time host-parasitoid population dynamic models.
Emerick, Brooks; Singh, Abhyudai
2016-02-01
Discrete-time models are the traditional approach for capturing population dynamics of a host-parasitoid system. Recent work has introduced a semi-discrete framework for obtaining model update functions that connect host-parasitoid population levels from year-to-year. In particular, this framework uses differential equations to describe the host-parasitoid interaction during the time of year when they come in contact, allowing specific behaviors to be mechanistically incorporated. We use the semi-discrete approach to study the effects of host-feeding, which occurs when a parasitoid consumes a potential host larva without ovipositing. We find that host-feeding by itself cannot stabilize the system, and both populations exhibit behavior similar to the Nicholson-Bailey model. However, when combined with stabilizing mechanisms such as density-dependent host mortality, host-feeding contracts the region of parameter space that allows for a stable host-parasitoid equilibrium. In contrast, when combined with a density-dependent parasitoid attack rate, host-feeding expands the non-zero equilibrium stability region. Our results show that host-feeding causes inefficiency in the parasitoid population, which yields a higher population of hosts per generation. This suggests that host-feeding may have limited long-term impact in terms of suppressing host levels for biological control applications. Copyright © 2015 Elsevier Inc. All rights reserved.
DEFF Research Database (Denmark)
Amado, Cristina; Teräsvirta, Timo
-run and the short-run dynamic behaviour of the volatilities. The structure of the conditional correlation matrix is assumed to be either time independent or to vary over time. We apply our model to pairs of seven daily stock returns belonging to the S&P 500 composite index and traded at the New York Stock Exchange......In this paper we investigate the effects of careful modelling the long-run dynamics of the volatilities of stock market returns on the conditional correlation structure. To this end we allow the individual unconditional variances in Conditional Correlation GARCH models to change smoothly over time...... by incorporating a nonstationary component in the variance equations. The modelling technique to determine the parametric structure of this time-varying component is based on a sequence of specification Lagrange multiplier-type tests derived in Amado and Teräsvirta (2011). The variance equations combine the long...
Directory of Open Access Journals (Sweden)
Rafał Stanisławski
2016-01-01
Full Text Available This paper presents new results on modeling and analysis of dynamics of fractional-order discrete-time linear time-invariant single-input single-output (LTI SISO systems by means of new, two-layer, “fractional-order discrete-time Laguerre filters.” It is interesting that the fractionality of the filters at the upper system dynamics layer is directly projected from the lower Laguerre-based approximation layer for the Grünwald-Letnikov difference. A new stability criterion for discrete-time fractional-order Laguerre-based LTI SISO systems is introduced and supplemented with a stability preservation analysis. Both the stability criterion and the stability preservation analysis bring up rather surprising results, which is illustrated with simulation examples.
International Nuclear Information System (INIS)
Guengoer, N.
1999-05-01
In this study, 134 Cs and 241 Am biokinetic experiments have been observed originally for Black Sea condition with using the gastropod Patella coerulea and the macro algae Enteremorpha linza and the common mussel Mytilus galloprovlncialis as bio indicator organisms. The experiments that have at least three originality, have been carried out very carefully and biokinetic parameters have been calculated by using classical model. The results are compared with the proportionally similar experiments in the literature globally. In this thesis, a new model application has proposed for the biokinetic evaluation for loss experiments of organisms. That is discrete time model. Loss experiments can be evaluated proportionally in a quick and easy way by using this model. Then, it can be observed that the calculated decreasing factor (r) by discrete time model, shows the loss process quality. Moreover, the loss experiments can be stopped when the decreasing factor goes to 1. So, the loss experiment can be evaluated rapidly and quickly with the adequate reliability by using discrete time model. Furthermore, the loss process in the organisms becomes slower and biologic half-lives becomes longer, when the decreasing factor (r) goes to 1. On the other hand, the biological depuration rate (k) goes to nearly zero. So, the proposed discrete time model that is applied in this thesis originally for biokinetic, can be evident that it has an adequate reliability for the biokinetic evaluation
Probabilistic forecasting of the solar irradiance with recursive ARMA and GARCH models
DEFF Research Database (Denmark)
David, M.; Ramahatana, F.; Trombe, Pierre-Julien
2016-01-01
Forecasting of the solar irradiance is a key feature in order to increase the penetration rate of solar energy into the energy grids. Indeed, the anticipation of the fluctuations of the solar renewables allows a better management of the production means of electricity and a better operation...... sky index show some similarities with that of financial time series. The aim of this paper is to assess the performances of a commonly used combination of two linear models (ARMA and GARCH) in econometrics in order to provide probabilistic forecasts of solar irradiance. In addition, a recursive...... regarding the statistical distribution of the error, the reliability of the probabilistic forecasts stands in the same order of magnitude as other works done in the field of solar forecasting....
Guay, M.; Beerens, R.; Nijmeijer, H.
2014-01-01
This paper considers the solution of a real-time optimization problem using adaptive extremum seeking control for a class of unknown discrete-time nonlinear systems. It is assumed that the equations describing the dynamics of the nonlinear system and the cost function to be minimized are unknown and
Prediction of selected Indian stock using a partitioning–interpolation based ARIMA–GARCH model
Directory of Open Access Journals (Sweden)
C. Narendra Babu
2015-07-01
Full Text Available Accurate long-term prediction of time series data (TSD is a very useful research challenge in diversified fields. As financial TSD are highly volatile, multi-step prediction of financial TSD is a major research problem in TSD mining. The two challenges encountered are, maintaining high prediction accuracy and preserving the data trend across the forecast horizon. The linear traditional models such as autoregressive integrated moving average (ARIMA and generalized autoregressive conditional heteroscedastic (GARCH preserve data trend to some extent, at the cost of prediction accuracy. Non-linear models like ANN maintain prediction accuracy by sacrificing data trend. In this paper, a linear hybrid model, which maintains prediction accuracy while preserving data trend, is proposed. A quantitative reasoning analysis justifying the accuracy of proposed model is also presented. A moving-average (MA filter based pre-processing, partitioning and interpolation (PI technique are incorporated by the proposed model. Some existing models and the proposed model are applied on selected NSE India stock market data. Performance results show that for multi-step ahead prediction, the proposed model outperforms the others in terms of both prediction accuracy and preserving data trend.
Zhang, Zhen; Yan, Peng; Jiang, Huan; Ye, Peiqing
2014-09-01
In this paper, we consider the discrete time-varying internal model-based control design for high precision tracking of complicated reference trajectories generated by time-varying systems. Based on a novel parallel time-varying internal model structure, asymptotic tracking conditions for the design of internal model units are developed, and a low order robust time-varying stabilizer is further synthesized. In a discrete time setting, the high precision tracking control architecture is deployed on a Voice Coil Motor (VCM) actuated servo gantry system, where numerical simulations and real time experimental results are provided, achieving the tracking errors around 3.5‰ for frequency-varying signals. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.
Browne, William J; Steele, Fiona; Golalizadeh, Mousa; Green, Martin J
2009-06-01
We consider the application of Markov chain Monte Carlo (MCMC) estimation methods to random-effects models and in particular the family of discrete time survival models. Survival models can be used in many situations in the medical and social sciences and we illustrate their use through two examples that differ in terms of both substantive area and data structure. A multilevel discrete time survival analysis involves expanding the data set so that the model can be cast as a standard multilevel binary response model. For such models it has been shown that MCMC methods have advantages in terms of reducing estimate bias. However, the data expansion results in very large data sets for which MCMC estimation is often slow and can produce chains that exhibit poor mixing. Any way of improving the mixing will result in both speeding up the methods and more confidence in the estimates that are produced. The MCMC methodological literature is full of alternative algorithms designed to improve mixing of chains and we describe three reparameterization techniques that are easy to implement in available software. We consider two examples of multilevel survival analysis: incidence of mastitis in dairy cattle and contraceptive use dynamics in Indonesia. For each application we show where the reparameterization techniques can be used and assess their performance.
Energy Technology Data Exchange (ETDEWEB)
Vanderbei, Robert J., E-mail: rvdb@princeton.edu [Princeton University, Department of Operations Research and Financial Engineering (United States); P Latin-Small-Letter-Dotless-I nar, Mustafa C., E-mail: mustafap@bilkent.edu.tr [Bilkent University, Department of Industrial Engineering (Turkey); Bozkaya, Efe B. [Sabanc Latin-Small-Letter-Dotless-I University, Faculty of Administrative Sciences (Turkey)
2013-02-15
An American option (or, warrant) is the right, but not the obligation, to purchase or sell an underlying equity at any time up to a predetermined expiration date for a predetermined amount. A perpetual American option differs from a plain American option in that it does not expire. In this study, we solve the optimal stopping problem of a perpetual American option (both call and put) in discrete time using linear programming duality. Under the assumption that the underlying stock price follows a discrete time and discrete state Markov process, namely a geometric random walk, we formulate the pricing problem as an infinite dimensional linear programming (LP) problem using the excessive-majorant property of the value function. This formulation allows us to solve complementary slackness conditions in closed-form, revealing an optimal stopping strategy which highlights the set of stock-prices where the option should be exercised. The analysis for the call option reveals that such a critical value exists only in some cases, depending on a combination of state-transition probabilities and the economic discount factor (i.e., the prevailing interest rate) whereas it ceases to be an issue for the put.
International Nuclear Information System (INIS)
Vanderbei, Robert J.; Pınar, Mustafa Ç.; Bozkaya, Efe B.
2013-01-01
An American option (or, warrant) is the right, but not the obligation, to purchase or sell an underlying equity at any time up to a predetermined expiration date for a predetermined amount. A perpetual American option differs from a plain American option in that it does not expire. In this study, we solve the optimal stopping problem of a perpetual American option (both call and put) in discrete time using linear programming duality. Under the assumption that the underlying stock price follows a discrete time and discrete state Markov process, namely a geometric random walk, we formulate the pricing problem as an infinite dimensional linear programming (LP) problem using the excessive-majorant property of the value function. This formulation allows us to solve complementary slackness conditions in closed-form, revealing an optimal stopping strategy which highlights the set of stock-prices where the option should be exercised. The analysis for the call option reveals that such a critical value exists only in some cases, depending on a combination of state-transition probabilities and the economic discount factor (i.e., the prevailing interest rate) whereas it ceases to be an issue for the put.
Mehdizadeh, Saeid; Behmanesh, Javad; Khalili, Keivan
2017-11-01
Precipitation plays an important role in determining the climate of a region. Precise estimation of precipitation is required to manage and plan water resources, as well as other related applications such as hydrology, climatology, meteorology and agriculture. Time series of hydrologic variables such as precipitation are composed of deterministic and stochastic parts. Despite this fact, the stochastic part of the precipitation data is not usually considered in modeling of precipitation process. As an innovation, the present study introduces three new hybrid models by integrating soft computing methods including multivariate adaptive regression splines (MARS), Bayesian networks (BN) and gene expression programming (GEP) with a time series model, namely generalized autoregressive conditional heteroscedasticity (GARCH) for modeling of the monthly precipitation. For this purpose, the deterministic (obtained by soft computing methods) and stochastic (obtained by GARCH time series model) parts are combined with each other. To carry out this research, monthly precipitation data of Babolsar, Bandar Anzali, Gorgan, Ramsar, Tehran and Urmia stations with different climates in Iran were used during the period of 1965-2014. Root mean square error (RMSE), relative root mean square error (RRMSE), mean absolute error (MAE) and determination coefficient (R2) were employed to evaluate the performance of conventional/single MARS, BN and GEP, as well as the proposed MARS-GARCH, BN-GARCH and GEP-GARCH hybrid models. It was found that the proposed novel models are more precise than single MARS, BN and GEP models. Overall, MARS-GARCH and BN-GARCH models yielded better accuracy than GEP-GARCH. The results of the present study confirmed the suitability of proposed methodology for precise modeling of precipitation.
Principles of discrete time mechanics
Jaroszkiewicz, George
2014-01-01
Could time be discrete on some unimaginably small scale? Exploring the idea in depth, this unique introduction to discrete time mechanics systematically builds the theory up from scratch, beginning with the historical, physical and mathematical background to the chronon hypothesis. Covering classical and quantum discrete time mechanics, this book presents all the tools needed to formulate and develop applications of discrete time mechanics in a number of areas, including spreadsheet mechanics, classical and quantum register mechanics, and classical and quantum mechanics and field theories. A consistent emphasis on contextuality and the observer-system relationship is maintained throughout.
Stochastic GARCH dynamics describing correlations between stocks
Prat-Ortega, G.; Savel'ev, S. E.
2014-09-01
The ARCH and GARCH processes have been successfully used for modelling price dynamics such as stock returns or foreign exchange rates. Analysing the long range correlations between stocks, we propose a model, based on the GARCH process, which is able to describe the main characteristics of the stock price correlations, including the mean, variance, probability density distribution and the noise spectrum.
Directory of Open Access Journals (Sweden)
Nishiura Hiroshi
2011-02-01
Full Text Available Abstract Background Real-time forecasting of epidemics, especially those based on a likelihood-based approach, is understudied. This study aimed to develop a simple method that can be used for the real-time epidemic forecasting. Methods A discrete time stochastic model, accounting for demographic stochasticity and conditional measurement, was developed and applied as a case study to the weekly incidence of pandemic influenza (H1N1-2009 in Japan. By imposing a branching process approximation and by assuming the linear growth of cases within each reporting interval, the epidemic curve is predicted using only two parameters. The uncertainty bounds of the forecasts are computed using chains of conditional offspring distributions. Results The quality of the forecasts made before the epidemic peak appears largely to depend on obtaining valid parameter estimates. The forecasts of both weekly incidence and final epidemic size greatly improved at and after the epidemic peak with all the observed data points falling within the uncertainty bounds. Conclusions Real-time forecasting using the discrete time stochastic model with its simple computation of the uncertainty bounds was successful. Because of the simplistic model structure, the proposed model has the potential to additionally account for various types of heterogeneity, time-dependent transmission dynamics and epidemiological details. The impact of such complexities on forecasting should be explored when the data become available as part of the disease surveillance.
Hybrid discrete-time neural networks.
Cao, Hongjun; Ibarz, Borja
2010-11-13
Hybrid dynamical systems combine evolution equations with state transitions. When the evolution equations are discrete-time (also called map-based), the result is a hybrid discrete-time system. A class of biological neural network models that has recently received some attention falls within this category: map-based neuron models connected by means of fast threshold modulation (FTM). FTM is a connection scheme that aims to mimic the switching dynamics of a neuron subject to synaptic inputs. The dynamic equations of the neuron adopt different forms according to the state (either firing or not firing) and type (excitatory or inhibitory) of their presynaptic neighbours. Therefore, the mathematical model of one such network is a combination of discrete-time evolution equations with transitions between states, constituting a hybrid discrete-time (map-based) neural network. In this paper, we review previous work within the context of these models, exemplifying useful techniques to analyse them. Typical map-based neuron models are low-dimensional and amenable to phase-plane analysis. In bursting models, fast-slow decomposition can be used to reduce dimensionality further, so that the dynamics of a pair of connected neurons can be easily understood. We also discuss a model that includes electrical synapses in addition to chemical synapses with FTM. Furthermore, we describe how master stability functions can predict the stability of synchronized states in these networks. The main results are extended to larger map-based neural networks.
Noise sensitivity of portfolio selection in constant conditional correlation GARCH models
Varga-Haszonits, I.; Kondor, I.
2007-11-01
This paper investigates the efficiency of minimum variance portfolio optimization for stock price movements following the Constant Conditional Correlation GARCH process proposed by Bollerslev. Simulations show that the quality of portfolio selection can be improved substantially by computing optimal portfolio weights from conditional covariances instead of unconditional ones. Measurement noise can be further reduced by applying some filtering method on the conditional correlation matrix (such as Random Matrix Theory based filtering). As an empirical support for the simulation results, the analysis is also carried out for a time series of S&P500 stock prices.
Relan, Rishi; Tiels, Koen; Marconato, Anna; Dreesen, Philippe; Schoukens, Johan
2018-05-01
Many real world systems exhibit a quasi linear or weakly nonlinear behavior during normal operation, and a hard saturation effect for high peaks of the input signal. In this paper, a methodology to identify a parsimonious discrete-time nonlinear state space model (NLSS) for the nonlinear dynamical system with relatively short data record is proposed. The capability of the NLSS model structure is demonstrated by introducing two different initialisation schemes, one of them using multivariate polynomials. In addition, a method using first-order information of the multivariate polynomials and tensor decomposition is employed to obtain the parsimonious decoupled representation of the set of multivariate real polynomials estimated during the identification of NLSS model. Finally, the experimental verification of the model structure is done on the cascaded water-benchmark identification problem.
GARCH and Irregularly Spaced Data
Meddahi, N.; Renault, E.; Werker, B.J.M.
2003-01-01
An exact discretization of continuous time stochastic volatility processes observed at irregularly spaced times is used to give insights on how a coherent GARCH model can be specified for such data. The relation of our approach with those in the existing literature is studied.
Time-aggregation effects on the baseline of continuous-time and discrete-time hazard models
ter Hofstede, F.; Wedel, M.
In this study we reinvestigate the effect of time-aggregation for discrete- and continuous-time hazard models. We reanalyze the results of a previous Monte Carlo study by ter Hofstede and Wedel (1998), in which the effects of time-aggregation on the parameter estimates of hazard models were
International Nuclear Information System (INIS)
Aloui, Chaker; Mabrouk, Samir
2010-01-01
In this paper, we evaluate the value-at-risk (VaR) and the expected shortfalls for some major crude oil and gas commodities for both short and long trading positions. Classical VaR estimations as well as RiskMetrics and other extensions to cases considering for long-range memory, asymmetry and fat-tail in energy markets volatility were conducted. We computed the VaR for three ARCH/GARCH-type models including FIGARCH, FIAPARCH and HYGARCH. These models were estimated in the presence of three alternative innovation's distributions: normal, Student and skewed Student. Our results show that considering for long-range memory, fat-tails and asymmetry performs better in predicting a one-day-ahead VaR for both short and long trading positions. Moreover, the FIAPARCH model outperforms the other models in the VaR's prediction. These results present several potential implications for energy markets risk quantifications and hedging strategies. (author)
Kouramas, K.I.
2011-08-01
This work presents a new algorithm for solving the explicit/multi- parametric model predictive control (or mp-MPC) problem for linear, time-invariant discrete-time systems, based on dynamic programming and multi-parametric programming techniques. The algorithm features two key steps: (i) a dynamic programming step, in which the mp-MPC problem is decomposed into a set of smaller subproblems in which only the current control, state variables, and constraints are considered, and (ii) a multi-parametric programming step, in which each subproblem is solved as a convex multi-parametric programming problem, to derive the control variables as an explicit function of the states. The key feature of the proposed method is that it overcomes potential limitations of previous methods for solving multi-parametric programming problems with dynamic programming, such as the need for global optimization for each subproblem of the dynamic programming step. © 2011 Elsevier Ltd. All rights reserved.
Directory of Open Access Journals (Sweden)
Olav Slupphaug
1999-07-01
Full Text Available In this paper a method for nonlinear robust stabilization based on solving a bilinear matrix inequality (BMI feasibility problem is developed. Robustness against model uncertainty is handled. In different non-overlapping regions of the state-space called clusters the plant is assumed to be an element in a polytope which vertices (local models are affine systems. In the clusters containing the origin in their closure, the local models are restricted to be linear systems. The clusters cover the region of interest in the state-space. An affine state-feedback is associated with each cluster. By utilizing the affinity of the local models and the state-feedback, a set of linear matrix inequalities (LMIs combined with a single nonconvex BMI are obtained which, if feasible, guarantee quadratic stability of the origin of the closed-loop. The feasibility problem is attacked by a branch-and-bound based global approach. If the feasibility check is successful, the Liapunov matrix and the piecewise affine state-feedback are given directly by the feasible solution. Control constraints are shown to be representable by LMIs or BMIs, and an application of the control design method to robustify constrained nonlinear model predictive control is presented. Also, the control design method is applied to a simple example.
International Nuclear Information System (INIS)
Batlle, C.; Barquin, J.
2004-01-01
This paper presents a fuel prices scenario generator in the frame of a simulation tool developed to support risk analysis in a competitive electricity environment. The tool feeds different erogenous risk factors to a wholesale electricity market model to perform a statistical analysis of the results. As the different fuel series that are studied, such as the oil or gas ones, present stochastic volatility and strong correlation among them, a multivariate Generalized Autoregressive Conditional Heteroskedastic (GARCH) model has been designed in order to allow the generation of future fuel prices paths. The model makes use of a decomposition method to simplify the consideration of the multidimensional conditional covariance. An example of its application with real data is also presented. (author)
Directory of Open Access Journals (Sweden)
Marek Karaś
2017-12-01
Full Text Available In this paper, we discuss the no-arbitrage condition in a discrete financial market model which does not hold the same interest rate assumptions. Our research was based on, essentially, one of the most important results in mathematical finance, called the Fundamental Theorem of Asset Pricing. For the standard approach a risk-free bank account process is used as numeraire. In those models it is assumed that the interest rates for borrowing and saving money are the same. In our paper we consider the model of a market (with d risky assets, which does not hold the same interest rate assumptions. We introduce two predictable processes for modelling deposits and loans. We propose a new concept of a martingale pair for the market and prove that if there exists a martingale pair for the considered market, then there is no arbitrage opportunity. We also consider special cases in which the existence of a martingale pair is necessary and the sufficient conditions for these markets to be arbitrage free
Akimenko, Vitalii; Anguelov, Roumen
2017-12-01
In this paper we study the nonlinear age-structured model of a polycyclic two-phase population dynamics including delayed effect of population density growth on the mortality. Both phases are modelled as a system of initial boundary values problem for semi-linear transport equation with delay and initial problem for nonlinear delay ODE. The obtained system is studied both theoretically and numerically. Three different regimes of population dynamics for asymptotically stable states of autonomous systems are obtained in numerical experiments for the different initial values of population density. The quasi-periodical travelling wave solutions are studied numerically for the autonomous system with the different values of time delays and for the system with oscillating death rate and birth modulus. In both cases it is observed three types of travelling wave solutions: harmonic oscillations, pulse sequence and single pulse.
Single-crossover recombination in discrete time.
von Wangenheim, Ute; Baake, Ellen; Baake, Michael
2010-05-01
Modelling the process of recombination leads to a large coupled nonlinear dynamical system. Here, we consider a particular case of recombination in discrete time, allowing only for single crossovers. While the analogous dynamics in continuous time admits a closed solution (Baake and Baake in Can J Math 55:3-41, 2003), this no longer works for discrete time. A more general model (i.e. without the restriction to single crossovers) has been studied before (Bennett in Ann Hum Genet 18:311-317, 1954; Dawson in Theor Popul Biol 58:1-20, 2000; Linear Algebra Appl 348:115-137, 2002) and was solved algorithmically by means of Haldane linearisation. Using the special formalism introduced by Baake and Baake (Can J Math 55:3-41, 2003), we obtain further insight into the single-crossover dynamics and the particular difficulties that arise in discrete time. We then transform the equations to a solvable system in a two-step procedure: linearisation followed by diagonalisation. Still, the coefficients of the second step must be determined in a recursive manner, but once this is done for a given system, they allow for an explicit solution valid for all times.
Construction of Discrete Time Shadow Price
International Nuclear Information System (INIS)
Rogala, Tomasz; Stettner, Lukasz
2015-01-01
In the paper expected utility from consumption over finite time horizon for discrete time markets with bid and ask prices and strictly concave utility function is considered. The notion of weak shadow price, i.e. an illiquid price, depending on the portfolio, under which the model without bid and ask price is equivalent to the model with bid and ask price is introduced. Existence and the form of weak shadow price is shown. Using weak shadow price usual (called in the paper strong) shadow price is then constructed
Brajesh Kumar; Singh, Priyanka
2008-01-01
This paper is based on an empirical study of volatility, risk premium and seasonality in risk-return relation of the Indian stock and commodity markets. This investigation is conducted by means of the General Autoregressive Conditional Heteroscedasticity in the mean model (GARCH-in-Mean) introduced by Engle et al. (1987). A systematic approach to model volatility in returns is presented. Volatility clustering and asymmetric nature is examined for Indian stock and commodity markets. The risk-r...
International Nuclear Information System (INIS)
Pham, Thao; Lemoine, Killian
2015-01-01
Electricity generated by renewable energy sources creates a downward pressure on wholesale prices through - the so-called 'merit order effect'. This effect tends to lower average power prices and average market revenue that renewables producers should have received, making integration costs of renewables very high at large penetration rate. It is therefore crucial to determine the amplitude of this merit order effect particularly in the context of increasing burden of renewable support policies borne by final consumers. Using hourly data for the period 2009-2012 in German electricity wholesale market for GARCH model under panel data framework, we find that wind and solar power generation injected into German electricity network during this period induces a decrease of electricity spot prices and a slight increase of their volatility. The model-based results suggest that the merit-order effect created by renewable production ranges from 3.86 to 8.34 euro/MWh which implies to the annual volume of consumers' surplus from 1.89 to 3.92 billion euros. However this surplus has not been re-distributed equally among different types of electricity consumers. (authors)
Directory of Open Access Journals (Sweden)
Iulian PANAIT
2012-05-01
Full Text Available In our paper we use data mining to compare the volatility structure of high (daily and low (weekly, monthly frequencies for seven Romanian companies traded on Bucharest Stock Exchange and three market indices, during 1997-2012. For each of the 10 time series and three frequencies we fit a GARCH-in-mean model and we find that persistency is more present in the daily returns as compared with the weekly and monthly series. On the other hand, the GARCH-in-mean failed to confirm (on our data the theoretical hypothesis that an increase in volatility leads to a rise in future returns, mainly because the variance coefficient from the mean equation of the model was not statistically significant for most of the time series analyzed and on most of the frequencies. The diagnosis that we ran in order the verify the goodness of fit for the model showed that GARCH-in-mean was well fitted on the weekly and monthly time series but behaved less well on the daily time series.
GARCH Option Valuation: Theory and Evidence
DEFF Research Database (Denmark)
Christoffersen, Peter; Jacobs, Kris; Ornthanalai, Chayawat
We survey the theory and empirical evidence on GARCH option valuation models. Our treatment includes the range of functional forms available for the volatility dynamic, multifactor models, nonnormal shock distributions as well as style of pricing kernels typically used. Various strategies...... for empirical implementation are laid out and we also discuss the links between GARCH and stochastic volatility models. In the appendix we provide Matlab computer code for option pricing via Monte Carlo simulation for nonaffine models as well as Fourier inversion for affine models....
Partition-based discrete-time quantum walks
Konno, Norio; Portugal, Renato; Sato, Iwao; Segawa, Etsuo
2018-04-01
We introduce a family of discrete-time quantum walks, called two-partition model, based on two equivalence-class partitions of the computational basis, which establish the notion of local dynamics. This family encompasses most versions of unitary discrete-time quantum walks driven by two local operators studied in literature, such as the coined model, Szegedy's model, and the 2-tessellable staggered model. We also analyze the connection of those models with the two-step coined model, which is driven by the square of the evolution operator of the standard discrete-time coined walk. We prove formally that the two-step coined model, an extension of Szegedy model for multigraphs, and the two-tessellable staggered model are unitarily equivalent. Then, selecting one specific model among those families is a matter of taste not generality.
Periodic Seasonal Reg-ARFIMA-GARCH Models for Daily Electricity Spot Prices
Ooms, M.; Koopman, S.J.; Carnero, A.M.
2007-01-01
Novel periodic extensions of dynamic long-memory regression models with autoregressive conditional heteroscedastic errors are considered for the analysis of daily electricity spot prices. The parameters of the model with mean and variance specifications are estimated simultaneously by the method of
Musci, Rashelle J; Fairman, Brian; Masyn, Katherine E; Uhl, George; Maher, Brion; Sisto, Danielle Y; Kellam, Sheppard G; Ialongo, Nicholas S
2018-01-01
The present study examines the interaction between a polygenic score and an elementary school-based universal preventive intervention trial and its effects on a discrete-time survival analysis of time to first smoking marijuana. Research has suggested that initiation of substances is both genetically and environmentally driven (Rhee et al., Archives of general psychiatry 60:1256-1264, 2003; Verweij et al., Addiction 105:417-430, 2010). A previous work has found a significant interaction between the polygenic score and the same elementary school-based intervention with tobacco smoking (Musci et al., in press). The polygenic score reflects the contribution of multiple genes and has been shown in prior research to be predictive of smoking cessation, tobacco use, and marijuana use (Uhl et al., Molecular Psychiatry 19:50-54, 2014). Using data from a longitudinal preventive intervention study (N = 678), we examined age of first marijuana use from sixth grade to age 18. Genetic data were collected during emerging adulthood and were genotyped using the Affymetrix 6.0 microarray (N = 545). The polygenic score was computed using these data. Discrete-time survival analysis was employed to test for intervention main and interaction effects with the polygenic score. We found main effect of the polygenic score approaching significance, with the participants with higher polygenic scores reporting their first smoking marijuana at an age significantly later than controls (p = .050). We also found a significant intervention × polygenic score interaction effect at p = .003, with participants at the higher end of the polygenic score benefiting the most from the intervention in terms of delayed age of first use. These results suggest that genetics may play an important role in the age of first use of marijuana and that differences in genetics may account for the differential effectiveness of classroom-based interventions in delaying substance use experimentation.
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.
Discrete-time nonlinear sliding mode controller
African Journals Online (AJOL)
user
Keywords: Discrete-time delay system, Sliding mode control, nonlinear sliding ... of engineering systems such as chemical process control, delay in the actuator ...... instrumentation from Motilal Nehru National Institute of Technology (MNNIT),.
Symmetries in discrete-time mechanics
International Nuclear Information System (INIS)
Khorrami, M.
1996-01-01
Based on a general formulation for discrete-time quantum mechanics, introduced by M. Khorrami (Annals Phys. 224 (1995), 101), symmetries in discrete-time quantum mechanics are investigated. It is shown that any classical continuous symmetry leads to a conserved quantity in classical mechanics, as well as quantum mechanics. The transformed wave function, however, has the correct evolution if and only if the symmetry is nonanomalous. Copyright copyright 1996 Academic Press, Inc
Chen, Cathy W. S.; Yang, Ming Jing; Gerlach, Richard; Jim Lo, H.
2006-07-01
In this paper, we investigate the asymmetric reactions of mean and volatility of stock returns in five major markets to their own local news and the US information via linear and nonlinear models. We introduce a four-regime Double-Threshold GARCH (DTGARCH) model, which allows asymmetry in both the conditional mean and variance equations simultaneously by employing two threshold variables, to analyze the stock markets’ reactions to different types of information (good/bad news) generated from the domestic markets and the US stock market. By applying the four-regime DTGARCH model, this study finds that the interaction between the information of domestic and US stock markets leads to the asymmetric reactions of stock returns and their variability. In addition, this research also finds that the positive autocorrelation reported in the previous studies of financial markets may in fact be mis-specified, and actually due to the local market's positive response to the US stock market.
Bitcoin, gold and the dollar: A GARCH volatility analysis
Dyhrberg, Anne Haubo
2015-01-01
This paper explores the financial asset capabilities of bitcoin using GARCH models. The initial model showed several similarities to gold and the dollar indicating hedging capabilities and advantages as a medium of exchange. The asymmetric GARCH showed that bitcoin may be useful in risk management and ideal for risk averse investors in anticipation of negative shocks to the market. Overall bitcoin has a place on the financial markets and in portfolio management as it can be classified as some...
Nonstationary ARCH and GARCH with t-distributed Innovations
DEFF Research Database (Denmark)
Pedersen, Rasmus Søndergaard; Rahbek, Anders
Consistency and asymptotic normality are established for the maximum likelihood estimators in the nonstationary ARCH and GARCH models with general t-distributed innovations. The results hold for joint estimation of (G)ARCH effects and the degrees of freedom parameter parametrizing the t-distribut......Consistency and asymptotic normality are established for the maximum likelihood estimators in the nonstationary ARCH and GARCH models with general t-distributed innovations. The results hold for joint estimation of (G)ARCH effects and the degrees of freedom parameter parametrizing the t......-distribution. With T denoting sample size, classic square-root T-convergence is shown to hold with closed form expressions for the multivariate covariances....
Estimating risk of foreign exchange portfolio: Using VaR and CVaR based on GARCH-EVT-Copula model
Wang, Zong-Run; Chen, Xiao-Hong; Jin, Yan-Bo; Zhou, Yan-Ju
2010-11-01
This paper introduces GARCH-EVT-Copula model and applies it to study the risk of foreign exchange portfolio. Multivariate Copulas, including Gaussian, t and Clayton ones, were used to describe a portfolio risk structure, and to extend the analysis from a bivariate to an n-dimensional asset allocation problem. We apply this methodology to study the returns of a portfolio of four major foreign currencies in China, including USD, EUR, JPY and HKD. Our results suggest that the optimal investment allocations are similar across different Copulas and confidence levels. In addition, we find that the optimal investment concentrates on the USD investment. Generally speaking, t Copula and Clayton Copula better portray the correlation structure of multiple assets than Normal Copula.
Discrete time analysis of a repairable machine
Alfa, Attahiru Sule; Castro, I. T.
2002-01-01
We consider, in discrete time, a single machine system that operates for a period of time represented by a general distribution. This machine is subject to failures during operations and the occurrence of these failures depends on how many times the machine has previously failed. Some failures are repairable and the repair times may or may not depend on the number of times the machine was previously repaired. Repair times also have a general distribution. The operating times...
Discrete-Time LPV Current Control of an Induction Motor
DEFF Research Database (Denmark)
Bendtsen, Jan Dimon; Trangbæk, Klaus
2003-01-01
In this paper we apply a new method for gain-scheduled output feedback control of nonlinear systems to current control of an induction motor. The method relies on recently developed controller synthesis results for linear parameter-varying (LPV) systems, where the controller synthesis is formulated...... as a set of linear matrix inequalities with full-block multipliers. A standard nonlinear model of the motor is constructed and written on LPV form. We then show that, although originally developed in continuous time, the controller synthesis results can be applied to a discrete-time model as well without...... further complications. The synthesis method is applied to the model, yielding an LPV discrete-time controller. Finally, the efficiency of the control scheme is validated via simulations as well as on the actual induction motor, both in open-loop current control and when an outer speed control loop...
Discrete-Time Nonlinear Control of VSC-HVDC System
Directory of Open Access Journals (Sweden)
TianTian Qian
2015-01-01
Full Text Available Because VSC-HVDC is a kind of strong nonlinear, coupling, and multi-input multioutput (MIMO system, its control problem is always attracting much attention from scholars. And a lot of papers have done research on its control strategy in the continuous-time domain. But the control system is implemented through the computer discrete sampling in practical engineering. It is necessary to study the mathematical model and control algorithm in the discrete-time domain. The discrete mathematical model based on output feedback linearization and discrete sliding mode control algorithm is proposed in this paper. And to ensure the effectiveness of the control system in the quasi sliding mode state, the fast output sampling method is used in the output feedback. The results from simulation experiment in MATLAB/SIMULINK prove that the proposed discrete control algorithm can make the VSC-HVDC system have good static, dynamic, and robust characteristics in discrete-time domain.
Discrete-time control system design with applications
Rabbath, C A
2014-01-01
This book presents practical techniques of discrete-time control system design. In general, the design techniques lead to low-order dynamic compensators that ensure satisfactory closed-loop performance for a wide range of sampling rates. The theory is given in the form of theorems, lemmas, and propositions. The design of the control systems is presented as step-by-step procedures and algorithms. The proposed feedback control schemes are applied to well-known dynamic system models. This book also discusses: Closed-loop performance of generic models of mobile robot and airborne pursuer dynamic systems under discrete-time feedback control with limited computing capabilities Concepts of discrete-time models and sampled-data models of continuous-time systems, for both single- and dual-rate operation Local versus global digital redesign Optimal, closed-loop digital redesign methods Plant input mapping design Generalized holds and samplers for use in feedback control loops, Numerical simulation of fixed-point arithm...
DEFF Research Database (Denmark)
Zhang, Xuping; Sørensen, Rasmus; RahbekIversen, Mathias
2018-01-01
This paper presents a novel and computationally efficient modeling method for the dynamics of flexible-link robot manipulators. In this method, a robot manipulator is decomposed into components/elements. The component/element dynamics is established using Newton–Euler equations, and then is linea......This paper presents a novel and computationally efficient modeling method for the dynamics of flexible-link robot manipulators. In this method, a robot manipulator is decomposed into components/elements. The component/element dynamics is established using Newton–Euler equations......, and then is linearized based on the acceleration-based state vector. The transfer matrices for each type of components/elements are developed, and used to establish the system equations of a flexible robot manipulator by concatenating the state vector from the base to the end-effector. With this strategy, the size...... manipulators, and only involves calculating and transferring component/element dynamic equations that have small size. The numerical simulations and experimental testing of flexible-link manipulators are conducted to validate the proposed methodologies....
A discrete-time adaptive control scheme for robot manipulators
Tarokh, M.
1990-01-01
A discrete-time model reference adaptive control scheme is developed for trajectory tracking of robot manipulators. The scheme utilizes feedback, feedforward, and auxiliary signals, obtained from joint angle measurement through simple expressions. Hyperstability theory is utilized to derive the adaptation laws for the controller gain matrices. It is shown that trajectory tracking is achieved despite gross robot parameter variation and uncertainties. The method offers considerable design flexibility and enables the designer to improve the performance of the control system by adjusting free design parameters. The discrete-time adaptation algorithm is extremely simple and is therefore suitable for real-time implementation. Simulations and experimental results are given to demonstrate the performance of the scheme.
Zheng, Yang; Zhou, Jianzhong; Xu, Yanhe; Zhang, Yuncheng; Qian, Zhongdong
2017-05-01
This paper proposes a distributed model predictive control based load frequency control (MPC-LFC) scheme to improve control performances in the frequency regulation of power system. In order to reduce the computational burden in the rolling optimization with a sufficiently large prediction horizon, the orthonormal Laguerre functions are utilized to approximate the predicted control trajectory. The closed-loop stability of the proposed MPC scheme is achieved by adding a terminal equality constraint to the online quadratic optimization and taking the cost function as the Lyapunov function. Furthermore, the treatments of some typical constraints in load frequency control have been studied based on the specific Laguerre-based formulations. Simulations have been conducted in two different interconnected power systems to validate the effectiveness of the proposed distributed MPC-LFC as well as its superiority over the comparative methods. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
Speeding Up Network Simulations Using Discrete Time
Lucas, Aaron; Armbruster, Benjamin
2013-01-01
We develop a way of simulating disease spread in networks faster at the cost of some accuracy. Instead of a discrete event simulation (DES) we use a discrete time simulation. This aggregates events into time periods. We prove a bound on the accuracy attained. We also discuss the choice of step size and do an analytical comparison of the computational costs. Our error bound concept comes from the theory of numerical methods for SDEs and the basic proof structure comes from the theory of numeri...
Discrete-Time Biomedical Signal Encryption
Directory of Open Access Journals (Sweden)
Victor Grigoraş
2017-12-01
Full Text Available Chaotic modulation is a strong method of improving communication security. Analog and discrete chaotic systems are presented in actual literature. Due to the expansion of digital communication, discrete-time systems become more efficient and closer to actual technology. The present contribution offers an in-depth analysis of the effects chaos encryption produce on 1D and 2D biomedical signals. The performed simulations show that modulating signals are precisely recovered by the synchronizing receiver if discrete systems are digitally implemented and the coefficients precisely correspond. Channel noise is also applied and its effects on biomedical signal demodulation are highlighted.
Integrals of Motion for Discrete-Time Optimal Control Problems
Torres, Delfim F. M.
2003-01-01
We obtain a discrete time analog of E. Noether's theorem in Optimal Control, asserting that integrals of motion associated to the discrete time Pontryagin Maximum Principle can be computed from the quasi-invariance properties of the discrete time Lagrangian and discrete time control system. As corollaries, results for first-order and higher-order discrete problems of the calculus of variations are obtained.
Frequency interval balanced truncation of discrete-time bilinear systems
DEFF Research Database (Denmark)
Jazlan, Ahmad; Sreeram, Victor; Shaker, Hamid Reza
2016-01-01
This paper presents the development of a new model reduction method for discrete-time bilinear systems based on the balanced truncation framework. In many model reduction applications, it is advantageous to analyze the characteristics of the system with emphasis on particular frequency intervals...... are the solution to a pair of new generalized Lyapunov equations. The conditions for solvability of these new generalized Lyapunov equations are derived and a numerical solution method for solving these generalized Lyapunov equations is presented. Numerical examples which illustrate the usage of the new...... generalized frequency interval controllability and observability gramians as part of the balanced truncation framework are provided to demonstrate the performance of the proposed method....
Global consensus for discrete-time competitive systems
International Nuclear Information System (INIS)
Shih, C.-W.; Tseng, J.-P.
2009-01-01
Grossberg established a remarkable convergence theorem for a class of competitive systems without knowing and using Lyapunov function for the systems. We present the parallel investigations for the discrete-time version of the Grossberg's model. Through developing an extended component-competing analysis for the coupled system, without knowing a Lyapunov function and applying the LaSalle's invariance principle, the global pattern formation or the so-called global consensus for the system can be achieved. A numerical simulation is performed to illustrate the present theory.
Robust performance results for discrete-time systems
Directory of Open Access Journals (Sweden)
Mahmoud Magdi S.
1997-01-01
Full Text Available The problems of robust performance and feedback control synthesis for a class of linear discrete-time systems with time-varying parametric uncertainties are addressed in this paper. The uncertainties are bound and have a linear matrix fractional form. Based on the concept of strongly robust H ∞ -performance criterion, results of robust stability and performance are developed and expressed in easily computable linear matrix inequalities. Synthesis of robust feedback controllers is carried out for several system models of interest.
Sampling rare fluctuations of discrete-time Markov chains
Whitelam, Stephen
2018-03-01
We describe a simple method that can be used to sample the rare fluctuations of discrete-time Markov chains. We focus on the case of Markov chains with well-defined steady-state measures, and derive expressions for the large-deviation rate functions (and upper bounds on such functions) for dynamical quantities extensive in the length of the Markov chain. We illustrate the method using a series of simple examples, and use it to study the fluctuations of a lattice-based model of active matter that can undergo motility-induced phase separation.
Discrete-Time LPV Current Control of an Induction Motor
DEFF Research Database (Denmark)
Bendtsen, Jan Dimon; Trangbæk, Klaus
2001-01-01
In this paper we apply a new method for gain-scheduled output feedback control of nonlinear systems to current control of an induction motor. The method relies on recently developed controller synthesis results for linear parameter-varying (LPV) systems, where the controller synthesis is formulated...... without further complications. The synthesis method is applied to the model, yielding an LPV discrete-time controller. Finally, the efficiency of the control scheme is validated via simulations as well as experimentally on the actual induction motor, both in open-loop current control and when an outer...... speed control loop is closed around the current loop...
Discrete-Time LPV Current Control of an Induction Motor
DEFF Research Database (Denmark)
Bendtsen, Jan Dimon; Trangbæk, Klaus
2003-01-01
In this paper we apply a new method for gain-scheduled output feedback control of nonlinear systems to current control of an induction motor. The method relies on recently developed controller synthesis results for linear parameter-varying (LPV) systems, where the controller synthesis is formulated...... further complications. The synthesis method is applied to the model, yielding an LPV discrete-time controller. Finally, the efficiency of the control scheme is validated via simulations as well as on the actual induction motor, both in open-loop current control and when an outer speed control loop...... is closed around the current loop....
DEFF Research Database (Denmark)
Hansen, Peter Reinhard; Lunde, Asger; Voev, Valeri Radkov
2014-01-01
is particularly useful for modeling financial returns during periods of rapid changes in the underlying covariance structure. When applied to market returns in conjunction with returns on an individual asset, the model yields a dynamic model specification of the conditional regression coefficient that is known...
International Nuclear Information System (INIS)
Huang Zhenkun; Wang Xinghua; Gao Feng
2006-01-01
In this Letter, we discuss discrete-time analogue of a continuous-time cellular neural network. Sufficient conditions are obtained for the existence of a unique almost periodic sequence solution which is globally attractive. Our results demonstrate dynamics of the formulated discrete-time analogue as mathematical models for the continuous-time cellular neural network in almost periodic case. Finally, a computer simulation illustrates the suitability of our discrete-time analogue as numerical algorithms in simulating the continuous-time cellular neural network conveniently
DEFF Research Database (Denmark)
Bollerslev, Tim
The literature on modeling and forecasting time-varying volatility is ripe with acronyms and abbreviations used to describe the many different parametric models that have been put forth since the original linear ARCH model introduced in the seminal Nobel Prize winning paper by Engle (1982......). The present paper provides an easy-to-use encyclopedic reference guide to this long list of ARCH acronyms. In addition to the acronyms associated with specific parametric models, I have also included descriptions of various abbreviations associated with more general statistical procedures and ideas...
Parisian ruin for the dual risk process in discrete-time
Palmowski, Zbigniew; Ramsden, Lewis; Papaioannou, Apostolos D.
2017-01-01
In this paper we consider the Parisian ruin probabilities for the dual risk model in a discrete-time setting. By exploiting the strong Markov property of the risk process we derive a recursive expression for the fnite-time Parisian ruin probability, in terms of classic discrete-time dual ruin probabilities. Moreover, we obtain an explicit expression for the corresponding infnite-time Parisian ruin probability as a limiting case. In order to obtain more analytic results, we employ a conditioni...
Synchronization of discrete-time hyperchaotic systems: An application in communications
International Nuclear Information System (INIS)
Aguilar-Bustos, A.Y.; Cruz-Hernandez, C.
2009-01-01
In this paper, the synchronization problem of discrete-time complex dynamics is presented. In particular, we use the model-matching approach from nonlinear control theory to synchronize two unidirectionally coupled discrete-time hyperchaotic systems. A potential application to secure/private communication of confidential information is also given. By using different (hyperchaotic) encryption schemes with a single and two transmission channels, we show that output synchronization of hyperchaotic maps is indeed suitable for encryption, transmission, and decryption of information.
Coordination Frictions and Job Heterogeneity: A Discrete Time Analysis
DEFF Research Database (Denmark)
Kennes, John; Le Maire, Christian Daniel
This paper develops and extends a dynamic, discrete time, job to worker matching model in which jobs are heterogeneous in equilibrium. The key assumptions of this economic environment are (i) matching is directed and (ii) coordination frictions lead to heterogeneous local labor markets. We de- rive...... a number of new theoretical results, which are essential for the empirical application of this type of model to matched employer-employee microdata. First, we o¤er a robust equilibrium concept in which there is a continu- ous dispersion of job productivities and wages. Second, we show that our model can...... of these results preserve the essential tractability of the baseline model with aggregate shocks. Therefore, we o¤er a parsimonious, general equilibrium framework in which to study the process by which the contin- uous dispersion of wages and productivities varies over the business cycle for a large population...
Dong, Lu; Zhong, Xiangnan; Sun, Changyin; He, Haibo
2017-07-01
This paper presents the design of a novel adaptive event-triggered control method based on the heuristic dynamic programming (HDP) technique for nonlinear discrete-time systems with unknown system dynamics. In the proposed method, the control law is only updated when the event-triggered condition is violated. Compared with the periodic updates in the traditional adaptive dynamic programming (ADP) control, the proposed method can reduce the computation and transmission cost. An actor-critic framework is used to learn the optimal event-triggered control law and the value function. Furthermore, a model network is designed to estimate the system state vector. The main contribution of this paper is to design a new trigger threshold for discrete-time systems. A detailed Lyapunov stability analysis shows that our proposed event-triggered controller can asymptotically stabilize the discrete-time systems. Finally, we test our method on two different discrete-time systems, and the simulation results are included.
Directory of Open Access Journals (Sweden)
Hegerty Scott W.
2015-11-01
Full Text Available Recent commodity price declines have added to worldwide macroeconomic risk, which has had serious effects on both commodity exporters and manufacturers that use oil and raw materials. These effects have been keenly felt in Central and Eastern Europe—particularly in Russia, but also in European Union member states. This study tests for spillovers among commodity-price and macroeconomic volatility by applying a VAR(1-MGARCH model to monthly time series for eight CEE countries. Overall, we find that oil prices do indeed have effects throughout the region, as do spillovers among exchange rates, inflation, interest rates, and output, but that they differ from country to country—particularly when different degrees of transition and integration are considered. While oil prices have a limited impact on the currencies of Russia and Ukraine, they do make a much larger contribution to the two countries’ macroeconomic volatility than do spillovers among the other macroeconomic variables.
Formal methods for discrete-time dynamical systems
Belta, Calin; Aydin Gol, Ebru
2017-01-01
This book bridges fundamental gaps between control theory and formal methods. Although it focuses on discrete-time linear and piecewise affine systems, it also provides general frameworks for abstraction, analysis, and control of more general models. The book is self-contained, and while some mathematical knowledge is necessary, readers are not expected to have a background in formal methods or control theory. It rigorously defines concepts from formal methods, such as transition systems, temporal logics, model checking and synthesis. It then links these to the infinite state dynamical systems through abstractions that are intuitive and only require basic convex-analysis and control-theory terminology, which is provided in the appendix. Several examples and illustrations help readers understand and visualize the concepts introduced throughout the book.
Process algebra with timing : real time and discrete time
Baeten, J.C.M.; Middelburg, C.A.; Bergstra, J.A.; Ponse, A.J.; Smolka, S.A.
2001-01-01
We present real time and discrete time versions of ACP with absolute timing and relative timing. The starting-point is a new real time version with absolute timing, called ACPsat, featuring urgent actions and a delay operator. The discrete time versions are conservative extensions of the discrete
On the application of Discrete Time Optimal Control Concepts to ...
African Journals Online (AJOL)
On the application of Discrete Time Optimal Control Concepts to Economic Problems. ... Journal of the Nigerian Association of Mathematical Physics ... Abstract. An extension of the use of the maximum principle to solve Discrete-time Optimal Control Problems (DTOCP), in which the state equations are in the form of general ...
Process algebra with timing: Real time and discrete time
Baeten, J.C.M.; Middelburg, C.A.
1999-01-01
We present real time and discrete time versions of ACP with absolute timing and relative timing. The startingpoint is a new real time version with absolute timing, called ACPsat , featuring urgent actions and a delay operator. The discrete time versions are conservative extensions of the discrete
Continuous and Discrete-Time Optimal Controls for an Isolated Signalized Intersection
Directory of Open Access Journals (Sweden)
Jiyuan Tan
2017-01-01
Full Text Available A classical control problem for an isolated oversaturated intersection is revisited with a focus on the optimal control policy to minimize total delay. The difference and connection between existing continuous-time planning models and recently proposed discrete-time planning models are studied. A gradient descent algorithm is proposed to convert the optimal control plan of the continuous-time model to the plan of the discrete-time model in many cases. Analytic proof and numerical tests for the algorithm are also presented. The findings shed light on the links between two kinds of models.
Forecasting Tehran stock exchange volatility; Markov switching GARCH approach
Abounoori, Esmaiel; Elmi, Zahra (Mila); Nademi, Younes
2016-03-01
This paper evaluates several GARCH models regarding their ability to forecast volatility in Tehran Stock Exchange (TSE). These include GARCH models with both Gaussian and fat-tailed residual conditional distribution, concerning their ability to describe and forecast volatility from 1-day to 22-day horizon. Results indicate that AR(2)-MRSGARCH-GED model outperforms other models at one-day horizon. Also, the AR(2)-MRSGARCH-GED as well as AR(2)-MRSGARCH-t models outperform other models at 5-day horizon. In 10 day horizon, three models of AR(2)-MRSGARCH outperform other models. Concerning 22 day forecast horizon, results indicate no differences between MRSGARCH models with that of standard GARCH models. Regarding Risk management out-of-sample evaluation (95% VaR), a few models seem to provide reasonable and accurate VaR estimates at 1-day horizon, with a coverage rate close to the nominal level. According to the risk management loss functions, there is not a uniformly most accurate model.
Discrete-time sliding mode control for MR vehicle suspension system
Energy Technology Data Exchange (ETDEWEB)
Sohn, J W; Choi, S B [Smart Structures and Systems Laboratory, Department of Mechanical Engineering, Inha University, Incheon 402-751 (Korea, Republic of); Wereley, N M [Smart Structures Laboratory, Department of Aerospace Engineering, University of Maryland, College Park, MD 20742 (United States)], E-mail: seungbok@inha.ac.kr
2009-02-01
This paper presents control performance of a full-vehicle suspension system featuring magnetorheological (MR) dampers via a discrete-time sliding mode control algorithm (DSMC). A cylindrical MR damper is designed by incorporating Bingham model of the MR fluid and the field-dependent damping characteristics of the MR damper are evaluated. A full-vehicle suspension model installed with independent four MR dampers is constructed and the governing equations which include vertical, pitch and roll motion are derived. A discrete-time control model is established with considering system uncertainties and a discrete-time sliding mode controller which has inherent robustness to model uncertainty and external disturbance is formulated. Vibration control performances under bump excitation are evaluated and presented.
Discrete-time sliding mode control for MR vehicle suspension system
International Nuclear Information System (INIS)
Sohn, J W; Choi, S B; Wereley, N M
2009-01-01
This paper presents control performance of a full-vehicle suspension system featuring magnetorheological (MR) dampers via a discrete-time sliding mode control algorithm (DSMC). A cylindrical MR damper is designed by incorporating Bingham model of the MR fluid and the field-dependent damping characteristics of the MR damper are evaluated. A full-vehicle suspension model installed with independent four MR dampers is constructed and the governing equations which include vertical, pitch and roll motion are derived. A discrete-time control model is established with considering system uncertainties and a discrete-time sliding mode controller which has inherent robustness to model uncertainty and external disturbance is formulated. Vibration control performances under bump excitation are evaluated and presented.
Discrete-time inverse optimal control for nonlinear systems
Sanchez, Edgar N
2013-01-01
Discrete-Time Inverse Optimal Control for Nonlinear Systems proposes a novel inverse optimal control scheme for stabilization and trajectory tracking of discrete-time nonlinear systems. This avoids the need to solve the associated Hamilton-Jacobi-Bellman equation and minimizes a cost functional, resulting in a more efficient controller. Design More Efficient Controllers for Stabilization and Trajectory Tracking of Discrete-Time Nonlinear Systems The book presents two approaches for controller synthesis: the first based on passivity theory and the second on a control Lyapunov function (CLF). Th
On synchronized regions of discrete-time complex dynamical networks
International Nuclear Information System (INIS)
Duan Zhisheng; Chen Guanrong
2011-01-01
In this paper, the local synchronization of discrete-time complex networks is studied. First, it is shown that for any natural number n, there exists a discrete-time network which has at least left floor n/2 right floor +1 disconnected synchronized regions for local synchronization, which implies the possibility of intermittent synchronization behaviors. Different from the continuous-time networks, the existence of an unbounded synchronized region is impossible for discrete-time networks. The convexity of the synchronized regions is also characterized based on the stability of a class of matrix pencils, which is useful for enlarging the stability region so as to improve the network synchronizability.
Hedging with futures: an application of GARCH to european electricity markets
G. Zanotti; G. Gabbi; M. Geranio
2009-01-01
European electricity markets have been subject to a broad deregulation process in the last few decades. We analyse hedging policies implemented through different hedge ratios estimation. More specifically we compare naïve, ordinary least squares, and GARCH conditional variance and correlations models to test if GARCH models lead to higher variance reduction in a context of high time varying volatility as the case of electricity markets. Our results show that the choice of the hedge ratio esti...
Cryptanalysis of a discrete-time synchronous chaotic encryption system
International Nuclear Information System (INIS)
Arroyo, David; Alvarez, Gonzalo; Li Shujun; Li Chengqing; Nunez, Juana
2008-01-01
Recently a chaotic cryptosystem based on discrete-time synchronization has been proposed. Some weaknesses of that new encryption system are addressed and exploited in order to successfully cryptanalyze the system
On periodic orbits in discrete-time cascade systems
Directory of Open Access Journals (Sweden)
Huimin Li
2006-01-01
Full Text Available We present some results on existence, minimum period, number of periodic orbits, and stability of periodic orbits in discrete-time cascade systems. Some examples are presented to illustrate these results.
Discrete-time optimal control and games on large intervals
Zaslavski, Alexander J
2017-01-01
Devoted to the structure of approximate solutions of discrete-time optimal control problems and approximate solutions of dynamic discrete-time two-player zero-sum games, this book presents results on properties of approximate solutions in an interval that is independent lengthwise, for all sufficiently large intervals. Results concerning the so-called turnpike property of optimal control problems and zero-sum games in the regions close to the endpoints of the time intervals are the main focus of this book. The description of the structure of approximate solutions on sufficiently large intervals and its stability will interest graduate students and mathematicians in optimal control and game theory, engineering, and economics. This book begins with a brief overview and moves on to analyze the structure of approximate solutions of autonomous nonconcave discrete-time optimal control Lagrange problems.Next the structures of approximate solutions of autonomous discrete-time optimal control problems that are discret...
Discrete-Time Filter Synthesis using Product of Gegenbauer Polynomials
N. Stojanovic; N. Stamenkovic; I. Krstic
2016-01-01
A new approximation to design continuoustime and discrete-time low-pass filters, presented in this paper, based on the product of Gegenbauer polynomials, provides the ability of more flexible adjustment of passband and stopband responses. The design is achieved taking into account a prescribed specification, leading to a better trade-off among the magnitude and group delay responses. Many well-known continuous-time and discrete-time transitional filter based on the classical polynomial approx...
Stabilization of discrete-time LTI positive systems
Directory of Open Access Journals (Sweden)
Krokavec Dušan
2017-12-01
Full Text Available The paper mitigates the existing conditions reported in the previous literature for control design of discrete-time linear positive systems. Incorporating an associated structure of linear matrix inequalities, combined with the Lyapunov inequality guaranteing asymptotic stability of discrete-time positive system structures, new conditions are presented with which the state-feedback controllers and the system state observers can be designed. Associated solutions of the proposed design conditions are illustrated by numerical illustrative examples.
Stabilisation of discrete-time polynomial fuzzy systems via a polynomial lyapunov approach
Nasiri, Alireza; Nguang, Sing Kiong; Swain, Akshya; Almakhles, Dhafer
2018-02-01
This paper deals with the problem of designing a controller for a class of discrete-time nonlinear systems which is represented by discrete-time polynomial fuzzy model. Most of the existing control design methods for discrete-time fuzzy polynomial systems cannot guarantee their Lyapunov function to be a radially unbounded polynomial function, hence the global stability cannot be assured. The proposed control design in this paper guarantees a radially unbounded polynomial Lyapunov functions which ensures global stability. In the proposed design, state feedback structure is considered and non-convexity problem is solved by incorporating an integrator into the controller. Sufficient conditions of stability are derived in terms of polynomial matrix inequalities which are solved via SOSTOOLS in MATLAB. A numerical example is presented to illustrate the effectiveness of the proposed controller.
Adaptive control of discrete-time chaotic systems: a fuzzy control approach
International Nuclear Information System (INIS)
Feng Gang; Chen Guanrong
2005-01-01
This paper discusses adaptive control of a class of discrete-time chaotic systems from a fuzzy control approach. Using the T-S model of discrete-time chaotic systems, an adaptive control algorithm is developed based on some conventional adaptive control techniques. The resulting adaptively controlled chaotic system is shown to be globally stable, and its robustness is discussed. A simulation example of the chaotic Henon map control is finally presented, to illustrate an application and the performance of the proposed control algorithm
Constant pressure and temperature discrete-time Langevin molecular dynamics
Energy Technology Data Exchange (ETDEWEB)
Grønbech-Jensen, Niels [Department of Mechanical and Aerospace Engineering, University of California, Davis, California 95616 (United States); Department of Mathematics, University of California, Davis, California 95616 (United States); Farago, Oded [Department of Biomedical Engineering, Ben Gurion University of the Negev, Be' er Sheva 84105 (Israel); Ilse Katz Institute for Nanoscale Science and Technology, Ben Gurion University of the Negev, Be' er Sheva 84105 (Israel)
2014-11-21
We present a new and improved method for simultaneous control of temperature and pressure in molecular dynamics simulations with periodic boundary conditions. The thermostat-barostat equations are built on our previously developed stochastic thermostat, which has been shown to provide correct statistical configurational sampling for any time step that yields stable trajectories. Here, we extend the method and develop a set of discrete-time equations of motion for both particle dynamics and system volume in order to seek pressure control that is insensitive to the choice of the numerical time step. The resulting method is simple, practical, and efficient. The method is demonstrated through direct numerical simulations of two characteristic model systems—a one-dimensional particle chain for which exact statistical results can be obtained and used as benchmarks, and a three-dimensional system of Lennard-Jones interacting particles simulated in both solid and liquid phases. The results, which are compared against the method of Kolb and Dünweg [J. Chem. Phys. 111, 4453 (1999)], show that the new method behaves according to the objective, namely that acquired statistical averages and fluctuations of configurational measures are accurate and robust against the chosen time step applied to the simulation.
Multiple Estimation Architecture in Discrete-Time Adaptive Mixing Control
Directory of Open Access Journals (Sweden)
Simone Baldi
2013-05-01
Full Text Available Adaptive mixing control (AMC is a recently developed control scheme for uncertain plants, where the control action coming from a bank of precomputed controller is mixed based on the parameter estimates generated by an on-line parameter estimator. Even if the stability of the control scheme, also in the presence of modeling errors and disturbances, has been shown analytically, its transient performance might be sensitive to the initial conditions of the parameter estimator. In particular, for some initial conditions, transient oscillations may not be acceptable in practical applications. In order to account for such a possible phenomenon and to improve the learning capability of the adaptive scheme, in this paper a new mixing architecture is developed, involving the use of parallel parameter estimators, or multi-estimators, each one working on a small subset of the uncertainty set. A supervisory logic, using performance signals based on the past and present estimation error, selects the parameter estimate to determine the mixing of the controllers. The stability and robustness properties of the resulting approach, referred to as multi-estimator adaptive mixing control (Multi-AMC, are analytically established. Besides, extensive simulations demonstrate that the scheme improves the transient performance of the original AMC with a single estimator. The control scheme and the analysis are carried out in a discrete-time framework, for easier implementation of the method in digital control.
Scaled Bilateral Teleoperation Using Discrete-Time Sliding-Mode Controller
Khan, S.; Sabanovic, A.; Nergiz, A.O.
2009-01-01
In this paper, the design of a discrete-time sliding-mode controller based on Lyapunov theory is presented along with a robust disturbance observer and is applied to a piezostage for high-precision motion. A linear model of a piezostage was used with nominal parameters to compensate the disturbance
Discrete-Time Filter Synthesis using Product of Gegenbauer Polynomials
Directory of Open Access Journals (Sweden)
N. Stojanovic
2016-09-01
Full Text Available A new approximation to design continuoustime and discrete-time low-pass filters, presented in this paper, based on the product of Gegenbauer polynomials, provides the ability of more flexible adjustment of passband and stopband responses. The design is achieved taking into account a prescribed specification, leading to a better trade-off among the magnitude and group delay responses. Many well-known continuous-time and discrete-time transitional filter based on the classical polynomial approximations(Chebyshev, Legendre, Butterworth are shown to be a special cases of proposed approximation method.
Engineering applications of discrete-time optimal control
DEFF Research Database (Denmark)
Vidal, Rene Victor Valqui; Ravn, Hans V.
1990-01-01
Many problems of design and operation of engineering systems can be formulated as optimal control problems where time has been discretisized. This is also true even if 'time' is not involved in the formulation of the problem, but rather another one-dimensional parameter. This paper gives a review...... of some well-known and new results in discrete time optimal control methods applicable to practical problem solving within engineering. Emphasis is placed on dynamic programming, the classical maximum principle and generalized versions of the maximum principle for optimal control of discrete time systems...
Liu, Xueyong; An, Haizhong; Huang, Shupei; Wen, Shaobo
2017-01-01
Aiming to investigate the evolution of mean and volatility spillovers between oil and stock markets in the time and frequency dimensions, we employed WTI crude oil prices, the S&P 500 (USA) index and the MICEX index (Russia) for the period Jan. 2003-Dec. 2014 as sample data. We first applied a wavelet-based GARCH-BEKK method to examine the spillover features in frequency dimension. To consider the evolution of spillover effects in time dimension at multiple-scales, we then divided the full sample period into three sub-periods, pre-crisis period, crisis period, and post-crisis period. The results indicate that spillover effects vary across wavelet scales in terms of strength and direction. By analysis the time-varying linkage, we found the different evolution features of spillover effects between the Oil-US stock market and Oil-Russia stock market. The spillover relationship between oil and US stock market is shifting to short-term while the spillover relationship between oil and Russia stock market is changing to all time scales. That result implies that the linkage between oil and US stock market is weakening in the long-term, and the linkage between oil and Russia stock market is getting close in all time scales. This may explain the phenomenon that the US stock index and the Russia stock index showed the opposite trend with the falling of oil price in the post-crisis period.
Invariant set computation for constrained uncertain discrete-time systems
Athanasopoulos, N.; Bitsoris, G.
2010-01-01
In this article a novel approach to the determination of polytopic invariant sets for constrained discrete-time linear uncertain systems is presented. First, the problem of stabilizing a prespecified initial condition set in the presence of input and state constraints is addressed. Second, the
Discrete time process algebra and the semantics of SDL
J.A. Bergstra; C.A. Middelburg; Y.S. Usenko (Yaroslav)
1998-01-01
htmlabstractWe present an extension of discrete time process algebra with relative timing where recursion, propositional signals and conditions, a counting process creation operator, and the state operator are combined. Except the counting process creation operator, which subsumes the original
Cryptanalyzing a discrete-time chaos synchronization secure communication system
International Nuclear Information System (INIS)
Alvarez, G.; Montoya, F.; Romera, M.; Pastor, G.
2004-01-01
This paper describes the security weakness of a recently proposed secure communication method based on discrete-time chaos synchronization. We show that the security is compromised even without precise knowledge of the chaotic system used. We also make many suggestions to improve its security in future versions
Cycles of a discrete time bipolar artificial neural network
International Nuclear Information System (INIS)
Cheng Suisun; Chen, J.-S.; Yueh, W.-C.
2009-01-01
A discrete time bipolar neural network depending on two parameters is studied. It is observed that its dynamical behaviors can be classified into six cases. For each case, the long time behaviors can be summarized in terms of fixed points, periodic points, basin of attractions, and related initial distributions. Mathematical reasons are supplied for these observations and applications in cellular automata are illustrated.
Simulating continuous-time Hamiltonian dynamics by way of a discrete-time quantum walk
International Nuclear Information System (INIS)
Schmitz, A.T.; Schwalm, W.A.
2016-01-01
Much effort has been made to connect the continuous-time and discrete-time quantum walks. We present a method for making that connection for a general graph Hamiltonian on a bigraph. Furthermore, such a scheme may be adapted for simulating discretized quantum models on a quantum computer. A coin operator is found for the discrete-time quantum walk which exhibits the same dynamics as the continuous-time evolution. Given the spectral decomposition of the graph Hamiltonian and certain restrictions, the discrete-time evolution is solved for explicitly and understood at or near important values of the parameters. Finally, this scheme is connected to past results for the 1D chain. - Highlights: • A discrete-time quantum walk is purposed which approximates a continuous-time quantum walk. • The purposed quantum walk could be used to simulate Hamiltonian dynamics on a quantum computer. • Given the spectra decomposition of the Hamiltonian, the quantum walk is solved explicitly. • The method is demonstrated and connected to previous work done on the 1D chain.
Stochastic ℋ∞ Finite-Time Control of Discrete-Time Systems with Packet Loss
Directory of Open Access Journals (Sweden)
Yingqi Zhang
2012-01-01
Full Text Available This paper investigates the stochastic finite-time stabilization and ℋ∞ control problem for one family of linear discrete-time systems over networks with packet loss, parametric uncertainties, and time-varying norm-bounded disturbance. Firstly, the dynamic model description studied is given, which, if the packet dropout is assumed to be a discrete-time homogenous Markov process, the class of discrete-time linear systems with packet loss can be regarded as Markovian jump systems. Based on Lyapunov function approach, sufficient conditions are established for the resulting closed-loop discrete-time system with Markovian jumps to be stochastic ℋ∞ finite-time boundedness and then state feedback controllers are designed to guarantee stochastic ℋ∞ finite-time stabilization of the class of stochastic systems. The stochastic ℋ∞ finite-time boundedness criteria can be tackled in the form of linear matrix inequalities with a fixed parameter. As an auxiliary result, we also give sufficient conditions on the robust stochastic stabilization of the class of linear systems with packet loss. Finally, simulation examples are presented to illustrate the validity of the developed scheme.
ITER technical advisory committee meeting at Garching
International Nuclear Information System (INIS)
Fujiwara, M.
1999-01-01
The ITER Technical Advisory Committee meeting took place on 24-27 February at the Garching Joint Work Site. According to the discussions at the ITER meeting in Yokohama in October 1998, the Technical Advisory Committee was requested to conduct a thorough review of the document 'Options for the reduced technical objectives / reduced cost ITER'
A Discrete-Time Geo/G/1 Retrial Queue with Two Different Types of Vacations
Directory of Open Access Journals (Sweden)
Feng Zhang
2015-01-01
Full Text Available We analyze a discrete-time Geo/G/1 retrial queue with two different types of vacations and general retrial times. Two different types of vacation policies are investigated in this model, one of which is nonexhaustive urgent vacation during serving and the other is normal exhaustive vacation. For this model, we give the steady-state analysis for the considered queueing system. Firstly, we obtain the generating functions of the number of customers in our model. Then, we obtain the closed-form expressions of some performance measures and also give a stochastic decomposition result for the system size. Moreover, the relationship between this discrete-time model and the corresponding continuous-time model is also investigated. Finally, some numerical results are provided to illustrate the effect of nonexhaustive urgent vacation on some performance characteristics of the system.
Discrete time population dynamics of a two-stage species with recruitment and capture
International Nuclear Information System (INIS)
Ladino, Lilia M.; Mammana, Cristiana; Michetti, Elisabetta; Valverde, Jose C.
2016-01-01
This work models and analyzes the dynamics of a two-stage species with recruitment and capture factors. It arises from the discretization of a previous model developed by Ladino and Valverde (2013), which represents a progress in the knowledge of the dynamics of exploited populations. Although the methods used here are related to the study of discrete-time systems and are different from those related to continuous version, the results are similar in both the discrete and the continuous case what confirm the skill in the selection of the factors to design the model. Unlike for the continuous-time case, for the discrete-time one some (non-negative) parametric constraints are derived from the biological significance of the model and become fundamental for the proofs of such results. Finally, numerical simulations show different scenarios of dynamics related to the analytical results which confirm the validity of the model.
Discrete time-crystalline order in black diamond
Zhou, Hengyun; Choi, Soonwon; Choi, Joonhee; Landig, Renate; Kucsko, Georg; Isoya, Junichi; Jelezko, Fedor; Onoda, Shinobu; Sumiya, Hitoshi; Khemani, Vedika; von Keyserlingk, Curt; Yao, Norman; Demler, Eugene; Lukin, Mikhail D.
2017-04-01
The interplay of periodic driving, disorder, and strong interactions has recently been predicted to result in exotic ``time-crystalline'' phases, which spontaneously break the discrete time-translation symmetry of the underlying drive. Here, we report the experimental observation of such discrete time-crystalline order in a driven, disordered ensemble of 106 dipolar spin impurities in diamond at room-temperature. We observe long-lived temporal correlations at integer multiples of the fundamental driving period, experimentally identify the phase boundary and find that the temporal order is protected by strong interactions; this order is remarkably stable against perturbations, even in the presence of slow thermalization. Our work opens the door to exploring dynamical phases of matter and controlling interacting, disordered many-body systems.
Parrondo's game using a discrete-time quantum walk
International Nuclear Information System (INIS)
Chandrashekar, C.M.; Banerjee, Subhashish
2011-01-01
We present a new form of a Parrondo game using discrete-time quantum walk on a line. The two players A and B with different quantum coins operators, individually losing the game can develop a strategy to emerge as joint winners by using their coins alternatively, or in combination for each step of the quantum walk evolution. We also present a strategy for a player A (B) to have a winning probability more than player B (A). Significance of the game strategy in information theory and physical applications are also discussed. - Highlights: → Novel form of Parrondo's game on a single particle discrete-time quantum walk. → Strategies for players to emerge as individual winners or as joint winners. → General framework for controlling and using quantum walk with multiple coins. → Strategies can be used in algorithms and situations involving directed motion.
Direct output feedback control of discrete-time systems
International Nuclear Information System (INIS)
Lin, C.C.; Chung, L.L.; Lu, K.H.
1993-01-01
An optimal direct output feedback control algorithm is developed for discrete-time systems with the consideration of time delay in control force action. Optimal constant output feedback gains are obtained through variational process such that certain prescribed quadratic performance index is minimized. Discrete-time control forces are then calculated from the multiplication of output measurements by these pre-calculated feedback gains. According to the proposed algorithm, structural system is assured to remain stable even in the presence of time delay. The number of sensors and controllers may be very small as compared with the dimension of states. Numerical results show that direct velocity feedback control is more sensitive to time delay than state feedback but, is still quite effective in reducing the dynamic responses under earthquake excitation. (author)
Zak Phase in Discrete-Time Quantum Walks
Puentes, G.; Santillán, O.
2015-01-01
We report on a simple scheme that may present a non-trivial geometric Zak phase ($\\Phi_{Zak}$) structure, which is based on a discrete-time quantum walk architecture. By detecting the Zak phase difference between two trajectories connecting adjacent Dirac points where the quasi-energy gap closes for opposite values of quasi-momentum ($k$), it is possible to identify geometric invariants. These geometric invariants correspond to $|\\Phi_{Zak}^{+(-)}-\\Phi_{Zak}^{-(+)}|=\\pi$ and $|\\Phi_{Zak}^{+(-...
Directory of Open Access Journals (Sweden)
Nurul Huda
2015-04-01
Full Text Available Objective - Islamic banks are banks which its activities, both fund raising and funds distribution are on the basis of Islamic principles, namely buying and selling and profit sharing. Islamic banking is aimed at supporting the implementation of national development in order to improve justice, togetherness, and equitable distribution of welfare. In pursuit of supporting the implementation of national development, Islamic banking often faced stability problems of financing instruments being operated. In this case, it is measured by the gap between the actual rate of return and the expected rate of return. The individual actual RoR of this instrument will generate an expected rate of return. This raises the gap or difference between the actual rate of return and the expected rate of return of individual instruments, which in this case is called the abnormal rate of return. The stability of abnormal rate of return of individual instruments is certainly influenced by the stability of the expected rate of return. Expected rate of return has a volatility or fluctuation levels for each financing instrument. It is also a key element or material basis for the establishment of a variance of individual instruments. Variance in this case indicates the level of uncertainty of the rate of return. Individual variance is the origin of the instrument base for variance in the portfolio finance that further a portfolio analysis. So, this paper is going to analyze the level of expected RoR volatility as an initial step to see and predict the stability of the fluctuations in the rate of return of Indonesian Islamic financing instruments.Methods – Probability of Occurence, Expected Rate of Return (RoR and GARCH (Generalized Autoregressive Conditional Heteroscedasticity.Results - The expected RoR volatility of the murabaha and istishna financing instruments tend to be more volatile than expected RoR volatility of musharaka and qardh financing instruments
Directory of Open Access Journals (Sweden)
Villalba Padilla, Fátima Irina
2014-12-01
Full Text Available Se parametriza de forma conjunta€€ la heteroscedasticidad condicional autorregresiva generalizada que corresponde al comportamiento de la varianza de tres variables: (a el índice de precios y cotizaciones (IPC, indicador principal del mercado bursátil mexicano, (b el emerging markets bond index para México (EMBI, como indicador de riesgo país y (c el precio de la canasta mexicana de tres crudos de exportación (MEZCLA. Las variables se emplean como estimadores de la tendencia de los precios de las acciones, los bonos y los energéticos, respectivamente, con el objetivo final de conformar un portafolio de inversión diversicado que incluya dichos activos. Se presentan los resultados empíricos de un modelo econométrico GARCH trivariado asimétrico. El modelo permite incorporar la covarianza entre las variables para explicar su interrelación y en la estimación se considera el efecto de los choques generados por las innovaciones positivas y negativas. El estudio contempla el periodo de 2002 a 2013. || We jointly parameterized the generalized autoregressive conditional heteroskedasticity that corresponds to the behavior of the variance of three variables: (a the core Mexican stock market index (IPC, (b the Emerging Markets Bond Index for Mexico (EMBI as country risk pointer and, (c the Mexican three oil basket exports mix (MEZCLA. The variables are used as trend indicators of stocks, bonds and energetics respectively with the ultimate goal of forming a diversified portfolio including such assets. This paper presents the empirical results of an asymmetric econometric trivariate GARCH model. The model incorporates the covariance between the variables in order to explain their relationship and we considered the shocks generated by positive and negative innovations. The study involves the period 2002- 2013.
International Nuclear Information System (INIS)
Janeschitz, G.; Connor, J.W.; Cordey, G.; Kardaun, O.; Mukhovatov, V.; Stambaugh, R.; Ryter, F.; Wakatani, M.
1999-01-01
This contribution to the ITER EDA Newsletter reports on the combined meeting of the core confinement and internal transport barrier expert group, confinement database and modeling expert group and edge pedestal expert group in Garching, Germany. This is the first workshop of its kind after the re-organisation of the expert groups. The new scheme of the meetings, namely to permit more interaction between groups by arranging them at the same time and location turned out to be very successful. The main issues discussed were for the Confinement Database: merging of edge pedestal and confinement data, improvement of the density- and magnetic shape parameters, addition of new dedicated threshold data, the effect of different divertors in JET; for the H-Mode Power Threshold Database: assembly of a new version of the database with about 650 time points from 10 tokamaks; for the 1-D Modelling Workshop: management of the database after the re-organisation of the Joint Central Team an ongoing efforts in plasma transport modelling; for the newly formed pedestal group: issues of the H-mode shear layer at the plasma edge. There was also an executive summary given of a recent USA workshop on internal transport barriers and regimes with weak or negative magnetic shear
Robust Active MPC Synchronization for Two Discrete-Time Chaotic Systems with Bounded Disturbance
Directory of Open Access Journals (Sweden)
Longge Zhang
2017-01-01
Full Text Available This paper proposes a synchronization scheme for two discrete-time chaotic systems with bounded disturbance. By using active control method and imposing some restriction on the error state, the computation of controller’s feedback matrix is converted to the min-max optimization problem. The theoretical results are derived with the aid of predictive model predictive paradigm and linear matrix inequality technique. Two example simulations are performed to show the effectiveness of the designed control method.
12 May 1979: 'Atom Disaster' in Garching
International Nuclear Information System (INIS)
Gerwin, R.
1979-01-01
'Die Zeit', in its number 25 (15 June 79), dealt with the mass media's reporting on a fire in a laboratory of the Technical University of Munich in Garching (District Munich) of 12 May 79. Under the headline 'After the fire in Garching - sensations at any price. The fire provoked the journalists' imagination', Robert Gerwin, the press agent of the Max Planck Society, dealt with the question of whether or not the TV and newspapers' reports on this fire were extremely exaggerating, suggesting the readers a sensation which was no sensation at all. The press section of the Max Planck Society kindly gave its permission to print this article in 'brandschutz'. (orig./HP) [de
Symposium on disruptive instabilities at Garching
International Nuclear Information System (INIS)
Lackner, K.
1979-01-01
The phenomenon of disruptive instabilities was investigated with a special care at the IPP at Garching. After lectures and panel sessions it appears suitable, to subdivide the disruptive phenomena into four classes: 1. The internal disruption (the socalled saw-tooth oscillators). 2. the socalled reconnection disruptions. 3. The large disruptions. 4. The small disruptions. The four appearance forms of the phenomena are briefly explained. (GG) [de
Importance of the macroeconomic variables for variance prediction: A GARCH-MIDAS approach
DEFF Research Database (Denmark)
Asgharian, Hossein; Hou, Ai Jun; Javed, Farrukh
2013-01-01
This paper aims to examine the role of macroeconomic variables in forecasting the return volatility of the US stock market. We apply the GARCH-MIDAS (Mixed Data Sampling) model to examine whether information contained in macroeconomic variables can help to predict short-term and long-term compone......This paper aims to examine the role of macroeconomic variables in forecasting the return volatility of the US stock market. We apply the GARCH-MIDAS (Mixed Data Sampling) model to examine whether information contained in macroeconomic variables can help to predict short-term and long...
Discrete-time Calogero-Moser system and Lagrangian 1-form structure
International Nuclear Information System (INIS)
Yoo-Kong, Sikarin; Lobb, Sarah; Nijhoff, Frank
2011-01-01
We study the Lagrange formalism of the (rational) Calogero-Moser (CM) system, both in discrete time and continuous time, as a first example of a Lagrangian 1-form structure in the sense of the recent paper (Lobb and Nijhoff 2009 J. Phys. A: Math. Theor.42 454013). The discrete-time model of the CM system was established some time ago arising as a pole reduction of a semi-discrete version of the Kadomtsev-Petviashvili (KP) equation, and was shown to lead to an exactly integrable correspondence (multivalued map). In this paper, we present the full KP solution based on the commutativity of the discrete-time flows in the two discrete KP variables. The compatibility of the corresponding Lax matrices is shown to lead directly to the relevant closure relation on the level of the Lagrangians. Performing successive continuum limits on both the level of the KP equation and the level of the CM system, we establish the proper Lagrangian 1-form structure for the continuum case of the CM model. We use the example of the three-particle case to elucidate the implementation of the novel least-action principle, which was presented in Lobb and Nijhoff (2009), for the simpler case of Lagrangian 1-forms. (paper)
Mapping of uncertainty relations between continuous and discrete time.
Chiuchiù, Davide; Pigolotti, Simone
2018-03-01
Lower bounds on fluctuations of thermodynamic currents depend on the nature of time, discrete or continuous. To understand the physical reason, we compare current fluctuations in discrete-time Markov chains and continuous-time master equations. We prove that current fluctuations in the master equations are always more likely, due to random timings of transitions. This comparison leads to a mapping of the moments of a current between discrete and continuous time. We exploit this mapping to obtain uncertainty bounds. Our results reduce the quests for uncertainty bounds in discrete and continuous time to a single problem.
Optimal Robust Fault Detection for Linear Discrete Time Systems
Directory of Open Access Journals (Sweden)
Nike Liu
2008-01-01
Full Text Available This paper considers robust fault-detection problems for linear discrete time systems. It is shown that the optimal robust detection filters for several well-recognized robust fault-detection problems, such as ℋ−/ℋ∞, ℋ2/ℋ∞, and ℋ∞/ℋ∞ problems, are the same and can be obtained by solving a standard algebraic Riccati equation. Optimal filters are also derived for many other optimization criteria and it is shown that some well-studied and seeming-sensible optimization criteria for fault-detection filter design could lead to (optimal but useless fault-detection filters.
Discrete-time BAM neural networks with variable delays
Liu, Xin-Ge; Tang, Mei-Lan; Martin, Ralph; Liu, Xin-Bi
2007-07-01
This Letter deals with the global exponential stability of discrete-time bidirectional associative memory (BAM) neural networks with variable delays. Using a Lyapunov functional, and linear matrix inequality techniques (LMI), we derive a new delay-dependent exponential stability criterion for BAM neural networks with variable delays. As this criterion has no extra constraints on the variable delay functions, it can be applied to quite general BAM neural networks with a broad range of time delay functions. It is also easy to use in practice. An example is provided to illustrate the theoretical development.
Discrete-time BAM neural networks with variable delays
International Nuclear Information System (INIS)
Liu Xinge; Tang Meilan; Martin, Ralph; Liu Xinbi
2007-01-01
This Letter deals with the global exponential stability of discrete-time bidirectional associative memory (BAM) neural networks with variable delays. Using a Lyapunov functional, and linear matrix inequality techniques (LMI), we derive a new delay-dependent exponential stability criterion for BAM neural networks with variable delays. As this criterion has no extra constraints on the variable delay functions, it can be applied to quite general BAM neural networks with a broad range of time delay functions. It is also easy to use in practice. An example is provided to illustrate the theoretical development
A parametric LTR solution for discrete-time systems
DEFF Research Database (Denmark)
Niemann, Hans Henrik; Jannerup, Ole Erik
1989-01-01
A parametric LTR (loop transfer recovery) solution for discrete-time compensators incorporating filtering observers which achieve exact recovery is presented for both minimum- and non-minimum-phase systems. First the recovery error, which defines the difference between the target loop transfer...... and the full loop transfer function, is manipulated into a general form involving the target loop transfer matrix and the fundamental recovery matrix. A parametric LTR solution based on the recovery matrix is developed. It is shown that the LQR/LTR (linear quadratic Gaussian/loop transfer recovery) solution...
On Stochastic Finite-Time Control of Discrete-Time Fuzzy Systems with Packet Dropout
Directory of Open Access Journals (Sweden)
Yingqi Zhang
2012-01-01
Full Text Available This paper is concerned with the stochastic finite-time stability and stochastic finite-time boundedness problems for one family of fuzzy discrete-time systems over networks with packet dropout, parametric uncertainties, and time-varying norm-bounded disturbance. Firstly, we present the dynamic model description studied, in which the discrete-time fuzzy T-S systems with packet loss can be described by one class of fuzzy Markovian jump systems. Then, the concepts of stochastic finite-time stability and stochastic finite-time boundedness and problem formulation are given. Based on Lyapunov function approach, sufficient conditions on stochastic finite-time stability and stochastic finite-time boundedness are established for the resulting closed-loop fuzzy discrete-time system with Markovian jumps, and state-feedback controllers are designed to ensure stochastic finite-time stability and stochastic finite-time boundedness of the class of fuzzy systems. The stochastic finite-time stability and stochastic finite-time boundedness criteria can be tackled in the form of linear matrix inequalities with a fixed parameter. As an auxiliary result, we also give sufficient conditions on the stochastic stability of the class of fuzzy T-S systems with packet loss. Finally, two illustrative examples are presented to show the validity of the developed methodology.
Neutrino oscillations in discrete-time quantum walk framework
Energy Technology Data Exchange (ETDEWEB)
Mallick, Arindam; Mandal, Sanjoy; Chandrashekar, C.M. [C. I. T. Campus, The Institute of Mathematical Sciences, Chennai (India); Homi Bhabha National Institute, Training School Complex, Mumbai (India)
2017-02-15
Here we present neutrino oscillation in the framework of quantum walks. Starting from a one spatial dimensional discrete-time quantum walk we present a scheme of evolutions that will simulate neutrino oscillation. The set of quantum walk parameters which is required to reproduce the oscillation probability profile obtained in both, long range and short range neutrino experiment is explicitly presented. Our scheme to simulate three-generation neutrino oscillation from quantum walk evolution operators can be physically realized in any low energy experimental set-up with access to control a single six-level system, a multiparticle three-qubit or a qubit-qutrit system. We also present the entanglement between spins and position space, during neutrino propagation that will quantify the wave function delocalization around instantaneous average position of the neutrino. This work will contribute towards understanding neutrino oscillation in the framework of the quantum information perspective. (orig.)
Adaptive Control and Function Projective Synchronization in 2D Discrete-Time Chaotic Systems
International Nuclear Information System (INIS)
Li Yin; Chen Yong; Li Biao
2009-01-01
This study addresses the adaptive control and function projective synchronization problems between 2D Rulkov discrete-time system and Network discrete-time system. Based on backstepping design with three controllers, a systematic, concrete and automatic scheme is developed to investigate the function projective synchronization of discrete-time chaotic systems. In addition, the adaptive control function is applied to achieve the state synchronization of two discrete-time systems. Numerical results demonstrate the effectiveness of the proposed control scheme.
Directory of Open Access Journals (Sweden)
Václav Klepáč
2015-01-01
Full Text Available The article points out the possibilities of using static D-Vine copula ARMA-GARCH model for estimation of 1 day ahead market Value at Risk. For the illustration we use data of the four companies listed on Prague Stock Exchange in range from 2010 to 2014. Vine copula approach allows us to construct high-dimensional copula from both elliptical and Archimedean bivariate copulas, i.e. multivariate probability distribution, created from process innovations. Due to a deeper shortage of existing domestic results or comparison studies with advanced volatility governed VaR forecasts we backtested D-Vine copula ARMA-GARCH model against the VaR rolling out of sample forecast from October 2012 to April 2014 of chosen benchmark models, e.g. multivariate VAR-GO-GARCH, VAR-DCC-GARCH and univariate ARMA-GARCH type models. Common backtesting via Kupiec and Christoffersen procedures offer generalization that technological superiority of model supports accuracy only in case of an univariate modeling – working with non-basic GARCH models and innovations with leptokurtic distributions. Multivariate VAR governed type models and static Copula Vines performed in stated backtesting comparison worse than selected univariate ARMA-GARCH, i.e. it have overestimated the level of actual market risk, probably due to hardly tractable time-varying dependence structure.
Day of the week effect on the Zimbabwe Stock Exchange: A non-linear GARCH analysis
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Batsirai Winmore Mazviona
2015-11-01
Full Text Available This study analysed the day of the week effect on the Zimbabwe Stock Exchange (ZSE by taking into account volatility of returns. The purpose of the study was to establish whether daily mean returns across a trading week differ from each other. We employ a non-linear approach in modelling the day of the week effects. In particular, we used the Generalised Autoregressive Conditional Heteroscedasticity (GARCH and the Exponential GARCH (EGARCH models. We used industrial and mining daily closing indices data from 19 February 2009 to 31 December 2013. The data was retrieved from the ZSE website. EViews 7 software was utilised for data analysis. In order to test the null hypothesis of equality of daily mean returns, a Wald test was carried out. The Wald F-statistic rejected the null hypothesis of equality of mean returns for the industrial index. We found the traditional negative Monday and positive Friday effect for the industrial index in GARCH (1,1 and EGARCH (1,1 models. The GARCH (1,1 detected a negative Friday effect and the EGARCH (1,1 detected negative Wednesday effect for the mining index. We found evidence of model dependency for the mining index results.
A Spectral Analysis of Discrete-Time Quantum Walks Related to the Birth and Death Chains
Ho, Choon-Lin; Ide, Yusuke; Konno, Norio; Segawa, Etsuo; Takumi, Kentaro
2018-04-01
In this paper, we consider a spectral analysis of discrete time quantum walks on the path. For isospectral coin cases, we show that the time averaged distribution and stationary distributions of the quantum walks are described by the pair of eigenvalues of the coins as well as the eigenvalues and eigenvectors of the corresponding random walks which are usually referred as the birth and death chains. As an example of the results, we derive the time averaged distribution of so-called Szegedy's walk which is related to the Ehrenfest model. It is represented by Krawtchouk polynomials which is the eigenvectors of the model and includes the arcsine law.
Synchronization of discrete-time spatiotemporal chaos via adaptive fuzzy control
International Nuclear Information System (INIS)
Xue Yueju; Yang Shiyuan
2003-01-01
A discrete-time adaptive fuzzy control scheme is presented to synchronize model-unknown coupled Henon-map lattices (CHMLs). The proposed method is robust to approximate errors, parameter mismatches and disturbances, because it integrates the merits of the adaptive fuzzy systems and the variable structure control with a sector. The simulation results of synchronization of CHMLs show that it not only can synchronize model-unknown CHMLs but also is robust against parameter mismatches and noise of the systems. These merits are advantageous for engineering realization
Synchronization of discrete-time spatiotemporal chaos via adaptive fuzzy control
Energy Technology Data Exchange (ETDEWEB)
Xue Yueju E-mail: xueyj@mail.tsinghua.edu.cn; Yang Shiyuan E-mail: ysy-dau@tsinghua.edu.cn
2003-08-01
A discrete-time adaptive fuzzy control scheme is presented to synchronize model-unknown coupled Henon-map lattices (CHMLs). The proposed method is robust to approximate errors, parameter mismatches and disturbances, because it integrates the merits of the adaptive fuzzy systems and the variable structure control with a sector. The simulation results of synchronization of CHMLs show that it not only can synchronize model-unknown CHMLs but also is robust against parameter mismatches and noise of the systems. These merits are advantageous for engineering realization.
Directory of Open Access Journals (Sweden)
Maode Yan
2008-01-01
Full Text Available This paper considers the problem of robust discrete-time sliding-mode control (DT-SMC design for a class of uncertain linear systems with time-varying delays. By applying a descriptor model transformation and Moon's inequality for bounding cross terms, a delay-dependent sufficient condition for the existence of stable sliding surface is given in terms of linear matrix inequalities (LMIs. Based on this existence condition, the synthesized sliding mode controller can guarantee the sliding-mode reaching condition of the specified discrete-time sliding surface for all admissible uncertainties and time-varying delays. An illustrative example verifies the effectiveness of the proposed method.
Liang, Hongjing; Zhang, Huaguang; Wang, Zhanshan
2015-11-01
This paper considers output synchronization of discrete-time multi-agent systems with directed communication topologies. The directed communication graph contains a spanning tree and the exosystem as its root. Distributed observer-based consensus protocols are proposed, based on the relative outputs of neighboring agents. A multi-step algorithm is presented to construct the observer-based protocols. In light of the discrete-time algebraic Riccati equation and internal model principle, synchronization problem is completed. At last, numerical simulation is provided to verify the effectiveness of the theoretical results. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.
Positive dynamical systems in discrete time theory, models, and applications
Krause, Ulrich
2015-01-01
This book provides a systematic, rigorous and self-contained treatment of positive dynamical systems. A dynamical system is positive when all relevant variables of a systemare nonnegative in a natural way. This is in biology, demography or economics, where the levels of populations or prices of goods are positive. The principle also finds application in electrical engineering, physics and computer sciences.
A modified GO-FLOW methodology with common cause failure based on Discrete Time Bayesian Network
International Nuclear Information System (INIS)
Fan, Dongming; Wang, Zili; Liu, Linlin; Ren, Yi
2016-01-01
Highlights: • Identification of particular causes of failure for common cause failure analysis. • Comparison two formalisms (GO-FLOW and Discrete Time Bayesian network) and establish the correlation between them. • Mapping the GO-FLOW model into Bayesian network model. • Calculated GO-FLOW model with common cause failures based on DTBN. - Abstract: The GO-FLOW methodology is a success-oriented system reliability modelling technique for multi-phase missions involving complex time-dependent, multi-state and common cause failure (CCF) features. However, the analysis algorithm cannot easily handle the multiple shared signals and CCFs. In addition, the simulative algorithm is time consuming when vast multi-state components exist in the model, and the multiple time points of phased mission problems increases the difficulty of the analysis method. In this paper, the Discrete Time Bayesian Network (DTBN) and the GO-FLOW methodology are integrated by the unified mapping rules. Based on these rules, the multi operators can be mapped into DTBN followed by, a complete GO-FLOW model with complex characteristics (e.g. phased mission, multi-state, and CCF) can be converted to the isomorphic DTBN and easily analyzed by utilizing the DTBN. With mature algorithms and tools, the multi-phase mission reliability parameter can be efficiently obtained via the proposed approach without considering the shared signals and the various complex logic operation. Meanwhile, CCF can also arise in the computing process.
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John Cortés-Romero
2013-01-01
Full Text Available The problem of active disturbance rejection control of induction motors is tackled by means of a generalized PI observer based discrete-time control, using the delta operator approach as the methodology of analyzing the sampled time process. In this scheme, model uncertainties and external disturbances are included in a general additive disturbance input which is to be online estimated and subsequently rejected via the controller actions. The observer carries out the disturbance estimation, thus reducing the complexity of the controller design. The controller efficiency is tested via some experimental results, performing a trajectory tracking task under load variations.
Parent-child communication and marijuana initiation: evidence using discrete-time survival analysis.
Nonnemaker, James M; Silber-Ashley, Olivia; Farrelly, Matthew C; Dench, Daniel
2012-12-01
This study supplements existing literature on the relationship between parent-child communication and adolescent drug use by exploring whether parental and/or adolescent recall of specific drug-related conversations differentially impact youth's likelihood of initiating marijuana use. Using discrete-time survival analysis, we estimated the hazard of marijuana initiation using a logit model to obtain an estimate of the relative risk of initiation. Our results suggest that parent-child communication about drug use is either not protective (no effect) or - in the case of youth reports of communication - potentially harmful (leading to increased likelihood of marijuana initiation). Copyright © 2012 Elsevier Ltd. All rights reserved.
Advanced discrete-time control designs and applications
Abidi, Khalid
2015-01-01
This book covers a wide spectrum of systems such as linear and nonlinear multivariable systems as well as control problems such as disturbance, uncertainty and time-delays. The purpose of this book is to provide researchers and practitioners a manual for the design and application of advanced discrete-time controllers. The book presents six different control approaches depending on the type of system and control problem. The first and second approaches are based on Sliding Mode control (SMC) theory and are intended for linear systems with exogenous disturbances. The third and fourth approaches are based on adaptive control theory and are aimed at linear/nonlinear systems with periodically varying parametric uncertainty or systems with input delay. The fifth approach is based on Iterative learning control (ILC) theory and is aimed at uncertain linear/nonlinear systems with repeatable tasks and the final approach is based on fuzzy logic control (FLC) and is intended for highly uncertain systems with heuristi...
Risk-based design of process systems using discrete-time Bayesian networks
International Nuclear Information System (INIS)
Khakzad, Nima; Khan, Faisal; Amyotte, Paul
2013-01-01
Temporal Bayesian networks have gained popularity as a robust technique to model dynamic systems in which the components' sequential dependency, as well as their functional dependency, cannot be ignored. In this regard, discrete-time Bayesian networks have been proposed as a viable alternative to solve dynamic fault trees without resort to Markov chains. This approach overcomes the drawbacks of Markov chains such as the state-space explosion and the error-prone conversion procedure from dynamic fault tree. It also benefits from the inherent advantages of Bayesian networks such as probability updating. However, effective mapping of the dynamic gates of dynamic fault trees into Bayesian networks while avoiding the consequent huge multi-dimensional probability tables has always been a matter of concern. In this paper, a new general formalism has been developed to model two important elements of dynamic fault tree, i.e., cold spare gate and sequential enforcing gate, with any arbitrary probability distribution functions. Also, an innovative Neutral Dependency algorithm has been introduced to model dynamic gates such as priority-AND gate, thus reducing the dimension of conditional probability tables by an order of magnitude. The second part of the paper is devoted to the application of discrete-time Bayesian networks in the risk assessment and safety analysis of complex process systems. It has been shown how dynamic techniques can effectively be applied for optimal allocation of safety systems to obtain maximum risk reduction.
Modeling the return and volatility of the Greek electricity marginal system price
International Nuclear Information System (INIS)
Theodorou, Petros; Karyampas, Dimitrios
2008-01-01
Traditional cost based optimization models (WASP) for expansion planning do not allow for mark-to-market valuation and cannot satisfy arbitrage free requirements. This work will fill this gap by developing and estimating models for mark-to-market valuation. Furthermore the present paper examines the return and volatility of the newly born Greek's electricity market's marginal system price. A detailed description of the market mechanism and regulation is used to describe how prices are determined in order to proceed with return and volatility modeling. Continuous time mean reverting and time varying mean reverting stochastic processes have been solved in discrete time processes and estimated econometrically along with ARMAX and GARCH models. It was found that GARCH model gave much better estimation and forecasting ability. Strong persistence in mean has been found giving suspicions of market inefficiency and strong incentives for arbitrage opportunities. Finally, the change in the regulatory framework has been controlled and found to have significant impact. (author)
Generation of a quantum integrable class of discrete-time or relativistic periodic Toda chains
International Nuclear Information System (INIS)
Kundu, Anjan
1994-01-01
A new integrable class of quantum models representing a family of different discrete-time or relativistic generalisations of the periodic Toda chain (TC), including that of a recently proposed classical model close to TC [Lett. Math. Phys. 29 (1993) 165] is presented. All such models are shown to be obtainable from a single ancestor model at different realisations of the underlying quantised algebra. As a consequence the 2x2 Lax operators and the associated quantum R-matrices for these models are easily derived ensuring their quantum integrability. It is shown that the functional Bethe ansatz developed for the quantum TC is trivially generalised to achieve separation of variables also for the present models. ((orig.))
CONTINUOUS MODELING OF FOREIGN EXCHANGE RATE OF USD VERSUS TRY
Directory of Open Access Journals (Sweden)
Yakup Arı
2011-01-01
Full Text Available This study aims to construct continuous-time autoregressive (CAR model and continuous-time GARCH (COGARCH model from discrete time data of foreign exchange rate of United States Dollar (USD versus Turkish Lira (TRY. These processes are solutions to stochastic differential equation Lévy-driven processes. We have shown that CAR(1 and COGARCH(1,1 processes are proper models to represent foreign exchange rate of USD and TRY for different periods of time February 2002- June 2010.
Hopf Bifurcation Analysis for a Stochastic Discrete-Time Hyperchaotic System
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Jie Ran
2015-01-01
Full Text Available The dynamics of a discrete-time hyperchaotic system and the amplitude control of Hopf bifurcation for a stochastic discrete-time hyperchaotic system are investigated in this paper. Numerical simulations are presented to exhibit the complex dynamical behaviors in the discrete-time hyperchaotic system. Furthermore, the stochastic discrete-time hyperchaotic system with random parameters is transformed into its equivalent deterministic system with the orthogonal polynomial theory of discrete random function. In addition, the dynamical features of the discrete-time hyperchaotic system with random disturbances are obtained through its equivalent deterministic system. By using the Hopf bifurcation conditions of the deterministic discrete-time system, the specific conditions for the existence of Hopf bifurcation in the equivalent deterministic system are derived. And the amplitude control with random intensity is discussed in detail. Finally, the feasibility of the control method is demonstrated by numerical simulations.
Value-at-Risk for South-East Asian Stock Markets: Stochastic Volatility vs. GARCH
Directory of Open Access Journals (Sweden)
Paul Bui Quang
2018-04-01
Full Text Available This study compares the performance of several methods to calculate the Value-at-Risk of the six main ASEAN stock markets. We use filtered historical simulations, GARCH models, and stochastic volatility models. The out-of-sample performance is analyzed by various backtesting procedures. We find that simpler models fail to produce sufficient Value-at-Risk forecasts, which appears to stem from several econometric properties of the return distributions. With stochastic volatility models, we obtain better Value-at-Risk forecasts compared to GARCH. The quality varies over forecasting horizons and across markets. This indicates that, despite a regional proximity and homogeneity of the markets, index volatilities are driven by different factors.
A Discrete-Time Queue with Balking, Reneging, and Working Vacations
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Veena Goswami
2014-01-01
Full Text Available This paper presents an analysis of balking and reneging in finite-buffer discrete-time single server queue with single and multiple working vacations. An arriving customer may balk with a probability or renege after joining according to a geometric distribution. The server works with different service rates rather than completely stopping the service during a vacation period. The service times during a busy period, vacation period, and vacation times are assumed to be geometrically distributed. We find the explicit expressions for the stationary state probabilities. Various system performance measures and a cost model to determine the optimal service rates are presented. Moreover, some queueing models presented in the literature are derived as special cases of our model. Finally, the influence of various parameters on the performance characteristics is shown numerically.
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.
Nonlinear Estimation of Discrete-Time Signals Under Random Observation Delay
International Nuclear Information System (INIS)
Caballero-Aguila, R.; Jimenez-Lopez, J. D.; Hermoso-Carazo, A.; Linares-Perez, J.; Nakamori, S.
2008-01-01
This paper presents an approximation to the nonlinear least-squares estimation problem of discrete-time stochastic signals using nonlinear observations with additive white noise which can be randomly delayed by one sampling time. The observation delay is modelled by a sequence of independent Bernoulli random variables whose values, zero or one, indicate that the real observation arrives on time or it is delayed and, hence, the available measurement to estimate the signal is not up-to-date. Assuming that the state-space model generating the signal is unknown and only the covariance functions of the processes involved in the observation equation are ready for use, a filtering algorithm based on linear approximations of the real observations is proposed.
MEMBANDINGKAN RISIKO SISTEMATIS MENGGUNAKAN CAPM-GARCH DAN CAPM-EGARCH
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VIKY AMELIAH
2017-11-01
Full Text Available In making stock investments, investors usually pay attention to the rate of return and risk of the stock investment. To calculate risk using capital asset pricing model (CAPM, GARCH, and EGARCH. The data used in this study is secondary data in the form of daily closing price (daily close price, JII price index and monthly SBI rate. All data were processed using matlab 13. The research sample consisted of 6 flagship shares for the period of 2013-2017 ie ADHI, SMGR, UNTR, BSDE, ICBP, KLBF. The conclusion of the research is the beta of each stock including aggressive beta because beta greater than 1. For return CAPM GARACH and CAPM EGARCH obtained Kalbe Farma stock (KLBF has small beta and big return means GARCH and EGARCH model equally Can predict that stock KLBF shares the least risk and large returns among the six stocks.
Estimation of value at risk in currency exchange rate portfolio using asymmetric GJR-GARCH Copula
Nurrahmat, Mohamad Husein; Noviyanti, Lienda; Bachrudin, Achmad
2017-03-01
In this study, we discuss the problem in measuring the risk in a portfolio based on value at risk (VaR) using asymmetric GJR-GARCH Copula. The approach based on the consideration that the assumption of normality over time for the return can not be fulfilled, and there is non-linear correlation for dependent model structure among the variables that lead to the estimated VaR be inaccurate. Moreover, the leverage effect also causes the asymmetric effect of dynamic variance and shows the weakness of the GARCH models due to its symmetrical effect on conditional variance. Asymmetric GJR-GARCH models are used to filter the margins while the Copulas are used to link them together into a multivariate distribution. Then, we use copulas to construct flexible multivariate distributions with different marginal and dependence structure, which is led to portfolio joint distribution does not depend on the assumptions of normality and linear correlation. VaR obtained by the analysis with confidence level 95% is 0.005586. This VaR derived from the best Copula model, t-student Copula with marginal distribution of t distribution.
LQR-Based Optimal Distributed Cooperative Design for Linear Discrete-Time Multiagent Systems.
Zhang, Huaguang; Feng, Tao; Liang, Hongjing; Luo, Yanhong
2017-03-01
In this paper, a novel linear quadratic regulator (LQR)-based optimal distributed cooperative design method is developed for synchronization control of general linear discrete-time multiagent systems on a fixed, directed graph. Sufficient conditions are derived for synchronization, which restrict the graph eigenvalues into a bounded circular region in the complex plane. The synchronizing speed issue is also considered, and it turns out that the synchronizing region reduces as the synchronizing speed becomes faster. To obtain more desirable synchronizing capacity, the weighting matrices are selected by sufficiently utilizing the guaranteed gain margin of the optimal regulators. Based on the developed LQR-based cooperative design framework, an approximate dynamic programming technique is successfully introduced to overcome the (partially or completely) model-free cooperative design for linear multiagent systems. Finally, two numerical examples are given to illustrate the effectiveness of the proposed design methods.
Decentralized Observer with a Consensus Filter for Distributed Discrete-Time Linear Systems
Acikmese, Behcet; Mandic, Milan
2011-01-01
This paper presents a decentralized observer with a consensus filter for the state observation of a discrete-time linear distributed systems. In this setup, each agent in the distributed system has an observer with a model of the plant that utilizes the set of locally available measurements, which may not make the full plant state detectable. This lack of detectability is overcome by utilizing a consensus filter that blends the state estimate of each agent with its neighbors' estimates. We assume that the communication graph is connected for all times as well as the sensing graph. It is proven that the state estimates of the proposed observer asymptotically converge to the actual plant states under arbitrarily changing, but connected, communication and sensing topologies. As a byproduct of this research, we also obtained a result on the location of eigenvalues, the spectrum, of the Laplacian for a family of graphs with self-loops.
Directory of Open Access Journals (Sweden)
Yunjie Wu
2013-01-01
Full Text Available In order to improve the tracking accuracy of flight simulator and expend its frequency response, a multirate-sampling-method-based discrete-time chattering free sliding mode control is developed and imported into the systems. By constructing the multirate sampling sliding mode controller, the flight simulator can perfectly track a given reference signal with an arbitrarily small dynamic tracking error, and the problems caused by a contradiction of reference signal period and control period in traditional design method can be eliminated. It is proved by theoretical analysis that the extremely high dynamic tracking precision can be obtained. Meanwhile, the robustness is guaranteed by sliding mode control even though there are modeling mismatch, external disturbances and measure noise. The validity of the proposed method is confirmed by experiments on flight simulator.
Directory of Open Access Journals (Sweden)
Jian Ding
2014-01-01
Full Text Available This paper addresses the problem of P-type iterative learning control for a class of multiple-input multiple-output linear discrete-time systems, whose aim is to develop robust monotonically convergent control law design over a finite frequency range. It is shown that the 2 D iterative learning control processes can be taken as 1 D state space model regardless of relative degree. With the generalized Kalman-Yakubovich-Popov lemma applied, it is feasible to describe the monotonically convergent conditions with the help of linear matrix inequality technique and to develop formulas for the control gain matrices design. An extension to robust control law design against systems with structured and polytopic-type uncertainties is also considered. Two numerical examples are provided to validate the feasibility and effectiveness of the proposed method.
PERHITUNGAN NILAI BETA DARI BEBERAPA SAHAM UNGGULAN DI INDONESIA DENGAN MENGGUNAKAN METODE GARCH
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NI KADEK PUSPITAYANTI
2016-05-01
Full Text Available The objective of investment in the capital market is to acquire dividends and capital gain. The fact proves that the advantage of investation risky assets is uncertain . This is because of the difficulty in analyzing and predicting Return and stock losses due to factors that affect the movement of the stock price , such as economic factors , political , social , and security. The model can be used by investors in predicting stock returns expected that Generalized Autoregressive Conditional Heteroscedaticity (GARCH. In this study calculations beta value of some leading stocks in Indonesia by using Generalized Autoregressive Conditional Heteroscedaticity (GARCH are presented . The data used this search is secondary data covering daily data sampled 5 shares of PT Unilever Indonesia Tbk , PT Indosat Tbk , PT Indofood Sukses Makmur Tbk , PT Telkom Indonesia Tbk , PT Holcim Indonesia Tbk. From the results described fifth beta value of these shares using the method GARCH beta greater than the market in the period from 23 September 2013 until 24 September 2014.
Yu, Jinpeng; Shi, Peng; Yu, Haisheng; Chen, Bing; Lin, Chong
2015-07-01
This paper considers the problem of discrete-time adaptive position tracking control for a interior permanent magnet synchronous motor (IPMSM) based on fuzzy-approximation. Fuzzy logic systems are used to approximate the nonlinearities of the discrete-time IPMSM drive system which is derived by direct discretization using Euler method, and a discrete-time fuzzy position tracking controller is designed via backstepping approach. In contrast to existing results, the advantage of the scheme is that the number of the adjustable parameters is reduced to two only and the problem of coupling nonlinearity can be overcome. It is shown that the proposed discrete-time fuzzy controller can guarantee the tracking error converges to a small neighborhood of the origin and all the signals are bounded. Simulation results illustrate the effectiveness and the potentials of the theoretic results obtained.
Decentralized control of discrete-time linear time invariant systems with input saturation
Deliu, Ciprian; Deliu, C.; Malek, Babak; Roy, Sandip; Saberi, Ali; Stoorvogel, Antonie Arij
2009-01-01
We study decentralized stabilization of discrete time linear time invariant (LTI) systems subject to actuator saturation, using LTI controllers. The requirement of stabilization under both saturation constraints and decentralization impose obvious necessary conditions on the open-loop plant, namely
A continuous-time/discrete-time mixed audio-band sigma delta ADC
International Nuclear Information System (INIS)
Liu Yan; Hua Siliang; Wang Donghui; Hou Chaohuan
2011-01-01
This paper introduces a mixed continuous-time/discrete-time, single-loop, fourth-order, 4-bit audio-band sigma delta ADC that combines the benefits of continuous-time and discrete-time circuits, while mitigating the challenges associated with continuous-time design. Measurement results show that the peak SNR of this ADC reaches 100 dB and the total power consumption is less than 30 mW. (semiconductor integrated circuits)
Function Projective Synchronization in Discrete-Time Chaotic System with Uncertain Parameters
International Nuclear Information System (INIS)
Chen Yong; Li Xin
2009-01-01
The function projective synchronization of discrete-time chaotic systems is presented. Based on backstepping design with three controllers, a systematic, concrete and automatic scheme is developed to investigate function projective synchronization (FPS) of discrete-time chaotic systems with uncertain parameters. With the aid of symbolic-numeric computation, we use the proposed scheme to illustrate FPS between two identical 3D Henon-like maps with uncertain parameters. Numeric simulations are used to verify the effectiveness of our scheme. (general)
Control of the formation of projective synchronisation in lower-dimensional discrete-time systems
International Nuclear Information System (INIS)
Chee, C.Y.; Xu Daolin
2003-01-01
Projective synchronisation was recently observed in partially linear discrete-time systems. The scaling factor that characterises the behaviour of projective synchronisation is however unpredictable. In order to manipulate the ultimate state of the synchronisation, a control algorithm based on Schur-Chon stability criteria is proposed to direct the scaling factor onto any predestined value. In the numerical experiment, we illustrate the application on two chaotic discrete-time systems
On Discrete Time Control of Continuous Time Systems
DEFF Research Database (Denmark)
Poulsen, Niels Kjølstad
This report is meant as a supplement or an extension to the material used in connection to or after the courses Stochastic Adaptive Control (02421) and Static and Dynamic Optimization (02711) given at the department Department of Informatics and Mathematical Modelling, The Technical University...
Informational and Causal Architecture of Discrete-Time Renewal Processes
Directory of Open Access Journals (Sweden)
Sarah E. Marzen
2015-07-01
Full Text Available Renewal processes are broadly used to model stochastic behavior consisting of isolated events separated by periods of quiescence, whose durations are specified by a given probability law. Here, we identify the minimal sufficient statistic for their prediction (the set of causal states, calculate the historical memory capacity required to store those states (statistical complexity, delineate what information is predictable (excess entropy, and decompose the entropy of a single measurement into that shared with the past, future, or both. The causal state equivalence relation defines a new subclass of renewal processes with a finite number of causal states despite having an unbounded interevent count distribution. We use the resulting formulae to analyze the output of the parametrized Simple Nonunifilar Source, generated by a simple two-state hidden Markov model, but with an infinite-state ϵ-machine presentation. All in all, the results lay the groundwork for analyzing more complex processes with infinite statistical complexity and infinite excess entropy.
IPP Max Planck Institute of Plasma of Physics at Garching
International Nuclear Information System (INIS)
1979-01-01
The cost accounting system of the IPP Max Planck Institute of Plasma Physics at Garching is described with all details as there are cost class accounting, cost centers, cost units and resulting overall cost summary. Detailed instructions are given about the implementation of this cost accounting system into the organisational structure of the IPP. (A.N.)
The ITER Management Advisory Committee (MAC) meeting in Garching
International Nuclear Information System (INIS)
Yoshikawa, M.
1999-01-01
The ITER management advisory committee meeting was held on 22-23 July 1999 in Garching, Germany. The main topics were the ITER EDA status, task status summary and work program, joint fund, information technology needs at the ITER joint work sites, the disposition of R and D components and a schedule of ITER meetings
DEFF Research Database (Denmark)
Mohd. Azam, Sazuan Nazrah
2017-01-01
In this paper, we used the modified quadruple tank system that represents a multi-input-multi-output (MIMO) system as an example to present the realization of a linear discrete-time state space model and to obtain the state estimation using Kalman filter in a methodical mannered. First, an existing...... part of the Kalman filter is used to estimates the current state, based on the model and the measurements. The static and dynamic Kalman filter is compared and all results is demonstrated through simulations....
On the Discrete-Time GeoX/G/1 Queues under N-Policy with Single and Multiple Vacations
Directory of Open Access Journals (Sweden)
Sung J. Kim
2013-01-01
Full Text Available We consider the discrete-time GeoX/G/1 queue under N-policy with single and multiple vacations. In this queueing system, the server takes multiple vacations and a single vacation whenever the system becomes empty and begins to serve customers only if the queue length is at least a predetermined threshold value N. Using the well-known property of stochastic decomposition, we derive the stationary queue-length distributions for both vacation models in a simple and unified manner. In addition, we derive their busy as well as idle-period distributions. Some classical vacation models are considered as special cases.
Equilibrium and response properties of the integrate-and-fire neuron in discrete time
Directory of Open Access Journals (Sweden)
Moritz Helias
2010-01-01
Full Text Available The integrate-and-fire neuron with exponential postsynaptic potentials is a frequently employed model to study neural networks. Simulations in discrete time still have highest performance at moderate numerical errors, which makes them first choice for long-term simulations of plastic networks. Here we extend the population density approach to investigate how the equilibrium and response properties of the leaky integrate-and-fire neuron are affected by time discretization. We present a novel analytical treatment of the boundary condition at threshold, taking both discretization of time and finite synaptic weights into account. We uncover an increased membrane potential density just below threshold as the decisive property that explains the deviations found between simulations and the classical diffusion approximation. Temporal discretization and finite synaptic weights both contribute to this effect. Our treatment improves the standard formula to calculate the neuron’s equilibrium firing rate. Direct solution of the Markov process describing the evolution of the membrane potential density confirms our analysis and yields a method to calculate the firing rate exactly. Knowing the shape of the membrane potential distribution near threshold enables us to devise the transient response properties of the neuron model to synaptic input. We find a pronounced non-linear fast response component that has not been described by the prevailing continuous time theory for Gaussian white noise input.
Chang, Insu
The objective of the thesis is to introduce a relatively general nonlinear controller/estimator synthesis framework using a special type of the state-dependent Riccati equation technique. The continuous time state-dependent Riccati equation (SDRE) technique is extended to discrete-time under input and state constraints, yielding constrained (C) discrete-time (D) SDRE, referred to as CD-SDRE. For the latter, stability analysis and calculation of a region of attraction are carried out. The derivation of the D-SDRE under state-dependent weights is provided. Stability of the D-SDRE feedback system is established using Lyapunov stability approach. Receding horizon strategy is used to take into account the constraints on D-SDRE controller. Stability condition of the CD-SDRE controller is analyzed by using a switched system. The use of CD-SDRE scheme in the presence of constraints is then systematically demonstrated by applying this scheme to problems of spacecraft formation orbit reconfiguration under limited performance on thrusters. Simulation results demonstrate the efficacy and reliability of the proposed CD-SDRE. The CD-SDRE technique is further investigated in a case where there are uncertainties in nonlinear systems to be controlled. First, the system stability under each of the controllers in the robust CD-SDRE technique is separately established. The stability of the closed-loop system under the robust CD-SDRE controller is then proven based on the stability of each control system comprising switching configuration. A high fidelity dynamical model of spacecraft attitude motion in 3-dimensional space is derived with a partially filled fuel tank, assumed to have the first fuel slosh mode. The proposed robust CD-SDRE controller is then applied to the spacecraft attitude control system to stabilize its motion in the presence of uncertainties characterized by the first fuel slosh mode. The performance of the robust CD-SDRE technique is discussed. Subsequently
Stabilization and tracking controller for a class of nonlinear discrete-time systems
International Nuclear Information System (INIS)
Sharma, B.B.; Kar, I.N.
2011-01-01
Highlights: → We present recursive design of stabilizing controller for nonlinear discrete-time systems. → Problem of stabilizing and tracking control of single link manipulator system is addressed. → We extend the proposed results to output tracking problems. → The proposed methodology is applied satisfactorily to discrete-time chaotic maps. - Abstract: In this paper, stabilization and tracking control problem for parametric strict feedback class of discrete time systems is addressed. Recursive design of control function based on contraction theory framework is proposed instead of traditional Lyapunov based method. Explicit structure of controller is derived for the addressed class of nonlinear discrete-time systems. Conditions for exponential stability of system states are derived in terms of controller parameters. At each stage of recursive procedure a specific structure of Jacobian matrix is ensured so as to satisfy conditions of stability. The closed loop dynamics in this case remains nonlinear in nature. The proposed algorithm establishes global stability results in quite a simple manner as it does not require formulation of error dynamics. Problem of stabilization and output tracking control in case of single link manipulator system with actuator dynamics is analyzed using the proposed strategy. The proposed results are further extended to stabilization of discrete time chaotic systems. Numerical simulations presented in the end show the effectiveness of the proposed approach.
On a random area variable arising in discrete-time queues and compact directed percolation
International Nuclear Information System (INIS)
Kearney, Michael J
2004-01-01
A well-known discrete-time, single-server queueing system with mean arrival rate λ and mean departure rate μ is considered from the perspective of the area, A, swept out by the queue occupation process during a busy period. We determine the exact form of the tail of the distribution, Pr(A > x); in particular, we show that Pr(A > x) ∼ Cx -1/4 exp(-Dx 1/2 ) for all ρ ≠ 1, where ρ ≡ λ/μ, and expressions for C and D are given. For the critical case ρ = 1 we show that Pr(A > x) ∼ C'x -1/3 , with C' also given. A simple mapping, used in the derivation, establishes a connection with compact directed percolation on a square lattice. As a corollary, therefore, we are also able to specify the large-area asymptotic behaviour of this model at all points in the phase diagram. This extends previous scaling results, which are only valid close to the percolation threshold
Bifurcation and complex dynamics of a discrete-time predator-prey system
Directory of Open Access Journals (Sweden)
S. M. Sohel Rana
2015-06-01
Full Text Available In this paper, we investigate the dynamics of a discrete-time predator-prey system of Holling-I type in the closed first quadrant R+2. The existence and local stability of positive fixed point of the discrete dynamical system is analyzed algebraically. It is shown that the system undergoes a flip bifurcation and a Neimark-Sacker bifurcation in the interior of R+2 by using bifurcation theory. It has been found that the dynamical behavior of the model is very sensitive to the parameter values and the initial conditions. Numerical simulation results not only show the consistence with the theoretical analysis but also display the new and interesting dynamic behaviors, including phase portraits, period-9, 10, 20-orbits, attracting invariant circle, cascade of period-doubling bifurcation from period-20 leading to chaos, quasi-periodic orbits, and sudden disappearance of the chaotic dynamics and attracting chaotic set. In particular, we observe that when the prey is in chaotic dynamic, the predator can tend to extinction or to a stable equilibrium. The Lyapunov exponents are numerically computed to characterize the complexity of the dynamical behaviors. The analysis and results in this paper are interesting in mathematics and biology.
Actor-critic-based optimal tracking for partially unknown nonlinear discrete-time systems.
Kiumarsi, Bahare; Lewis, Frank L
2015-01-01
This paper presents a partially model-free adaptive optimal control solution to the deterministic nonlinear discrete-time (DT) tracking control problem in the presence of input constraints. The tracking error dynamics and reference trajectory dynamics are first combined to form an augmented system. Then, a new discounted performance function based on the augmented system is presented for the optimal nonlinear tracking problem. In contrast to the standard solution, which finds the feedforward and feedback terms of the control input separately, the minimization of the proposed discounted performance function gives both feedback and feedforward parts of the control input simultaneously. This enables us to encode the input constraints into the optimization problem using a nonquadratic performance function. The DT tracking Bellman equation and tracking Hamilton-Jacobi-Bellman (HJB) are derived. An actor-critic-based reinforcement learning algorithm is used to learn the solution to the tracking HJB equation online without requiring knowledge of the system drift dynamics. That is, two neural networks (NNs), namely, actor NN and critic NN, are tuned online and simultaneously to generate the optimal bounded control policy. A simulation example is given to show the effectiveness of the proposed method.
Wei, Qinglai; Liu, Derong; Lin, Qiao
In this paper, a novel local value iteration adaptive dynamic programming (ADP) algorithm is developed to solve infinite horizon optimal control problems for discrete-time nonlinear systems. The focuses of this paper are to study admissibility properties and the termination criteria of discrete-time local value iteration ADP algorithms. In the discrete-time local value iteration ADP algorithm, the iterative value functions and the iterative control laws are both updated in a given subset of the state space in each iteration, instead of the whole state space. For the first time, admissibility properties of iterative control laws are analyzed for the local value iteration ADP algorithm. New termination criteria are established, which terminate the iterative local ADP algorithm with an admissible approximate optimal control law. Finally, simulation results are given to illustrate the performance of the developed algorithm.In this paper, a novel local value iteration adaptive dynamic programming (ADP) algorithm is developed to solve infinite horizon optimal control problems for discrete-time nonlinear systems. The focuses of this paper are to study admissibility properties and the termination criteria of discrete-time local value iteration ADP algorithms. In the discrete-time local value iteration ADP algorithm, the iterative value functions and the iterative control laws are both updated in a given subset of the state space in each iteration, instead of the whole state space. For the first time, admissibility properties of iterative control laws are analyzed for the local value iteration ADP algorithm. New termination criteria are established, which terminate the iterative local ADP algorithm with an admissible approximate optimal control law. Finally, simulation results are given to illustrate the performance of the developed algorithm.
A Novel Analytic Technique for the Service Station Reliability in a Discrete-Time Repairable Queue
Directory of Open Access Journals (Sweden)
Renbin Liu
2013-01-01
Full Text Available This paper presents a decomposition technique for the service station reliability in a discrete-time repairable GeomX/G/1 queueing system, in which the server takes exhaustive service and multiple adaptive delayed vacation discipline. Using such a novel analytic technique, some important reliability indices and reliability relation equations of the service station are derived. Furthermore, the structures of the service station indices are also found. Finally, special cases and numerical examples validate the derived results and show that our analytic technique is applicable to reliability analysis of some complex discrete-time repairable bulk arrival queueing systems.
Observation of Discrete-Time-Crystal Signatures in an Ordered Dipolar Many-Body System
Rovny, Jared; Blum, Robert L.; Barrett, Sean E.
2018-05-01
A discrete time crystal (DTC) is a robust phase of driven systems that breaks the discrete time translation symmetry of the driving Hamiltonian. Recent experiments have observed DTC signatures in two distinct systems. Here we show nuclear magnetic resonance observations of DTC signatures in a third, strikingly different system: an ordered spatial crystal. We use a novel DTC echo experiment to probe the coherence of the driven system. Finally, we show that interactions during the pulse of the DTC sequence contribute to the decay of the signal, complicating attempts to measure the intrinsic lifetime of the DTC.
Discrete-time bidirectional associative memory neural networks with variable delays
International Nuclear Information System (INIS)
Liang Jinling; Cao Jinde; Ho, Daniel W.C.
2005-01-01
Based on the linear matrix inequality (LMI), some sufficient conditions are presented in this Letter for the existence, uniqueness and global exponential stability of the equilibrium point of discrete-time bidirectional associative memory (BAM) neural networks with variable delays. Some of the stability criteria obtained in this Letter are delay-dependent, and some of them are delay-independent, they are less conservative than the ones reported so far in the literature. Furthermore, the results provide one more set of easily verified criteria for determining the exponential stability of discrete-time BAM neural networks
Discrete-time bidirectional associative memory neural networks with variable delays
Liang, variable delays [rapid communication] J.; Cao, J.; Ho, D. W. C.
2005-02-01
Based on the linear matrix inequality (LMI), some sufficient conditions are presented in this Letter for the existence, uniqueness and global exponential stability of the equilibrium point of discrete-time bidirectional associative memory (BAM) neural networks with variable delays. Some of the stability criteria obtained in this Letter are delay-dependent, and some of them are delay-independent, they are less conservative than the ones reported so far in the literature. Furthermore, the results provide one more set of easily verified criteria for determining the exponential stability of discrete-time BAM neural networks.
International Nuclear Information System (INIS)
Liang Jinling; Cao Jinde
2004-01-01
First, convergence of continuous-time Bidirectional Associative Memory (BAM) neural networks are studied. By using Lyapunov functionals and some analysis technique, the delay-independent sufficient conditions are obtained for the networks to converge exponentially toward the equilibrium associated with the constant input sources. Second, discrete-time analogues of the continuous-time BAM networks are formulated and studied. It is shown that the convergence characteristics of the continuous-time systems are preserved by the discrete-time analogues without any restriction imposed on the uniform discretionary step size. An illustrative example is given to demonstrate the effectiveness of the obtained results
David Ardia; Lennart F. Hoogerheide
2013-01-01
We investigate the time-variation of the cross-sectional distribution of asymmetric GARCH model parameters over the S&P 500 constituents for the period 2000-2012. We find the following results. First, the unconditional variances in the GARCH model obviously show major time-variation, with a high level after the dot-com bubble and the highest peak in the latest financial crisis. Second, in these more volatile periods it is especially the persistence of deviations of volatility from is uncondit...
Forecasting volatility in gold returns under the GARCH, IGARCH and FIGARCH frameworks: New evidence
Bentes, Sonia R.
2015-11-01
This study employs three volatility models of the GARCH family to examine the volatility behavior of gold returns. Much of the literature on this topic suggests that gold plays a fundamental role as a hedge and safe haven against adverse market conditions, which is particularly relevant in periods of high volatility. This makes understanding gold volatility important for a number of theoretical and empirical applications, namely investment valuation, portfolio selection, risk management, monetary policy-making, futures and option pricing, hedging strategies and value-at-risk (VaR) policies (e.g. Baur and Lucey (2010)). We use daily data from August 2, 1976 to February 6, 2015 and divide the full sample into two periods: the in-sample period (August 2, 1976-October 24, 2008) is used to estimate model coefficients, while the out-of-sample period (October 27, 2008-February 6, 2015) is for forecasting purposes. Specifically, we employ the GARCH(1,1), IGARCH(1,1) and FIGARCH(1, d,1) specifications. The results show that the FIGARCH(1, d,1) is the best model to capture linear dependence in the conditional variance of the gold returns as given by the information criteria. It is also found to be the best model to forecast the volatility of gold returns.
RF Negative Ion Source Development at IPP Garching
International Nuclear Information System (INIS)
Kraus, W.; McNeely, P.; Berger, M.; Christ-Koch, S.; Falter, H. D.; Fantz, U.; Franzen, P.; Froeschle, M.; Heinemann, B.; Leyer, S.; Riedl, R.; Speth, E.; Wuenderlich, D.
2007-01-01
IPP Garching is heavily involved in the development of an ion source for Neutral Beam Heating of the ITER Tokamak. RF driven ion sources have been successfully developed and are in operation on the ASDEX-Upgrade Tokamak for positive ion based NBH by the NB Heating group at IPP Garching. Building on this experience a RF driven H- ion source has been under development at IPP Garching as an alternative to the ITER reference design ion source. The number of test beds devoted to source development for ITER has increased from one (BATMAN) by the addition of two test beds (MANITU, RADI). This paper contains descriptions of the three test beds. Results on diagnostic development using laser photodetachment and cavity ringdown spectroscopy are given for BATMAN. The latest results for long pulse development on MANITU are presented including the to date longest pulse (600 s). As well, details of source modifications necessitated for pulses in excess of 100 s are given. The newest test bed RADI is still being commissioned and only technical details of the test bed are included in this paper. The final topic of the paper is an investigation into the effects of biasing the plasma grid
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....
A new criterion for global robust stability of interval neural networks with discrete time delays
International Nuclear Information System (INIS)
Li Chuandong; Chen Jinyu; Huang Tingwen
2007-01-01
This paper further studies global robust stability of a class of interval neural networks with discrete time delays. By introducing an equivalent transformation of interval matrices, a new criterion on global robust stability is established. In comparison with the results reported in the literature, the proposed approach leads to results with less restrictive conditions. Numerical examples are also worked through to illustrate our results
Property - preserving convergent sequences of invariant sets for linear discrete - time systems
Athanasopoulos, N.; Lazar, M.; Bitsoris, G.
2014-01-01
Abstract: New sequences of monotonically increasing sets are introduced, for linear discrete-time systems subject to input and state constraints. The elements of the set sequences are controlled invariant and admissible regions of stabilizability. They are generated from the iterative application of
Directory of Open Access Journals (Sweden)
Xinggui Liu
2011-01-01
Full Text Available In this paper, by using Mawhin's continuation theorem of coincidence degree theory, we establish the existence of at least four positive periodic solutions for a discrete time Lotka-Volterra competitive system with harvesting terms. An example is given to illustrate the effectiveness of our results.
International Nuclear Information System (INIS)
Chen, S.-F.
2009-01-01
The asymptotic stability problem for discrete-time systems with time-varying delay subject to saturation nonlinearities is addressed in this paper. In terms of linear matrix inequalities (LMIs), a delay-dependent sufficient condition is derived to ensure the asymptotic stability. A numerical example is given to demonstrate the theoretical results.
Nonparametric Estimation of Interval Reliability for Discrete-Time Semi-Markov Systems
DEFF Research Database (Denmark)
Georgiadis, Stylianos; Limnios, Nikolaos
2016-01-01
In this article, we consider a repairable discrete-time semi-Markov system with finite state space. The measure of the interval reliability is given as the probability of the system being operational over a given finite-length time interval. A nonparametric estimator is proposed for the interval...
Naz, Rehana
2018-01-01
Pontrygin-type maximum principle is extended for the present value Hamiltonian systems and current value Hamiltonian systems of nonlinear difference equations for uniform time step $h$. A new method termed as a discrete time current value Hamiltonian method is established for the construction of first integrals for current value Hamiltonian systems of ordinary difference equations arising in Economic growth theory.
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...
Statistical inference for discrete-time samples from affine stochastic delay differential equations
DEFF Research Database (Denmark)
Küchler, Uwe; Sørensen, Michael
2013-01-01
Statistical inference for discrete time observations of an affine stochastic delay differential equation is considered. The main focus is on maximum pseudo-likelihood estimators, which are easy to calculate in practice. A more general class of prediction-based estimating functions is investigated...
Discrete-Time Mixing Receiver Architecture for RF-Sampling Software-Defined Radio
Ru, Z.; Klumperink, Eric A.M.; Nauta, Bram
2010-01-01
Abstract—A discrete-time (DT) mixing architecture for RF-sampling receivers is presented. This architecture makes RF sampling more suitable for software-defined radio (SDR) as it achieves wideband quadrature demodulation and wideband harmonic rejection. The paper consists of two parts. In the first
Quasi-stationary distributions for reducible absorbing Markov chains in discrete time
van Doorn, Erik A.; Pollett, P.K.
2009-01-01
We consider discrete-time Markov chains with one coffin state and a finite set $S$ of transient states, and are interested in the limiting behaviour of such a chain as time $n \\to \\infty,$ conditional on survival up to $n$. It is known that, when $S$ is irreducible, the limiting conditional
Global stability of discrete-time recurrent neural networks with impulse effects
International Nuclear Information System (INIS)
Zhou, L; Li, C; Wan, J
2008-01-01
This paper formulates and studies a class of discrete-time recurrent neural networks with impulse effects. A stability criterion, which characterizes the effects of impulse and stability property of the corresponding impulse-free networks on the stability of the impulsive networks in an aggregate form, is established. Two simplified and numerically tractable criteria are also provided
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
Sampled-data and discrete-time H2 optimal control
Trentelman, Harry L.; Stoorvogel, Anton A.
1993-01-01
This paper deals with the sampled-data H2 optimal control problem. Given a linear time-invariant continuous-time system, the problem of minimizing the H2 performance over all sampled-data controllers with a fixed sampling period can be reduced to a pure discrete-time H2 optimal control problem. This
Discrete-Time receivers for software-defined radio: challenges and solutions
Ru, Z.; Klumperink, Eric A.M.; Nauta, Bram
2007-01-01
Abstract—CMOS radio receiver architectures, based on radio frequency (RF) sampling followed by discrete-time (DT) signal processing via switched-capacitor circuits, have recently been proposed for dedicated radio standards. This paper explores the suitability of such DT receivers for highly flexible
On the Suitability of Discrete-Time Receivers for Software-Defined Radio
Ru, Z.; Klumperink, Eric A.M.; Nauta, Bram
2007-01-01
Abstract—CMOS radio receiver architectures, based on radio frequency (RF) sampling followed by discrete-time (D-T) signal processing via switched-capacitor circuits, have recently been proposed for dedicated radio standards. This paper explores the suitability of such D-T receivers for highly
A theory of Markovian time-inconsistent stochastic control in discrete time
DEFF Research Database (Denmark)
Bjork, Tomas; Murgoci, Agatha
2014-01-01
We develop a theory for a general class of discrete-time stochastic control problems that, in various ways, are time-inconsistent in the sense that they do not admit a Bellman optimality principle. We attack these problems by viewing them within a game theoretic framework, and we look for subgame...
Homogeneous Discrete Time Alternating Compound Renewal Process: A Disability Insurance Application
Directory of Open Access Journals (Sweden)
Guglielmo D’Amico
2015-01-01
Full Text Available Discrete time alternating renewal process is a very simple tool that permits solving many real life problems. This paper, after the presentation of this tool, introduces the compound environment in the alternating process giving a systematization to this important tool. The claim costs for a temporary disability insurance contract are presented. The algorithm and an example of application are also provided.
ON THE ANISOTROPIC NORM OF DISCRETE TIME STOCHASTIC SYSTEMS WITH STATE DEPENDENT NOISE
Directory of Open Access Journals (Sweden)
Isaac Yaesh
2013-01-01
Full Text Available The purpose of this paper is to determine conditions for the bound-edness of the anisotropic norm of discrete-time linear stochastic sys-tems with state dependent noise. It is proved that these conditions canbe expressed in terms of the feasibility of a specific system of matrixinequalities.
Less Conservative ℋ∞ Fuzzy Control for Discrete-Time Takagi-Sugeno Systems
Directory of Open Access Journals (Sweden)
Leonardo Amaral Mozelli
2011-01-01
Full Text Available New analysis and control design conditions of discrete-time fuzzy systems are proposed. Using fuzzy Lyapunov's functions and introducing slack variables, less conservative conditions are obtained. The controller guarantees system stabilization and ℋ∞ performance. Numerical tests and a practical experiment in Chua's circuit are presented to show the effectiveness.
Decentralized control of discrete-time linear time invariant systems with input saturation
Deliu, C.; Deliu, Ciprian; Malek, Babak; Roy, Sandip; Saberi, Ali; Stoorvogel, Antonie Arij
We study decentralized stabilization of discrete-time linear time invariant (LTI) systems subject to actuator saturation, using LTI controllers. The requirement of stabilization under both saturation constraints and decentralization impose obvious necessary conditions on the open-loop plant, namely
Communication scheduling in robust self-triggered MPC for linear discrete-time systems
Brunner, F.D.; Gommans, T.M.P.; Heemels, W.P.M.H.; Allgöwer, F.
2015-01-01
We consider a networked control system consisting of a physical plant, an actuator, a sensor, and a controller that is connected to the actuator and sensor via a communication network. The plant is described by a linear discrete-time system subject to additive disturbances. In order to reduce the
Geometric ergodicity and quasi-stationarity in discrete-time birth-death processes
van Doorn, Erik A.; Schrijner, Pauline
1995-01-01
We study two aspects of discrete-time birth-death processes, the common feature of which is the central role played by the decay parameter of the process. First, conditions for geometric ergodicity and bounds for the decay parameter are obtained. Then the existence and structure of quasi-stationary
It's Deja Vu All over Again: Using Multiple-Spell Discrete-Time Survival Analysis.
Willett, John B.; Singer, Judith D.
1995-01-01
The multiple-spell discrete-time survival analysis method is introduced and illustrated using longitudinal data on exit from and reentry into the teaching profession. The method is applicable to many educational problems involving the sequential occurrence of disparate events or episodes. (SLD)
Direct Adaptive Control of a Class of Nonlinear Discrete-Time Systems
DEFF Research Database (Denmark)
Bendtsen, Jan Dimon
2004-01-01
In this paper we deal with direct adaptive control of a specific class of discrete-time SISO systems, where the nonlinearities are convex and an upper bound is known. We use a control law based on a linear combination of a set of globally uniformly bounded basis functions with compact support, wh...
Linear quadratic Gaussian balancing for discrete-time infinite-dimensional linear systems
Opmeer, MR; Curtain, RF
2004-01-01
In this paper, we study the existence of linear quadratic Gaussian (LQG)-balanced realizations for discrete-time infinite-dimensional systems. LQG-balanced realizations are those for which the smallest nonnegative self-adjoint solutions of the control and filter Riccati equations are equal. We show
Globally asymptotically stable analysis in a discrete time eco-epidemiological system
International Nuclear Information System (INIS)
Hu, Zengyun; Teng, Zhidong; Zhang, Tailei; Zhou, Qiming; Chen, Xi
2017-01-01
Highlights: • Dynamical behaviors of a discrete time eco-epidemiological system are discussed. • Global asymptotical stability of this system is obtained by an iteration scheme which can be expended to general dimensional discrete system. • More complex dynamical behaviors are obtained by numerical simulations. - Abstract: In this study, the dynamical behaviors of a discrete time eco-epidemiological system are discussed. The local stability, bifurcation and chaos are obtained. Moreover, the global asymptotical stability of this system is explored by an iteration scheme. The numerical simulations illustrate the theoretical results and exhibit the complex dynamical behaviors such as flip bifurcation, Hopf bifurcation and chaotic dynamical behaviors. Our main results provide an efficient method to analyze the global asymptotical stability for general three dimensional discrete systems.
Autonomous learning by simple dynamical systems with a discrete-time formulation
Bilen, Agustín M.; Kaluza, Pablo
2017-05-01
We present a discrete-time formulation for the autonomous learning conjecture. The main feature of this formulation is the possibility to apply the autonomous learning scheme to systems in which the errors with respect to target functions are not well-defined for all times. This restriction for the evaluation of functionality is a typical feature in systems that need a finite time interval to process a unit piece of information. We illustrate its application on an artificial neural network with feed-forward architecture for classification and a phase oscillator system with synchronization properties. The main characteristics of the discrete-time formulation are shown by constructing these systems with predefined functions.
Exponential stability result for discrete-time stochastic fuzzy uncertain neural networks
International Nuclear Information System (INIS)
Mathiyalagan, K.; Sakthivel, R.; Marshal Anthoni, S.
2012-01-01
This Letter addresses the stability analysis problem for a class of uncertain discrete-time stochastic fuzzy neural networks (DSFNNs) with time-varying delays. By constructing a new Lyapunov–Krasovskii functional combined with the free weighting matrix technique, a new set of delay-dependent sufficient conditions for the robust exponential stability of the considered DSFNNs is established in terms of Linear Matrix Inequalities (LMIs). Finally, numerical examples with simulation results are provided to illustrate the applicability and usefulness of the obtained theory. -- Highlights: ► Applications of neural networks require the knowledge of dynamic behaviors. ► Exponential stability of discrete-time stochastic fuzzy neural networks is studied. ► Linear matrix inequality optimization approach is used to obtain the result. ► Delay-dependent stability criterion is established in terms of LMIs. ► Examples with simulation are provided to show the effectiveness of the result.
A simple method of chaos control for a class of chaotic discrete-time systems
International Nuclear Information System (INIS)
Jiang Guoping; Zheng Weixing
2005-01-01
In this paper, a simple method is proposed for chaos control for a class of discrete-time chaotic systems. The proposed method is built upon the state feedback control and the characteristic of ergodicity of chaos. The feedback gain matrix of the controller is designed using a simple criterion, so that control parameters can be selected via the pole placement technique of linear control theory. The new controller has a feature that it only uses the state variable for control and does not require the target equilibrium point in the feedback path. Moreover, the proposed control method cannot only overcome the so-called 'odd eigenvalues number limitation' of delayed feedback control, but also control the chaotic systems to the specified equilibrium points. The effectiveness of the proposed method is demonstrated by a two-dimensional discrete-time chaotic system
Sliding mode control-based linear functional observers for discrete-time stochastic systems
Singh, Satnesh; Janardhanan, Sivaramakrishnan
2017-11-01
Sliding mode control (SMC) is one of the most popular techniques to stabilise linear discrete-time stochastic systems. However, application of SMC becomes difficult when the system states are not available for feedback. This paper presents a new approach to design a SMC-based functional observer for discrete-time stochastic systems. The functional observer is based on the Kronecker product approach. Existence conditions and stability analysis of the proposed observer are given. The control input is estimated by a novel linear functional observer. This approach leads to a non-switching type of control, thereby eliminating the fundamental cause of chatter. Furthermore, the functional observer is designed in such a way that the effect of process and measurement noise is minimised. Simulation example is given to illustrate and validate the proposed design method.
Adaptive Neural Tracking Control for Discrete-Time Switched Nonlinear Systems with Dead Zone Inputs
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Jidong Wang
2017-01-01
Full Text Available In this paper, the adaptive neural controllers of subsystems are proposed for a class of discrete-time switched nonlinear systems with dead zone inputs under arbitrary switching signals. Due to the complicated framework of the discrete-time switched nonlinear systems and the existence of the dead zone, it brings about difficulties for controlling such a class of systems. In addition, the radial basis function neural networks are employed to approximate the unknown terms of each subsystem. Switched update laws are designed while the parameter estimation is invariable until its corresponding subsystem is active. Then, the closed-loop system is stable and all the signals are bounded. Finally, to illustrate the effectiveness of the proposed method, an example is employed.
Discrete-Time Stable Generalized Self-Learning Optimal Control With Approximation Errors.
Wei, Qinglai; Li, Benkai; Song, Ruizhuo
2018-04-01
In this paper, a generalized policy iteration (GPI) algorithm with approximation errors is developed for solving infinite horizon optimal control problems for nonlinear systems. The developed stable GPI algorithm provides a general structure of discrete-time iterative adaptive dynamic programming algorithms, by which most of the discrete-time reinforcement learning algorithms can be described using the GPI structure. It is for the first time that approximation errors are explicitly considered in the GPI algorithm. The properties of the stable GPI algorithm with approximation errors are analyzed. The admissibility of the approximate iterative control law can be guaranteed if the approximation errors satisfy the admissibility criteria. The convergence of the developed algorithm is established, which shows that the iterative value function is convergent to a finite neighborhood of the optimal performance index function, if the approximate errors satisfy the convergence criterion. Finally, numerical examples and comparisons are presented.
Limitations of discrete-time quantum walk on a one-dimensional infinite chain
Lin, Jia-Yi; Zhu, Xuanmin; Wu, Shengjun
2018-04-01
How well can we manipulate the state of a particle via a discrete-time quantum walk? We show that the discrete-time quantum walk on a one-dimensional infinite chain with coin operators that are independent of the position can only realize product operators of the form eiξ A ⊗1p, which cannot change the position state of the walker. We present a scheme to construct all possible realizations of all the product operators of the form eiξ A ⊗1p. When the coin operators are dependent on the position, we show that the translation operators on the position can not be realized via a DTQW with coin operators that are either the identity operator 1 or the Pauli operator σx.
Discrete Time McKean–Vlasov Control Problem: A Dynamic Programming Approach
Energy Technology Data Exchange (ETDEWEB)
Pham, Huyên, E-mail: pham@math.univ-paris-diderot.fr; Wei, Xiaoli, E-mail: tyswxl@gmail.com [Laboratoire de Probabilités et Modèles Aléatoires, CNRS, UMR 7599, Université Paris Diderot (France)
2016-12-15
We consider the stochastic optimal control problem of nonlinear mean-field systems in discrete time. We reformulate the problem into a deterministic control problem with marginal distribution as controlled state variable, and prove that dynamic programming principle holds in its general form. We apply our method for solving explicitly the mean-variance portfolio selection and the multivariate linear-quadratic McKean–Vlasov control problem.
Discrete Time McKean–Vlasov Control Problem: A Dynamic Programming Approach
International Nuclear Information System (INIS)
Pham, Huyên; Wei, Xiaoli
2016-01-01
We consider the stochastic optimal control problem of nonlinear mean-field systems in discrete time. We reformulate the problem into a deterministic control problem with marginal distribution as controlled state variable, and prove that dynamic programming principle holds in its general form. We apply our method for solving explicitly the mean-variance portfolio selection and the multivariate linear-quadratic McKean–Vlasov control problem.
CROSAT: A digital computer program for statistical-spectral analysis of two discrete time series
International Nuclear Information System (INIS)
Antonopoulos Domis, M.
1978-03-01
The program CROSAT computes directly from two discrete time series auto- and cross-spectra, transfer and coherence functions, using a Fast Fourier Transform subroutine. Statistical analysis of the time series is optional. While of general use the program is constructed to be immediately compatible with the ICL 4-70 and H316 computers at AEE Winfrith, and perhaps with minor modifications, with any other hardware system. (author)
International Nuclear Information System (INIS)
Park, Moon Kyu; Kim, Yong Hee; Cha, Kune Ho; Kim, Myung Ki
1998-01-01
A method is described to develop an H∞ filtering method for the dynamic compensation of self-powered neutron detectors normally used for fixed incore instruments. An H∞ norm of the filter transfer matrix is used as the optimization criteria in the worst-case estimation error sense. Filter modeling is performed for discrete-time model. The filter gains are optimized in the sense of noise attenuation level of H∞ setting. By introducing Bounded Real Lemma, the conventional algebraic Riccati inequalities are converted into Linear Matrix Inequalities (LMIs). Finally, the filter design problem is solved via the convex optimization framework using LMIs. The simulation results show that remarkable improvements are achieved in view of the filter response time and the filter design efficiency
DEFF Research Database (Denmark)
Mørkholt, Jakob; Elliott, S.J.; Sors, T.C.
1997-01-01
with a piezoceramic patch control actuator and a point velocity sensor and excited by a point force driven by white noise acting as the primary source. The design objective has been to suppress the effect of the primary disturbance on the output by minimising the mean square value of the output. Apart from comparing......A comparison of three ways of designing optimal discrete time feedback controllers has been carried out via computer simulations. The three design methods are similar in that they are all based on the minimisation of a quadratic cost function under certain assumptions about the disturbance noise...... and sensor noise in the system to be controlled. They are also based on (different) models of the plant under control and the disturbance to be suppressed by the controllers. Controllers based on the three methods have been designed from a model of a lightly damped, rectangular plate fitted...
Directory of Open Access Journals (Sweden)
Tao Wang
2013-01-01
Full Text Available To obtain reliable transient auditory evoked potentials (AEPs from EEGs recorded using high stimulus rate (HSR paradigm, it is critical to design the stimulus sequences of appropriate frequency properties. Traditionally, the individual stimulus events in a stimulus sequence occur only at discrete time points dependent on the sampling frequency of the recording system and the duration of stimulus sequence. This dependency likely causes the implementation of suboptimal stimulus sequences, sacrificing the reliability of resulting AEPs. In this paper, we explicate the use of continuous-time stimulus sequence for HSR paradigm, which is independent of the discrete electroencephalogram (EEG recording system. We employ simulation studies to examine the applicability of the continuous-time stimulus sequences and the impacts of sampling frequency on AEPs in traditional studies using discrete-time design. Results from these studies show that the continuous-time sequences can offer better frequency properties and improve the reliability of recovered AEPs. Furthermore, we find that the errors in the recovered AEPs depend critically on the sampling frequencies of experimental systems, and their relationship can be fitted using a reciprocal function. As such, our study contributes to the literature by demonstrating the applicability and advantages of continuous-time stimulus sequences for HSR paradigm and by revealing the relationship between the reliability of AEPs and sampling frequencies of the experimental systems when discrete-time stimulus sequences are used in traditional manner for the HSR paradigm.
International Nuclear Information System (INIS)
Liu Yurong; Wang Zidong; Liu Xiaohui
2008-01-01
In this Letter, we investigate the state estimation problem for a new class of discrete-time neural networks with Markovian jumping parameters as well as mode-dependent mixed time-delays. The parameters of the discrete-time neural networks are subject to the switching from one mode to another at different times according to a Markov chain, and the mixed time-delays consist of both discrete and distributed delays that are dependent on the Markovian jumping mode. New techniques are developed to deal with the mixed time-delays in the discrete-time setting, and a novel Lyapunov-Krasovskii functional is put forward to reflect the mode-dependent time-delays. Sufficient conditions are established in terms of linear matrix inequalities (LMIs) that guarantee the existence of the state estimators. We show that both the existence conditions and the explicit expression of the desired estimator can be characterized in terms of the solution to an LMI. A numerical example is exploited to show the usefulness of the derived LMI-based conditions
Choi, Hyun Duck; Ahn, Choon Ki; Karimi, Hamid Reza; Lim, Myo Taeg
2017-10-01
This paper studies delay-dependent exponential dissipative and l 2 - l ∞ filtering problems for discrete-time switched neural networks (DSNNs) including time-delayed states. By introducing a novel discrete-time inequality, which is a discrete-time version of the continuous-time Wirtinger-type inequality, we establish new sets of linear matrix inequality (LMI) criteria such that discrete-time filtering error systems are exponentially stable with guaranteed performances in the exponential dissipative and l 2 - l ∞ senses. The design of the desired exponential dissipative and l 2 - l ∞ filters for DSNNs can be achieved by solving the proposed sets of LMI conditions. Via numerical simulation results, we show the validity of the desired discrete-time filter design approach.
Dideriksen, Jakob Lund; Feeney, Daniel F; Almuklass, Awad M; Enoka, Roger M
2017-08-01
Force trajectories during isometric force-matching tasks involving isometric contractions vary substantially across individuals. In this study, we investigated if this variability can be explained by discrete time proportional, integral, derivative (PID) control algorithms with varying model parameters. To this end, we analyzed the pinch force trajectories of 24 subjects performing two rapid force-matching tasks with visual feedback. Both tasks involved isometric contractions to a target force of 10% maximal voluntary contraction. One task involved a single action (pinch) and the other required a double action (concurrent pinch and wrist extension). 50,000 force trajectories were simulated with a computational neuromuscular model whose input was determined by a PID controller with different PID gains and frequencies at which the controller adjusted muscle commands. The goal was to find the best match between each experimental force trajectory and all simulated trajectories. It was possible to identify one realization of the PID controller that matched the experimental force produced during each task for most subjects (average index of similarity: 0.87 ± 0.12; 1 = perfect similarity). The similarities for both tasks were significantly greater than that would be expected by chance (single action: p = 0.01; double action: p = 0.04). Furthermore, the identified control frequencies in the simulated PID controller with the greatest similarities decreased as task difficulty increased (single action: 4.0 ± 1.8 Hz; double action: 3.1 ± 1.3 Hz). Overall, the results indicate that discrete time PID controllers are realistic models for the neural control of force in rapid force-matching tasks involving isometric contractions.
Directory of Open Access Journals (Sweden)
Norman Josephy
2011-01-01
Full Text Available We present a method of optimal hedging and pricing of equity-linked life insurance products in an incomplete discrete-time financial market. A pure endowment life insurance contract with guarantee is used as an example. The financial market incompleteness is caused by the assumption that the underlying risky asset price ratios are distributed in a compact interval, generalizing the assumptions of multinomial incomplete market models. For a range of initial hedging capitals for the embedded financial option, we numerically solve an optimal hedging problem and determine a risk-return profile of each optimal non-self-financing hedging strategy. The fair price of the insurance contract is determined according to the insurer's risk-return preferences. Illustrative numerical results of testing our algorithm on hypothetical insurance contracts are documented. A discussion and a test of a hedging strategy recalibration technique for long-term contracts are presented.
Limit theory for the sample autocorrelations and extremes of a GARCH (1,1) process
Mikosch, T; Starica, C
2000-01-01
The asymptotic theory for the sample autocorrelations and extremes of a GARCH(I, 1) process is provided. Special attention is given to the case when the sum of the ARCH and GARCH parameters is close to 1, that is, when one is close to an infinite Variance marginal distribution. This situation has
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Yiming Jiang
2016-01-01
Full Text Available Over the last few decades, the intelligent control methods such as fuzzy logic control (FLC and neural network (NN control have been successfully used in various applications. The rapid development of digital computer based control systems requires control signals to be calculated in a digital or discrete-time form. In this background, the intelligent control methods developed for discrete-time systems have drawn great attentions. This survey aims to present a summary of the state of the art of the design of FLC and NN-based intelligent control for discrete-time systems. For discrete-time FLC systems, numerous remarkable design approaches are introduced and a series of efficient methods to deal with the robustness, stability, and time delay of FLC discrete-time systems are recommended. Techniques for NN-based intelligent control for discrete-time systems, such as adaptive methods and adaptive dynamic programming approaches, are also reviewed. Overall, this paper is devoted to make a brief summary for recent progresses in FLC and NN-based intelligent control design for discrete-time systems as well as to present our thoughts and considerations of recent trends and potential research directions in this area.
Quantum circuit dynamics via path integrals: Is there a classical action for discrete-time paths?
International Nuclear Information System (INIS)
Penney, Mark D; Koh, Dax Enshan; Spekkens, Robert W
2017-01-01
It is straightforward to compute the transition amplitudes of a quantum circuit using the sum-over-paths methodology when the gates in the circuit are balanced, where a balanced gate is one for which all non-zero transition amplitudes are of equal magnitude. Here we consider the question of whether, for such circuits, the relative phases of different discrete-time paths through the configuration space can be defined in terms of a classical action, as they are for continuous-time paths. We show how to do so for certain kinds of quantum circuits, namely, Clifford circuits where the elementary systems are continuous-variable systems or discrete systems of odd-prime dimension. These types of circuit are distinguished by having phase-space representations that serve to define their classical counterparts. For discrete systems, the phase-space coordinates are also discrete variables. We show that for each gate in the generating set, one can associate a symplectomorphism on the phase-space and to each of these one can associate a generating function, defined on two copies of the configuration space. For discrete systems, the latter association is achieved using tools from algebraic geometry. Finally, we show that if the action functional for a discrete-time path through a sequence of gates is defined using the sum of the corresponding generating functions, then it yields the correct relative phases for the path-sum expression. These results are likely to be relevant for quantizing physical theories where time is fundamentally discrete, characterizing the classical limit of discrete-time quantum dynamics, and proving complexity results for quantum circuits. (paper)
Quantum circuit dynamics via path integrals: Is there a classical action for discrete-time paths?
Penney, Mark D.; Enshan Koh, Dax; Spekkens, Robert W.
2017-07-01
It is straightforward to compute the transition amplitudes of a quantum circuit using the sum-over-paths methodology when the gates in the circuit are balanced, where a balanced gate is one for which all non-zero transition amplitudes are of equal magnitude. Here we consider the question of whether, for such circuits, the relative phases of different discrete-time paths through the configuration space can be defined in terms of a classical action, as they are for continuous-time paths. We show how to do so for certain kinds of quantum circuits, namely, Clifford circuits where the elementary systems are continuous-variable systems or discrete systems of odd-prime dimension. These types of circuit are distinguished by having phase-space representations that serve to define their classical counterparts. For discrete systems, the phase-space coordinates are also discrete variables. We show that for each gate in the generating set, one can associate a symplectomorphism on the phase-space and to each of these one can associate a generating function, defined on two copies of the configuration space. For discrete systems, the latter association is achieved using tools from algebraic geometry. Finally, we show that if the action functional for a discrete-time path through a sequence of gates is defined using the sum of the corresponding generating functions, then it yields the correct relative phases for the path-sum expression. These results are likely to be relevant for quantizing physical theories where time is fundamentally discrete, characterizing the classical limit of discrete-time quantum dynamics, and proving complexity results for quantum circuits.
Robust Stabilization of Discrete-Time Systems with Time-Varying Delay: An LMI Approach
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Valter J. S. Leite
2008-01-01
Full Text Available Sufficient linear matrix inequality (LMI conditions to verify the robust stability and to design robust state feedback gains for the class of linear discrete-time systems with time-varying delay and polytopic uncertainties are presented. The conditions are obtained through parameter-dependent Lyapunov-Krasovskii functionals and use some extra variables, which yield less conservative LMI conditions. Both problems, robust stability analysis and robust synthesis, are formulated as convex problems where all system matrices can be affected by uncertainty. Some numerical examples are presented to illustrate the advantages of the proposed LMI conditions.
Global exponential stability for discrete-time neural networks with variable delays
International Nuclear Information System (INIS)
Chen Wuhua; Lu Xiaomei; Liang Dongying
2006-01-01
This Letter provides new exponential stability criteria for discrete-time neural networks with variable delays. The main technique is to reduce exponential convergence estimation of the neural network solution to that of one component of the corresponding solution by constructing Lyapunov function based on M-matrix. By introducing the tuning parameter diagonal matrix, the delay-independent and delay-dependent exponential stability conditions have been unified in the same mathematical formula. The effectiveness of the new results are illustrated by three examples
Dynamical Properties of Discrete-Time Background Neural Networks with Uniform Firing Rate
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Min Wan
2013-01-01
Full Text Available The dynamics of a discrete-time background network with uniform firing rate and background input is investigated. The conditions for stability are firstly derived. An invariant set is then obtained so that the nondivergence of the network can be guaranteed. In the invariant set, it is proved that all trajectories of the network starting from any nonnegative value will converge to a fixed point under some conditions. In addition, bifurcation and chaos are discussed. It is shown that the network can engender bifurcation and chaos with the increase of background input. The computations of Lyapunov exponents confirm the chaotic behaviors.
Game theory to characterize solutions of a discrete-time Hamilton-Jacobi equation
International Nuclear Information System (INIS)
Toledo, Porfirio
2013-01-01
We study the behavior of solutions of a discrete-time Hamilton-Jacobi equation in a minimax framework of game theory. The solutions of this problem represent the optimal payoff of a zero-sum game of two players, where the number of moves between the players converges to infinity. A real number, called the critical value, plays a central role in this work; this number is the asymptotic average action of optimal trajectories. The aim of this paper is to show the existence and characterization of solutions of a Hamilton-Jacobi equation for this kind of games
Guaranteed Cost Finite-Time Control of Discrete-Time Positive Impulsive Switched Systems
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Leipo Liu
2018-01-01
Full Text Available This paper considers the guaranteed cost finite-time boundedness of discrete-time positive impulsive switched systems. Firstly, the definition of guaranteed cost finite-time boundedness is introduced. By using the multiple linear copositive Lyapunov function (MLCLF and average dwell time (ADT approach, a state feedback controller is designed and sufficient conditions are obtained to guarantee that the corresponding closed-loop system is guaranteed cost finite-time boundedness (GCFTB. Such conditions can be solved by linear programming. Finally, a numerical example is provided to show the effectiveness of the proposed method.
Observer-based hyperchaos synchronization in cascaded discrete-time systems
International Nuclear Information System (INIS)
Grassi, Giuseppe
2009-01-01
This paper deals with the observer-based synchronization in a cascade connection of hyperchaotic discrete-time systems. The paper demonstrates that exact synchronization in finite time is achievable between pairs of drive-response systems using only a scalar synchronizing signal. This 'propagated synchronization' starts from the innermost drive-response system pair and propagates toward the outermost drive-system pair. Choosing the drive-system input to be an information signal (encrypted via an arbitrary encryption function) yields a potential application of this architecture in chaos-based communications.
The Iterative Solution to Discrete-Time H∞ Control Problems for Periodic Systems
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Ivan G. Ivanov
2016-03-01
Full Text Available This paper addresses the problem of solving discrete-time H ∞ control problems for periodic systems. The approach for solving such a type of equations is well known in the literature. However, the focus of our research is set on the numerical computation of the stabilizing solution. In particular, two effective methods for practical realization of the known iterative processes are described. Furthermore, a new iterative approach is investigated and applied. On the basis of numerical experiments, we compare the presented methods. A major conclusion is that the new iterative approach is faster than rest of the methods and it uses less RAM memory than other methods.
A VHDL Core for Intrinsic Evolution of Discrete Time Filters with Signal Feedback
Gwaltney, David A.; Dutton, Kenneth
2005-01-01
The design of an Evolvable Machine VHDL Core is presented, representing a discrete-time processing structure capable of supporting control system applications. This VHDL Core is implemented in an FPGA and is interfaced with an evolutionary algorithm implemented in firmware on a Digital Signal Processor (DSP) to create an evolvable system platform. The salient features of this architecture are presented. The capability to implement IIR filter structures is presented along with the results of the intrinsic evolution of a filter. The robustness of the evolved filter design is tested and its unique characteristics are described.
Optimal control of LQR for discrete time-varying systems with input delays
Yin, Yue-Zhu; Yang, Zhong-Lian; Yin, Zhi-Xiang; Xu, Feng
2018-04-01
In this work, we consider the optimal control problem of linear quadratic regulation for discrete time-variant systems with single input and multiple input delays. An innovative and simple method to derive the optimal controller is given. The studied problem is first equivalently converted into a problem subject to a constraint condition. Last, with the established duality, the problem is transformed into a static mathematical optimisation problem without input delays. The optimal control input solution to minimise performance index function is derived by solving this optimisation problem with two methods. A numerical simulation example is carried out and its results show that our two approaches are both feasible and very effective.
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Yueyang Li
2014-01-01
Full Text Available This paper investigates the H∞ fixed-lag fault estimator design for linear discrete time-varying (LDTV systems with intermittent measurements, which is described by a Bernoulli distributed random variable. Through constructing a novel partially equivalent dynamic system, the fault estimator design is converted into a deterministic quadratic minimization problem. By applying the innovation reorganization technique and the projection formula in Krein space, a necessary and sufficient condition is obtained for the existence of the estimator. The parameter matrices of the estimator are derived by recursively solving two standard Riccati equations. An illustrative example is provided to show the effectiveness and applicability of the proposed algorithm.
On the Solution of the Eigenvalue Assignment Problem for Discrete-Time Systems
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El-Sayed M. E. Mostafa
2017-01-01
Full Text Available The output feedback eigenvalue assignment problem for discrete-time systems is considered. The problem is formulated first as an unconstrained minimization problem, where a three-term nonlinear conjugate gradient method is proposed to find a local solution. In addition, a cut to the objective function is included, yielding an inequality constrained minimization problem, where a logarithmic barrier method is proposed for finding the local solution. The conjugate gradient method is further extended to tackle the eigenvalue assignment problem for the two cases of decentralized control systems and control systems with time delay. The performance of the methods is illustrated through various test examples.
Finite-Time Stability Analysis of Discrete-Time Linear Singular Systems
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Songlin Wo
2014-01-01
Full Text Available The finite-time stability (FTS problem of discrete-time linear singular systems (DTLSS is considered in this paper. A necessary and sufficient condition for FTS is obtained, which can be expressed in terms of matrix inequalities. Then, another form of the necessary and sufficient condition for FTS is also given by using matrix-null space technology. In order to solve the stability problem expediently, a sufficient condition for FTS is given via linear matrix inequality (LMI approach; this condition can be expressed in terms of LMIs. Finally, an illustrating example is also given to show the effectiveness of the proposed method.
Long- and Short-Term Cryptocurrency Volatility Components: A GARCH-MIDAS Analysis
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Christian Conrad
2018-05-01
Full Text Available We use the GARCH-MIDAS model to extract the long- and short-term volatility components of cryptocurrencies. As potential drivers of Bitcoin volatility, we consider measures of volatility and risk in the US stock market as well as a measure of global economic activity. We find that S&P 500 realized volatility has a negative and highly significant effect on long-term Bitcoin volatility. The finding is atypical for volatility co-movements across financial markets. Moreover, we find that the S&P 500 volatility risk premium has a significantly positive effect on long-term Bitcoin volatility. Finally, we find a strong positive association between the Baltic dry index and long-term Bitcoin volatility. This result shows that Bitcoin volatility is closely linked to global economic activity. Overall, our findings can be used to construct improved forecasts of long-term Bitcoin volatility.
Persistence of non-Markovian Gaussian stationary processes in discrete time
Nyberg, Markus; Lizana, Ludvig
2018-04-01
The persistence of a stochastic variable is the probability that it does not cross a given level during a fixed time interval. Although persistence is a simple concept to understand, it is in general hard to calculate. Here we consider zero mean Gaussian stationary processes in discrete time n . Few results are known for the persistence P0(n ) in discrete time, except the large time behavior which is characterized by the nontrivial constant θ through P0(n ) ˜θn . Using a modified version of the independent interval approximation (IIA) that we developed before, we are able to calculate P0(n ) analytically in z -transform space in terms of the autocorrelation function A (n ) . If A (n )→0 as n →∞ , we extract θ numerically, while if A (n )=0 , for finite n >N , we find θ exactly (within the IIA). We apply our results to three special cases: the nearest-neighbor-correlated "first order moving average process", where A (n )=0 for n >1 , the double exponential-correlated "second order autoregressive process", where A (n ) =c1λ1n+c2λ2n , and power-law-correlated variables, where A (n ) ˜n-μ . Apart from the power-law case when μ <5 , we find excellent agreement with simulations.
Discrete-time retrial queue with Bernoulli vacation, preemptive resume and feedback customers
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Peishu Chen
2015-09-01
Full Text Available Purpose: We consider a discrete-time Geo/G/1 retrial queue where the retrial time follows a general distribution, the server subject to Bernoulli vacation policy and the customer has preemptive resume priority, Bernoulli feedback strategy. The main purpose of this paper is to derive the generating functions of the stationary distribution of the system state, the orbit size and some important performance measures. Design/methodology: Using probability generating function technique, some valuable and interesting performance measures of the system are obtained. We also investigate two stochastic decomposition laws and present some numerical results. Findings: We obtain the probability generating functions of the system state distribution as well as those of the orbit size and the system size distributions. We also obtain some analytical expressions for various performance measures such as idle and busy probabilities, mean orbit and system sizes. Originality/value: The analysis of discrete-time retrial queues with Bernoulli vacation, preemptive resume and feedback customers is interesting and to the best of our knowledge, no other scientific journal paper has dealt with this question. This fact gives the reason why efforts should be taken to plug this gap.
Impulsive stabilization and impulsive synchronization of discrete-time delayed neural networks.
Chen, Wu-Hua; Lu, Xiaomei; Zheng, Wei Xing
2015-04-01
This paper investigates the problems of impulsive stabilization and impulsive synchronization of discrete-time delayed neural networks (DDNNs). Two types of DDNNs with stabilizing impulses are studied. By introducing the time-varying Lyapunov functional to capture the dynamical characteristics of discrete-time impulsive delayed neural networks (DIDNNs) and by using a convex combination technique, new exponential stability criteria are derived in terms of linear matrix inequalities. The stability criteria for DIDNNs are independent of the size of time delay but rely on the lengths of impulsive intervals. With the newly obtained stability results, sufficient conditions on the existence of linear-state feedback impulsive controllers are derived. Moreover, a novel impulsive synchronization scheme for two identical DDNNs is proposed. The novel impulsive synchronization scheme allows synchronizing two identical DDNNs with unknown delays. Simulation results are given to validate the effectiveness of the proposed criteria of impulsive stabilization and impulsive synchronization of DDNNs. Finally, an application of the obtained impulsive synchronization result for two identical chaotic DDNNs to a secure communication scheme is presented.
International Nuclear Information System (INIS)
Gómez de León, F C; Meroño Pérez, P A
2010-01-01
The traditional method for measuring the velocity and the angular vibration in the shaft of rotating machines using incremental encoders is based on counting the pulses at given time intervals. This method is generically called the time interval measurement system (TIMS). A variant of this method that we have developed in this work consists of measuring the corresponding time of each pulse from the encoder and sampling the signal by means of an A/D converter as if it were an analog signal, that is to say, in discrete time. For this reason, we have denominated this method as the discrete time interval measurement system (DTIMS). This measurement system provides a substantial improvement in the precision and frequency resolution compared with the traditional method of counting pulses. In addition, this method permits modification of the width of some pulses in order to obtain a mark-phase on every lap. This paper explains the theoretical fundamentals of the DTIMS and its application for measuring the angular vibrations of rotating machines. It also displays the required relationship between the sampling rate of the signal, the number of pulses of the encoder and the rotating velocity in order to obtain the required resolution and to delimit the methodological errors in the measurement
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Mengjuan Cao
2014-01-01
Full Text Available The linear discrete-time descriptor noncausal multirate system is considered for the presentation of a new design approach for optimal preview control. First, according to the characteristics of causal controllability and causal observability, the descriptor noncausal system is constructed into a descriptor causal closed-loop system. Second, by using the characteristics of the causal system and elementary transformation, the descriptor causal closed-loop system is transformed into a normal system. Then, taking advantage of the discrete lifting technique, the normal multirate system is converted to a single-rate system. By making use of the standard preview control method, we construct the descriptor augmented error system. The quadratic performance index for the multirate system is given, which can be changed into one for the single-rate system. In addition, a new single-rate system is obtained, the optimal control law of which is given. Returning to the original system, the optimal preview controller for linear discrete-time descriptor noncausal multirate systems is derived. The stabilizability and detectability of the lifted single-rate system are discussed in detail. The optimal preview control design techniques are illustrated by simulation results for a simple example.
Cai, Chao-Ran; Wu, Zhi-Xi; Guan, Jian-Yue
2014-11-01
Recently, Gómez et al. proposed a microscopic Markov-chain approach (MMCA) [S. Gómez, J. Gómez-Gardeñes, Y. Moreno, and A. Arenas, Phys. Rev. E 84, 036105 (2011)PLEEE81539-375510.1103/PhysRevE.84.036105] to the discrete-time susceptible-infected-susceptible (SIS) epidemic process and found that the epidemic prevalence obtained by this approach agrees well with that by simulations. However, we found that the approach cannot be straightforwardly extended to a susceptible-infected-recovered (SIR) epidemic process (due to its irreversible property), and the epidemic prevalences obtained by MMCA and Monte Carlo simulations do not match well when the infection probability is just slightly above the epidemic threshold. In this contribution we extend the effective degree Markov-chain approach, proposed for analyzing continuous-time epidemic processes [J. Lindquist, J. Ma, P. Driessche, and F. Willeboordse, J. Math. Biol. 62, 143 (2011)JMBLAJ0303-681210.1007/s00285-010-0331-2], to address discrete-time binary-state (SIS) or three-state (SIR) epidemic processes on uncorrelated complex networks. It is shown that the final epidemic size as well as the time series of infected individuals obtained from this approach agree very well with those by Monte Carlo simulations. Our results are robust to the change of different parameters, including the total population size, the infection probability, the recovery probability, the average degree, and the degree distribution of the underlying networks.
Chen, Xiaofeng; Song, Qiankun; Li, Zhongshan; Zhao, Zhenjiang; Liu, Yurong
2018-07-01
This paper addresses the problem of stability for continuous-time and discrete-time quaternion-valued neural networks (QVNNs) with linear threshold neurons. Applying the semidiscretization technique to the continuous-time QVNNs, the discrete-time analogs are obtained, which preserve the dynamical characteristics of their continuous-time counterparts. Via the plural decomposition method of quaternion, homeomorphic mapping theorem, as well as Lyapunov theorem, some sufficient conditions on the existence, uniqueness, and global asymptotical stability of the equilibrium point are derived for the continuous-time QVNNs and their discrete-time analogs, respectively. Furthermore, a uniform sufficient condition on the existence, uniqueness, and global asymptotical stability of the equilibrium point is obtained for both continuous-time QVNNs and their discrete-time version. Finally, two numerical examples are provided to substantiate the effectiveness of the proposed results.
Modelling the Volatility-Return Trade-off when Volatility may be Nonstationary
DEFF Research Database (Denmark)
Dahl, Christian Møller; Iglesias, Emma M.
In this paper a new GARCH-M type model, denoted the GARCH-AR, is proposed. In particular, it is shown that it is possible to generate a volatility-return trade-off in a regression model simply by introducing dynamics in the standardized disturbance process. Importantly, the volatility in the GARCH......, we provide an empirical illustration showing the empirical relevance of the GARCH-AR model based on modelling a wide range of leading US stock return series....
Global exponential stability of BAM neural networks with time-varying delays: The discrete-time case
Raja, R.; Marshal Anthoni, S.
2011-02-01
This paper deals with the problem of stability analysis for a class of discrete-time bidirectional associative memory (BAM) neural networks with time-varying delays. By employing the Lyapunov functional and linear matrix inequality (LMI) approach, a new sufficient conditions is proposed for the global exponential stability of discrete-time BAM neural networks. The proposed LMI based results can be easily checked by LMI control toolbox. Moreover, an example is also provided to demonstrate the effectiveness of the proposed method.
Liu, Hongjian; Wang, Zidong; Shen, Bo; Huang, Tingwen; Alsaadi, Fuad E
2018-06-01
This paper is concerned with the globally exponential stability problem for a class of discrete-time stochastic memristive neural networks (DSMNNs) with both leakage delays as well as probabilistic time-varying delays. For the probabilistic delays, a sequence of Bernoulli distributed random variables is utilized to determine within which intervals the time-varying delays fall at certain time instant. The sector-bounded activation function is considered in the addressed DSMNN. By taking into account the state-dependent characteristics of the network parameters and choosing an appropriate Lyapunov-Krasovskii functional, some sufficient conditions are established under which the underlying DSMNN is globally exponentially stable in the mean square. The derived conditions are made dependent on both the leakage and the probabilistic delays, and are therefore less conservative than the traditional delay-independent criteria. A simulation example is given to show the effectiveness of the proposed stability criterion. Copyright © 2018 Elsevier Ltd. All rights reserved.
A discrete-time queueing system with changes in the vacation times
Directory of Open Access Journals (Sweden)
Atencia Ivan
2016-06-01
Full Text Available This paper considers a discrete-time queueing system in which an arriving customer can decide to follow a last come first served (LCFS service discipline or to become a negative customer that eliminates the one at service, if any. After service completion, the server can opt for a vacation time or it can remain on duty. Changes in the vacation times as well as their associated distribution are thoroughly studied. An extensive analysis of the system is carried out and, using a probability generating function approach, steady-state performance measures such as the first moments of the busy period of the queue content and of customers delay are obtained. Finally, some numerical examples to show the influence of the parameters on several performance characteristics are given.
Neural networks for tracking of unknown SISO discrete-time nonlinear dynamic systems.
Aftab, Muhammad Saleheen; Shafiq, Muhammad
2015-11-01
This article presents a Lyapunov function based neural network tracking (LNT) strategy for single-input, single-output (SISO) discrete-time nonlinear dynamic systems. The proposed LNT architecture is composed of two feedforward neural networks operating as controller and estimator. A Lyapunov function based back propagation learning algorithm is used for online adjustment of the controller and estimator parameters. The controller and estimator error convergence and closed-loop system stability analysis is performed by Lyapunov stability theory. Moreover, two simulation examples and one real-time experiment are investigated as case studies. The achieved results successfully validate the controller performance. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.
Design of an optimal preview controller for linear discrete-time descriptor systems with state delay
Cao, Mengjuan; Liao, Fucheng
2015-04-01
In this paper, the linear discrete-time descriptor system with state delay is studied, and a design method for an optimal preview controller is proposed. First, by using the discrete lifting technique, the original system is transformed into a general descriptor system without state delay in form. Then, taking advantage of the first-order forward difference operator, we construct a descriptor augmented error system, including the state vectors of the lifted system, error vectors, and desired target signals. Rigorous mathematical proofs are given for the regularity, stabilisability, causal controllability, and causal observability of the descriptor augmented error system. Based on these, the optimal preview controller with preview feedforward compensation for the original system is obtained by using the standard optimal regulator theory of the descriptor system. The effectiveness of the proposed method is shown by numerical simulation.
Sun, Ying; Ding, Derui; Zhang, Sunjie; Wei, Guoliang; Liu, Hongjian
2018-07-01
In this paper, the non-fragile ?-? control problem is investigated for a class of discrete-time stochastic nonlinear systems under event-triggered communication protocols, which determine whether the measurement output should be transmitted to the controller or not. The main purpose of the addressed problem is to design an event-based output feedback controller subject to gain variations guaranteeing the prescribed disturbance attenuation level described by the ?-? performance index. By utilizing the Lyapunov stability theory combined with S-procedure, a sufficient condition is established to guarantee both the exponential mean-square stability and the ?-? performance for the closed-loop system. In addition, with the help of the orthogonal decomposition, the desired controller parameter is obtained in terms of the solution to certain linear matrix inequalities. Finally, a simulation example is exploited to demonstrate the effectiveness of the proposed event-based controller design scheme.
Switched periodic systems in discrete time: stability and input-output norms
Bolzern, Paolo; Colaneri, Patrizio
2013-07-01
This paper deals with the analysis of stability and the characterisation of input-output norms for discrete-time periodic switched linear systems. Such systems consist of a network of time-periodic linear subsystems sharing the same state vector and an exogenous switching signal that triggers the jumps between the subsystems. The overall system exhibits a complex dynamic behaviour due to the interplay between the time periodicity of the subsystem parameters and the switching signal. Both arbitrary switching signals and signals satisfying a dwell-time constraint are considered. Linear matrix inequality conditions for stability and guaranteed H2 and H∞ performances are provided. The results heavily rely on the merge of the theory of linear periodic systems and recent developments on switched linear time-invariant systems.
Time-dependent switched discrete-time linear systems control and filtering
Zhang, Lixian; Shi, Peng; Lu, Qiugang
2016-01-01
This book focuses on the basic control and filtering synthesis problems for discrete-time switched linear systems under time-dependent switching signals. Chapter 1, as an introduction of the book, gives the backgrounds and motivations of switched systems, the definitions of the typical time-dependent switching signals, the differences and links to other types of systems with hybrid characteristics and a literature review mainly on the control and filtering for the underlying systems. By summarizing the multiple Lyapunov-like functions (MLFs) approach in which different requirements on comparisons of Lyapunov function values at switching instants, a series of methodologies are developed for the issues on stability and stabilization, and l2-gain performance or tube-based robustness for l∞ disturbance, respectively, in Chapters 2 and 3. Chapters 4 and 5 are devoted to the control and filtering problems for the time-dependent switched linear systems with either polytopic uncertainties or measurable time-varying...
Fault-tolerant Control of Discrete-time LPV systems using Virtual Actuators and Sensors
DEFF Research Database (Denmark)
Tabatabaeipour, Mojtaba; Stoustrup, Jakob; Bak, Thomas
2015-01-01
This paper proposes a new fault-tolerant control (FTC) method for discrete-time linear parameter varying (LPV) systems using a reconfiguration block. The basic idea of the method is to achieve the FTC goal without re-designing the nominal controller by inserting a reconfiguration block between......, it transforms the output of the controller for the faulty system such that the stability and performance goals are preserved. Input-to-state stabilizing LPV gains of the virtual actuator and sensor are obtained by solving linear matrix inequalities (LMIs). We show that separate design of these gains guarantees....... Finally, the effectiveness of the method is demonstrated via a numerical example and stator current control of an induction motor....
Optimal maintenance policy for a system subject to damage in a discrete time process
International Nuclear Information System (INIS)
Chien, Yu-Hung; Sheu, Shey-Huei; Zhang, Zhe George
2012-01-01
Consider a system operating over n discrete time periods (n=1, 2, …). Each operation period causes a random amount of damage to the system which accumulates over time periods. The system fails when the cumulative damage exceeds a failure level ζ and a corrective maintenance (CM) action is immediately taken. To prevent such a failure, a preventive maintenance (PM) may be performed. In an operation period without a CM or PM, a regular maintenance (RM) is conducted at the end of that period to maintain the operation of the system. We propose a maintenance policy which prescribes a PM when the accumulated damage exceeds a pre-specified level δ ( ⁎ and N ⁎ and discuss some useful properties about them. It has been shown that a δ-based PM outperforms a N-based PM in terms of cost minimization. Numerical examples are presented to demonstrate the optimization of this class of maintenance policies.
Simultaneous Robust Fault and State Estimation for Linear Discrete-Time Uncertain Systems
Directory of Open Access Journals (Sweden)
Feten Gannouni
2017-01-01
Full Text Available We consider the problem of robust simultaneous fault and state estimation for linear uncertain discrete-time systems with unknown faults which affect both the state and the observation matrices. Using transformation of the original system, a new robust proportional integral filter (RPIF having an error variance with an optimized guaranteed upper bound for any allowed uncertainty is proposed to improve robust estimation of unknown time-varying faults and to improve robustness against uncertainties. In this study, the minimization problem of the upper bound of the estimation error variance is formulated as a convex optimization problem subject to linear matrix inequalities (LMI for all admissible uncertainties. The proportional and the integral gains are optimally chosen by solving the convex optimization problem. Simulation results are given in order to illustrate the performance of the proposed filter, in particular to solve the problem of joint fault and state estimation.
Fast state estimation subject to random data loss in discrete-time nonlinear stochastic systems
Mahdi Alavi, S. M.; Saif, Mehrdad
2013-12-01
This paper focuses on the design of the standard observer in discrete-time nonlinear stochastic systems subject to random data loss. By the assumption that the system response is incrementally bounded, two sufficient conditions are subsequently derived that guarantee exponential mean-square stability and fast convergence of the estimation error for the problem at hand. An efficient algorithm is also presented to obtain the observer gain. Finally, the proposed methodology is employed for monitoring the Continuous Stirred Tank Reactor (CSTR) via a wireless communication network. The effectiveness of the designed observer is extensively assessed by using an experimental tested-bed that has been fabricated for performance evaluation of the over wireless-network estimation techniques under realistic radio channel conditions.
Directory of Open Access Journals (Sweden)
Saïda Bedoui
2013-01-01
Full Text Available This paper addresses the problem of simultaneous identification of linear discrete time delay multivariable systems. This problem involves both the estimation of the time delays and the dynamic parameters matrices. In fact, we suggest a new formulation of this problem allowing defining the time delay and the dynamic parameters in the same estimated vector and building the corresponding observation vector. Then, we use this formulation to propose a new method to identify the time delays and the parameters of these systems using the least square approach. Convergence conditions and statistics properties of the proposed method are also developed. Simulation results are presented to illustrate the performance of the proposed method. An application of the developed approach to compact disc player arm is also suggested in order to validate simulation results.
Consensus of discrete-time multi-agent systems with adversaries and time delays
Wu, Yiming; He, Xiongxiong; Liu, Shuai; Xie, Lihua
2014-05-01
This paper studies the resilient asymptotic consensus problem for discrete-time multi-agent systems in the presence of adversaries and transmission delays. The network is assumed to have ? loyal agents and ? adversarial agents, and each loyal agent in the network has no knowledge of the network topology other than an upper bound on the number of adversarial agents in its neighborhood. For the considered networked system, only locally delayed information is available for each loyal agent, and also the information flow is directed and a control protocol using only local information is designed to guarantee the realization of consensus with respect to communication graph, which satisfies a featured network robustness. Numerical examples are finally given to demonstrate the effectiveness of theoretical results.
Transformation of nonlinear discrete-time system into the extended observer form
Kaparin, V.; Kotta, Ü.
2018-04-01
The paper addresses the problem of transforming discrete-time single-input single-output nonlinear state equations into the extended observer form, which, besides the input and output, also depends on a finite number of their past values. Necessary and sufficient conditions for the existence of both the extended coordinate and output transformations, solving the problem, are formulated in terms of differential one-forms, associated with the input-output equation, corresponding to the state equations. An algorithm for transformation of state equations into the extended observer form is proposed and illustrated by an example. Moreover, the considered approach is compared with the method of dynamic observer error linearisation, which likewise is intended to enlarge the class of systems transformable into an observer form.
Bifurcation and complex dynamics of a discrete-time predator-prey system involving group defense
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S. M. Sohel Rana
2015-09-01
Full Text Available In this paper, we investigate the dynamics of a discrete-time predator-prey system involving group defense. The existence and local stability of positive fixed point of the discrete dynamical system is analyzed algebraically. It is shown that the system undergoes a flip bifurcation and a Neimark-Sacker bifurcation in the interior of R+2 by using bifurcation theory. Numerical simulation results not only show the consistence with the theoretical analysis but also display the new and interesting dynamical behaviors, including phase portraits, period-7, 20-orbits, attracting invariant circle, cascade of period-doubling bifurcation from period-20 leading to chaos, quasi-periodic orbits, and sudden disappearance of the chaotic dynamics and attracting chaotic set. The Lyapunov exponents are numerically computed to characterize the complexity of the dynamical behaviors.
Homogenous polynomially parameter-dependent H∞ filter designs of discrete-time fuzzy systems.
Zhang, Huaguang; Xie, Xiangpeng; Tong, Shaocheng
2011-10-01
This paper proposes a novel H(∞) filtering technique for a class of discrete-time fuzzy systems. First, a novel kind of fuzzy H(∞) filter, which is homogenous polynomially parameter dependent on membership functions with an arbitrary degree, is developed to guarantee the asymptotic stability and a prescribed H(∞) performance of the filtering error system. Second, relaxed conditions for H(∞) performance analysis are proposed by using a new fuzzy Lyapunov function and the Finsler lemma with homogenous polynomial matrix Lagrange multipliers. Then, based on a new kind of slack variable technique, relaxed linear matrix inequality-based H(∞) filtering conditions are proposed. Finally, two numerical examples are provided to illustrate the effectiveness of the proposed approach.
Directory of Open Access Journals (Sweden)
Liyun Su
2011-01-01
Full Text Available In order to suppress the interference of the strong fractional noise signal in discrete-time ultrawideband (UWB systems, this paper presents a new UWB multi-scale Kalman filter (KF algorithm for the interference suppression. This approach solves the problem of the narrowband interference (NBI as nonstationary fractional signal in UWB communication, which does not need to estimate any channel parameter. In this paper, the received sampled signal is transformed through multiscale wavelet to obtain a state transition equation and an observation equation based on the stationarity theory of wavelet coefficients in time domain. Then through the Kalman filter method, fractional signal of arbitrary scale is easily figured out. Finally, fractional noise interference is subtracted from the received signal. Performance analysis and computer simulations reveal that this algorithm is effective to reduce the strong fractional noise when the sampling rate is low.
Fault detection for discrete-time LPV systems using interval observers
Zhang, Zhi-Hui; Yang, Guang-Hong
2017-10-01
This paper is concerned with the fault detection (FD) problem for discrete-time linear parameter-varying systems subject to bounded disturbances. A parameter-dependent FD interval observer is designed based on parameter-dependent Lyapunov and slack matrices. The design method is presented by translating the parameter-dependent linear matrix inequalities (LMIs) into finite ones. In contrast to the existing results based on parameter-independent and diagonal Lyapunov matrices, the derived disturbance attenuation, fault sensitivity and nonnegative conditions lead to less conservative LMI characterisations. Furthermore, without the need to design the residual evaluation functions and thresholds, the residual intervals generated by the interval observers are used directly for FD decision. Finally, simulation results are presented for showing the effectiveness and superiority of the proposed method.
Variable speed wind turbine control by discrete-time sliding mode approach.
Torchani, Borhen; Sellami, Anis; Garcia, Germain
2016-05-01
The aim of this paper is to propose a new design variable speed wind turbine control by discrete-time sliding mode approach. This methodology is designed for linear saturated system. The saturation constraint is reported on inputs vector. To this end, the back stepping design procedure is followed to construct a suitable sliding manifold that guarantees the attainment of a stabilization control objective. It is well known that the mechanisms are investigated in term of the most proposed assumptions to deal with the damping, shaft stiffness and inertia effect of the gear. The objectives are to synthesize robust controllers that maximize the energy extracted from wind, while reducing mechanical loads and rotor speed tracking combined with an electromagnetic torque. Simulation results of the proposed scheme are presented. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.
International Nuclear Information System (INIS)
Banu, L Jarina; Balasubramaniam, P
2015-01-01
This paper investigates the problem of non-fragile observer design for a class of discrete-time genetic regulatory networks (DGRNs) with time-varying delays and randomly occurring uncertainties. A non-fragile observer is designed, for estimating the true concentration of mRNAs and proteins from available measurement outputs. One important feature of the results obtained that are reported here is that the parameter uncertainties are assumed to be random and their probabilities of occurrence are known a priori. On the basis of the Lyapunov–Krasovskii functional approach and using a convex combination technique, a delay-dependent estimation criterion is established for DGRNs in terms of linear matrix inequalities (LMIs) that can be efficiently solved using any available LMI solver. Finally numerical examples are provided to substantiate the theoretical results. (paper)
Frequency-shaped and observer-based discrete-time sliding mode control
Mehta, Axaykumar
2015-01-01
It is well established that the sliding mode control strategy provides an effective and robust method of controlling the deterministic system due to its well-known invariance property to a class of bounded disturbance and parameter variations. Advances in microcomputer technologies have made digital control increasingly popular among the researchers worldwide. And that led to the study of discrete-time sliding mode control design and its implementation. This brief presents, a method for multi-rate frequency shaped sliding mode controller design based on switching and non-switching type of reaching law. In this approach, the frequency dependent compensator dynamics are introduced through a frequency-shaped sliding surface by assigning frequency dependent weighing matrices in a linear quadratic regulator (LQR) design procedure. In this way, the undesired high frequency dynamics or certain frequency disturbance can be eliminated. The states are implicitly obtained by measuring the output at a faster rate than th...
Robust extended Kalman filter of discrete-time Markovian jump nonlinear system under uncertain noise
International Nuclear Information System (INIS)
Zhu, Jin; Park, Jun Hong; Lee, Kwan Soo; Spiryagin, Maksym
2008-01-01
This paper examines the problem of robust extended Kalman filter design for discrete -time Markovian jump nonlinear systems with noise uncertainty. Because of the existence of stochastic Markovian switching, the state and measurement equations of underlying system are subject to uncertain noise whose covariance matrices are time-varying or un-measurable instead of stationary. First, based on the expression of filtering performance deviation, admissible uncertainty of noise covariance matrix is given. Secondly, two forms of noise uncertainty are taken into account: Non- Structural and Structural. It is proved by applying game theory that this filter design is a robust mini-max filter. A numerical example shows the validity of the method
Attractors of relaxation discrete-time systems with chaotic dynamics on a fast time scale
International Nuclear Information System (INIS)
Maslennikov, Oleg V.; Nekorkin, Vladimir I.
2016-01-01
In this work, a new type of relaxation systems is considered. Their prominent feature is that they comprise two distinct epochs, one is slow regular motion and another is fast chaotic motion. Unlike traditionally studied slow-fast systems that have smooth manifolds of slow motions in the phase space and fast trajectories between them, in this new type one observes, apart the same geometric objects, areas of transient chaos. Alternating periods of slow regular motions and fast chaotic ones as well as transitions between them result in a specific chaotic attractor with chaos on a fast time scale. We formulate basic properties of such attractors in the framework of discrete-time systems and consider several examples. Finally, we provide an important application of such systems, the neuronal electrical activity in the form of chaotic spike-burst oscillations.
Discrete-time recurrent neural networks with time-varying delays: Exponential stability analysis
International Nuclear Information System (INIS)
Liu, Yurong; Wang, Zidong; Serrano, Alan; Liu, Xiaohui
2007-01-01
This Letter is concerned with the analysis problem of exponential stability for a class of discrete-time recurrent neural networks (DRNNs) with time delays. The delay is of the time-varying nature, and the activation functions are assumed to be neither differentiable nor strict monotonic. Furthermore, the description of the activation functions is more general than the recently commonly used Lipschitz conditions. Under such mild conditions, we first prove the existence of the equilibrium point. Then, by employing a Lyapunov-Krasovskii functional, a unified linear matrix inequality (LMI) approach is developed to establish sufficient conditions for the DRNNs to be globally exponentially stable. It is shown that the delayed DRNNs are globally exponentially stable if a certain LMI is solvable, where the feasibility of such an LMI can be easily checked by using the numerically efficient Matlab LMI Toolbox. A simulation example is presented to show the usefulness of the derived LMI-based stability condition
Allee effect in a discrete-time predator-prey system
International Nuclear Information System (INIS)
Celik, Canan; Duman, Oktay
2009-01-01
In this paper, we study the stability of a discrete-time predator-prey system with and without Allee effect. By analyzing both systems, we first obtain local stability conditions of the equilibrium points without the Allee effect and then exhibit the impact of the Allee effect on stability when it is imposed on prey population. We also show the stabilizing effect of Allee effect by numerical simulations and verify that when the prey population is subject to an Allee effect, the trajectory of the solutions approximates to the corresponding equilibrium point much faster. Furthermore, for some fixed parameter values satisfying necessary conditions, we show that the corresponding equilibrium point moves from instability to stability under the Allee effect on prey population.
THE IMPACT OF POLITICAL AND ECONOMIC NEWS ON THE EURO/RON EXCHANGE RATE: A GARCH APPROACH
Cristi Spulbar; Mihai Nitoi
2012-01-01
Within this study we try to capture the impact of political news and economic news from euro area on the exchange rate between Romanian currency and euro. In order to do this we used a GARCH model. As we observed, both variables influence the exchange rate, this fact implying national currency depreciation and a volatility growth. The political news and the economic news positively affect the euro/ron exchange rate volatility. The two factors conjugation, as it has happened in the recent peri...
THE IMPACT OF POLITICAL AND ECONOMIC NEWS ON THE EURO/RON EXCHANGE RATE: A GARCH APPROACH
Directory of Open Access Journals (Sweden)
Mihai Niţoi
2012-12-01
Full Text Available Within this study we try to capture the impact of political news and economic news from euro area on the exchange rate between Romanian currency and euro. In order to do this we used a GARCH model. As we observed, both variables influence the exchange rate, this fact implying national currency depreciation and a volatility growth. The political news and the economic news positively affect the euro/ron exchange rate volatility. The two factors conjugation, as it has happened in the recent period is to be avoided because it can have financial and economic consequences with a very high cost for Romania.
Maximum likelihood unit rooting test in the presence GARCH: A new test with increased power
Cook , Steve
2008-01-01
Abstract The literature on testing the unit root hypothesis in the presence of GARCH errors is extended. A new test based upon the combination of local-to-unity detrending and joint maximum likelihood estimation of the autoregressive parameter and GARCH process is presented. The finite sample distribution of the test is derived under alternative decisions regarding the deterministic terms employed. Using Monte Carlo simulation, the newly proposed ML t-test is shown to exhibit incre...
Ettore Spalletti: Salle des départs a Garches
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Andrea Dall'Asta
2012-06-01
Full Text Available Ettore Spalletti re-inventa nel 1996 l’obitorio dell’ospedale Raymond Poincaré a Garches - alle porte di Parigi. È uno spazio privo di simboli religiosi, in cui i corpi, posti nella bara, sono esposti all’ultimo sguardo dei familiari e degli amici. È la Salle des départs, sala delle partenze, in cui ogni uomo è chiamato a soggiornare - musulmano, cristiano, non credente – per il breve transito dal mondo della vita a quello della morte, verso una nuova vita. L’intento di Spalletti è quello di umanizzare un luogo che aiuti le persone a elaborare il lutto, infondendo pace e serenità. Da uno spazio anonimo, grazie alla forza espressiva del colore azzurro, come quello del manto di una Madonna che accoglie i suoi figli, l’artista ci fa immergere in un luogo che si presenta come l’incarnazione della purezza, diventando simbolo della promessa della trascendenza e dell’assoluto.
Wang, Licheng; Wang, Zidong; Han, Qing-Long; Wei, Guoliang
2017-09-06
The synchronization control problem is investigated for a class of discrete-time dynamical networks with packet dropouts via a coding-decoding-based approach. The data is transmitted through digital communication channels and only the sequence of finite coded signals is sent to the controller. A series of mutually independent Bernoulli distributed random variables is utilized to model the packet dropout phenomenon occurring in the transmissions of coded signals. The purpose of the addressed synchronization control problem is to design a suitable coding-decoding procedure for each node, based on which an efficient decoder-based control protocol is developed to guarantee that the closed-loop network achieves the desired synchronization performance. By applying a modified uniform quantization approach and the Kronecker product technique, criteria for ensuring the detectability of the dynamical network are established by means of the size of the coding alphabet, the coding period and the probability information of packet dropouts. Subsequently, by resorting to the input-to-state stability theory, the desired controller parameter is obtained in terms of the solutions to a certain set of inequality constraints which can be solved effectively via available software packages. Finally, two simulation examples are provided to demonstrate the effectiveness of the obtained results.
International Nuclear Information System (INIS)
Li Hongjie; Yue Dong
2010-01-01
The paper investigates the synchronization stability problem for a class of complex dynamical networks with Markovian jumping parameters and mixed time delays. The complex networks consist of m modes and the networks switch from one mode to another according to a Markovian chain with known transition probability. The mixed time delays are composed of discrete and distributed delays, the discrete time delay is assumed to be random and its probability distribution is known a priori. In terms of the probability distribution of the delays, the new type of system model with probability-distribution-dependent parameter matrices is proposed. Based on the stochastic analysis techniques and the properties of the Kronecker product, delay-dependent synchronization stability criteria in the mean square are derived in the form of linear matrix inequalities which can be readily solved by using the LMI toolbox in MATLAB, the solvability of derived conditions depends on not only the size of the delay, but also the probability of the delay-taking values in some intervals. Finally, a numerical example is given to illustrate the feasibility and effectiveness of the proposed method.
Oil shock transmission to stock market returns: Wavelet-multivariate Markov switching GARCH approach
International Nuclear Information System (INIS)
Jammazi, Rania
2012-01-01
Since oil prices are typically governed by nonlinear and chaotic behavior, it’s become rather difficult to capture the dominant properties of their fluctuations. In recent years, unprecedented interest emerged on the decomposition methods in order to capture drifts or spikes relatively to this data. Together, our understanding of the nature of crude oil price shocks and their effects on the stock market returns has evolved noticeably. We accommodate these findings to investigate two issues that have been at the center of recent debates on the effect of crude oil shocks on the stock market returns of five developed countries (USA, UK, Japan, Germany and Canada). First, we analyze whether shocks and or volatility emanating from two major crude oil markets are transmitted to the equity markets. We do this by applying, the Haar A Trous Wavelet decomposition to monthly real crude oil series in a first step, and the trivariate BEKK Markov Switching GARCH model to analyze the effect of the smooth part on the degree of the stock market instability in a second step. The motivation behind the use of the former method is that noises and erratic behavior often appeared at the edge of the signal, can affect the quality of the shock and thus increase erroneous results of the shock transmission to the stock market. The proposed model is able to circumvent the path dependency problem that can influence the prediction’s robustness and can provide useful information for investors and government agencies that have largely based their views on the notion that crude oil markets affect negatively stock market returns. Second, under the hypothesis of common increased volatility, we investigate whether these states happen around the identified international crises. Indeed, the results show that the A Haar Trous Wavelet decomposition method appears to be an important step toward improving accuracy of the smooth signal in detecting key real crude oil volatility features. Additionally
Kim, Wonhee; Chen, Xu; Lee, Youngwoo; Chung, Chung Choo; Tomizuka, Masayoshi
2018-05-01
A discrete-time backstepping control algorithm is proposed for reference tracking of systems affected by both broadband disturbances at low frequencies and narrow band disturbances at high frequencies. A discrete time DOB, which is constructed based on infinite impulse response filters is applied to compensate for narrow band disturbances at high frequencies. A discrete-time nonlinear damping backstepping controller with an augmented observer is proposed to track the desired output and to compensate for low frequency broadband disturbances along with a disturbance observer, for rejecting narrow band high frequency disturbances. This combination has the merit of simultaneously compensating both broadband disturbances at low frequencies and narrow band disturbances at high frequencies. The performance of the proposed method is validated via experiments.
State control of discrete-time linear systems to be bound in state variables by equality constraints
International Nuclear Information System (INIS)
Filasová, Anna; Krokavec, Dušan; Serbák, Vladimír
2014-01-01
The paper is concerned with the problem of designing the discrete-time equivalent PI controller to control the discrete-time linear systems in such a way that the closed-loop state variables satisfy the prescribed equality constraints. Since the problem is generally singular, using standard form of the Lyapunov function and a symmetric positive definite slack matrix, the design conditions are proposed in the form of the enhanced Lyapunov inequality. The results, offering the conditions of the control existence and the optimal performance with respect to the prescribed equality constraints for square discrete-time linear systems, are illustrated with the numerical example to note effectiveness and applicability of the considered approach
Rodolfo Cermeño; Benjamín Oliva
2010-01-01
In this paper we investigate empirically the relationship among conditional mean and variances of exchange rate depreciation, inflation and output growth in Mexico using a multivariate GARCH-in-mean model (MGARCH-M). The study is performed with monthly data over the period 1993-2009. The results support the existence of a positive relationship between exchange rate depreciation and its volatility as well as a negative effect of exchange rate uncertainty on output growth. On the other hand, no...
Estimating 'Value at Risk' of crude oil price and its spillover effect using the GED-GARCH approach
International Nuclear Information System (INIS)
Fan, Ying; Wei, Yi-Ming; Zhang, Yue-Jun; Tsai, Hsien-Tang
2008-01-01
Estimation has been carried out using GARCH-type models, based on the Generalized Error Distribution (GED), for both the extreme downside and upside Value-at-Risks (VaR) of returns in the WTI and Brent crude oil spot markets. Furthermore, according to a new concept of Granger causality in risk, a kernel-based test is proposed to detect extreme risk spillover effect between the two oil markets. Results of an empirical study indicate that the GED-GARCH-based VaR approach appears more effective than the well-recognized HSAF (i.e. historical simulation with ARMA forecasts). Moreover, this approach is also more realistic and comprehensive than the standard normal distribution-based VaR model that is commonly used. Results reveal that there is significant two-way risk spillover effect between WTI and Brent markets. Supplementary study indicates that at the 99% confidence level, when negative market news arises that brings about a slump in oil price return, historical information on risk in the WTI market helps to forecast the Brent market. Conversely, it is not the case when positive news occurs and returns rise. Historical information on risk in the two markets can facilitate forecasts of future extreme market risks for each other. These results are valuable for anyone who needs evaluation and forecasts of the risk situation in international crude oil markets. (author)
A Generalized Stability Theorem for Discrete-Time Nonautonomous Chaos System with Applications
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Mei Zhang
2015-01-01
Full Text Available Firstly, this study introduces a definition of generalized stability (GST in discrete-time nonautonomous chaos system (DNCS, which is an extension for chaos generalized synchronization. Secondly, a constructive theorem of DNCS has been proposed. As an example, a GST DNCS is constructed based on a novel 4-dimensional discrete chaotic map. Numerical simulations show that the dynamic behaviors of this map have chaotic attractor characteristics. As one application, we design a chaotic pseudorandom number generator (CPRNG based on the GST DNCS. We use the SP800-22 test suite to test the randomness of four 100-key streams consisting of 1,000,000 bits generated by the CPRNG, the RC4 algorithm, the ZUC algorithm, and a 6-dimensional CGS-based CPRNG, respectively. The numerical results show that the randomness performances of the two CPRNGs are promising. In addition, theoretically the key space of the CPRNG is larger than 21116. As another application, this study designs a stream avalanche encryption scheme (SAES in RGB image encryption. The results show that the GST DNCS is able to generate the avalanche effects which are similar to those generated via ideal CPRNGs.
Rational solutions of the discrete time Toda lattice and the alternate discrete Painleve II equation
International Nuclear Information System (INIS)
Common, Alan K; Hone, Andrew N W
2008-01-01
The Yablonskii-Vorob'ev polynomials y n (t), which are defined by a second-order bilinear differential-difference equation, provide rational solutions of the Toda lattice. They are also polynomial tau-functions for the rational solutions of the second Painleve equation (P II ). Here we define two-variable polynomials Y n (t, h) on a lattice with spacing h, by considering rational solutions of the discrete time Toda lattice as introduced by Suris. These polynomials are shown to have many properties that are analogous to those of the Yablonskii-Vorob'ev polynomials, to which they reduce when h = 0. They also provide rational solutions for a particular discretization of P II , namely the so-called alternate discrete P II , and this connection leads to an expression in terms of the Umemura polynomials for the third Painleve equation (P III ). It is shown that the Baecklund transformation for the alternate discrete Painleve equation is a symplectic map, and the shift in time is also symplectic. Finally we present a Lax pair for the alternate discrete P II , which recovers Jimbo and Miwa's Lax pair for P II in the continuum limit h → 0
An Augmented Discrete-Time Approach for Human-Robot Collaboration
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Peidong Liang
2016-01-01
Full Text Available Human-robot collaboration (HRC is a key feature to distinguish the new generation of robots from conventional robots. Relevant HRC topics have been extensively investigated recently in academic institutes and companies to improve human and robot interactive performance. Generally, human motor control regulates human motion adaptively to the external environment with safety, compliance, stability, and efficiency. Inspired by this, we propose an augmented approach to make a robot understand human motion behaviors based on human kinematics and human postural impedance adaptation. Human kinematics is identified by geometry kinematics approach to map human arm configuration as well as stiffness index controlled by hand gesture to anthropomorphic arm. While human arm postural stiffness is estimated and calibrated within robot empirical stability region, human motion is captured by employing a geometry vector approach based on Kinect. A biomimetic controller in discrete-time is employed to make Baxter robot arm imitate human arm behaviors based on Baxter robot dynamics. An object moving task is implemented to validate the performance of proposed methods based on Baxter robot simulator. Results show that the proposed approach to HRC is intuitive, stable, efficient, and compliant, which may have various applications in human-robot collaboration scenarios.
Chun, Tae Yoon; Lee, Jae Young; Park, Jin Bae; Choi, Yoon Ho
2018-06-01
In this paper, we propose two multirate generalised policy iteration (GPI) algorithms applied to discrete-time linear quadratic regulation problems. The proposed algorithms are extensions of the existing GPI algorithm that consists of the approximate policy evaluation and policy improvement steps. The two proposed schemes, named heuristic dynamic programming (HDP) and dual HDP (DHP), based on multirate GPI, use multi-step estimation (M-step Bellman equation) at the approximate policy evaluation step for estimating the value function and its gradient called costate, respectively. Then, we show that these two methods with the same update horizon can be considered equivalent in the iteration domain. Furthermore, monotonically increasing and decreasing convergences, so called value iteration (VI)-mode and policy iteration (PI)-mode convergences, are proved to hold for the proposed multirate GPIs. Further, general convergence properties in terms of eigenvalues are also studied. The data-driven online implementation methods for the proposed HDP and DHP are demonstrated and finally, we present the results of numerical simulations performed to verify the effectiveness of the proposed methods.
Value Iteration Adaptive Dynamic Programming for Optimal Control of Discrete-Time Nonlinear Systems.
Wei, Qinglai; Liu, Derong; Lin, Hanquan
2016-03-01
In this paper, a value iteration adaptive dynamic programming (ADP) algorithm is developed to solve infinite horizon undiscounted optimal control problems for discrete-time nonlinear systems. The present value iteration ADP algorithm permits an arbitrary positive semi-definite function to initialize the algorithm. A novel convergence analysis is developed to guarantee that the iterative value function converges to the optimal performance index function. Initialized by different initial functions, it is proven that the iterative value function will be monotonically nonincreasing, monotonically nondecreasing, or nonmonotonic and will converge to the optimum. In this paper, for the first time, the admissibility properties of the iterative control laws are developed for value iteration algorithms. It is emphasized that new termination criteria are established to guarantee the effectiveness of the iterative control laws. Neural networks are used to approximate the iterative value function and compute the iterative control law, respectively, for facilitating the implementation of the iterative ADP algorithm. Finally, two simulation examples are given to illustrate the performance of the present method.
Theory and computation of disturbance invariant sets for discrete-time linear systems
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Kolmanovsky Ilya
1998-01-01
Full Text Available This paper considers the characterization and computation of invariant sets for discrete-time, time-invariant, linear systems with disturbance inputs whose values are confined to a specified compact set but are otherwise unknown. The emphasis is on determining maximal disturbance-invariant sets X that belong to a specified subset Γ of the state space. Such d-invariant sets have important applications in control problems where there are pointwise-in-time state constraints of the form χ ( t ∈ Γ . One purpose of the paper is to unite and extend in a rigorous way disparate results from the prior literature. In addition there are entirely new results. Specific contributions include: exploitation of the Pontryagin set difference to clarify conceptual matters and simplify mathematical developments, special properties of maximal invariant sets and conditions for their finite determination, algorithms for generating concrete representations of maximal invariant sets, practical computational questions, extension of the main results to general Lyapunov stable systems, applications of the computational techniques to the bounding of state and output response. Results on Lyapunov stable systems are applied to the implementation of a logic-based, nonlinear multimode regulator. For plants with disturbance inputs and state-control constraints it enlarges the constraint-admissible domain of attraction. Numerical examples illustrate the various theoretical and computational results.
Computational Procedures for a Class of GI/D/k Systems in Discrete Time
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Md. Mostafizur Rahman
2009-01-01
Full Text Available A class of discrete time GI/D/k systems is considered for which the interarrival times have finite support and customers are served in first-in first-out (FIFO order. The system is formulated as a single server queue with new general independent interarrival times and constant service duration by assuming cyclic assignment of customers to the identical servers. Then the queue length is set up as a quasi-birth-death (QBD type Markov chain. It is shown that this transformed GI/D/1 system has special structures which make the computation of the matrix R simple and efficient, thereby reducing the number of multiplications in each iteration significantly. As a result we were able to keep the computation time very low. Moreover, use of the resulting structural properties makes the computation of the distribution of queue length of the transformed system efficient. The computation of the distribution of waiting time is also shown to be simple by exploiting the special structures.
A new look at the robust control of discrete-time Markov jump linear systems
Todorov, M. G.; Fragoso, M. D.
2016-03-01
In this paper, we make a foray in the role played by a set of four operators on the study of robust H2 and mixed H2/H∞ control problems for discrete-time Markov jump linear systems. These operators appear in the study of mean square stability for this class of systems. By means of new linear matrix inequality (LMI) characterisations of controllers, which include slack variables that, to some extent, separate the robustness and performance objectives, we introduce four alternative approaches to the design of controllers which are robustly stabilising and at the same time provide a guaranteed level of H2 performance. Since each operator provides a different degree of conservatism, the results are unified in the form of an iterative LMI technique for designing robust H2 controllers, whose convergence is attained in a finite number of steps. The method yields a new way of computing mixed H2/H∞ controllers, whose conservatism decreases with iteration. Two numerical examples illustrate the applicability of the proposed results for the control of a small unmanned aerial vehicle, and for an underactuated robotic arm.
Adaptive Dynamic Programming for Discrete-Time Zero-Sum Games.
Wei, Qinglai; Liu, Derong; Lin, Qiao; Song, Ruizhuo
2018-04-01
In this paper, a novel adaptive dynamic programming (ADP) algorithm, called "iterative zero-sum ADP algorithm," is developed to solve infinite-horizon discrete-time two-player zero-sum games of nonlinear systems. The present iterative zero-sum ADP algorithm permits arbitrary positive semidefinite functions to initialize the upper and lower iterations. A novel convergence analysis is developed to guarantee the upper and lower iterative value functions to converge to the upper and lower optimums, respectively. When the saddle-point equilibrium exists, it is emphasized that both the upper and lower iterative value functions are proved to converge to the optimal solution of the zero-sum game, where the existence criteria of the saddle-point equilibrium are not required. If the saddle-point equilibrium does not exist, the upper and lower optimal performance index functions are obtained, respectively, where the upper and lower performance index functions are proved to be not equivalent. Finally, simulation results and comparisons are shown to illustrate the performance of the present method.
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Bingbing Xu
2013-01-01
Full Text Available We consider the leader-following consensus problem of discrete-time multiagent systems on a directed communication topology. Two types of distributed observer-based consensus protocols are considered to solve such a problem. The observers involved in the proposed protocols include full-order observer and reduced-order observer, which are used to reconstruct the state variables. Two algorithms are provided to construct the consensus protocols, which are based on the modified discrete-time algebraic Riccati equation and Sylvester equation. In light of graph and matrix theory, some consensus conditions are established. Finally, a numerical example is provided to illustrate the obtained result.
Jin, Long; Liao, Bolin; Liu, Mei; Xiao, Lin; Guo, Dongsheng; Yan, Xiaogang
2017-01-01
By incorporating the physical constraints in joint space, a different-level simultaneous minimization scheme, which takes both the robot kinematics and robot dynamics into account, is presented and investigated for fault-tolerant motion planning of redundant manipulator in this paper. The scheme is reformulated as a quadratic program (QP) with equality and bound constraints, which is then solved by a discrete-time recurrent neural network. Simulative verifications based on a six-link planar redundant robot manipulator substantiate the efficacy and accuracy of the presented acceleration fault-tolerant scheme, the resultant QP and the corresponding discrete-time recurrent neural network.
A New Approach to Rational Discrete-Time Approximations to Continuous-Time Fractional-Order Systems
Matos , Carlos; Ortigueira , Manuel ,
2012-01-01
Part 10: Signal Processing; International audience; In this paper a new approach to rational discrete-time approximations to continuous fractional-order systems of the form 1/(sα+p) is proposed. We will show that such fractional-order LTI system can be decomposed into sub-systems. One has the classic behavior and the other is similar to a Finite Impulse Response (FIR) system. The conversion from continuous-time to discrete-time systems will be done using the Laplace transform inversion integr...
Forecasting of exported volume for brazilian fruits by time series analysis: an arima/garch approach
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Abdinardo Moreira Barreto de Oliveira
2015-06-01
Full Text Available The aim of this paper was to offer econometric forecasting models to the Brazilian exported volume fruits, with a view to assisting the planning and production control, also motivated by the existence of a few published papers dealing with this issue. In this sense, it was used the ARIMA/GARCH models, considering, likewise, the occurrence of a multiplicative stochastic seasonality in these series. They were collected 300 observations of exported net weight (kg between Jan/1989 and Dec/2013 of the following fruits: pineapple, banana, orange, lemon, apple, papaya, mango, watermelon, melon and grape, which selection criteria was its importance in the exported basket fruit, because they represented 97% of total received dollars, and 99% of total volume sold in 2010, of a population about 28 kinds of exported fruits. The results showed that it was not only observed the existence of a 12 month multiplicative seasonality in banana and mango. On the other hand, they were identified two fruits groups: (1 those which are continuously exported, and (2 those which have export peaks. On the quality of the models, they were considered satisfactory for six of the ten fruits analyzed. On the volatility, it was seen a high persistence in banana and papaya series, pointing to the existence of a structural break in time series, which could be linked to the economic crises happened in the last 17 years.
Suris, Yuri B.
1997-01-01
A fairly complete list of Toda-like integrable lattice systems, both in the continuous and discrete time, is given. For each system the Newtonian, Lagrangian and Hamiltonian formulations are presented, as well as the 2x2 Lax representation and r-matrix structure. The material is given in the "no comment" style, in particular, all proofs are omitted.
Zhou, Ji; Castellanos, Michelle
2013-01-01
Utilizing longitudinal data of 3477 students from 28 institutions, we examine the effects of structural diversity and quality of interracial relation on students' persistence towards graduation within six years. We utilize multilevel discrete-time survival analysis to account for the longitudinal persistence patterns as well as the nested…
Analysis and Design of a High-Order Discrete-Time Passive IIR Low-Pass Filter
Tohidian, M.; Madadi, I.; Staszewski, R.B.
2014-01-01
In this paper, we propose a discrete-time IIR low-pass filter that achieves a high-order of filtering through a charge-sharing rotation. Its sampling rate is then multiplied through pipelining. The first stage of the filter can operate in either a voltage-sampling or charge-sampling mode. It uses
Energy Technology Data Exchange (ETDEWEB)
Shorikov, A. F. [Ural Federal University, 19 S. Mira, Ekaterinburg, 620002, Russia and Institute of Mathematics and Mechanics, Ural Division of Russian Academy of Sciences, 16 S. Kovalevskaya, Ekaterinburg, 620990 (Russian Federation)
2014-11-18
We consider a discrete-time dynamical system consisting of three controllable objects. The motions of all objects are given by the corresponding vector linear or convex discrete-time recurrent vector relations, and control system for its has two levels: basic (first or I level) that is dominating and subordinate level (second or II level) and both have different criterions of functioning and united a priori by determined informational and control connections defined in advance. For the dynamical system in question, we propose a mathematical formalization in the form of solving a multistep problem of two-level hierarchical minimax program control over the terminal approach process with incomplete information and give a general scheme for its solution.
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Yolanda Vidal
2015-05-01
Full Text Available This paper develops a fault diagnosis (FD and fault-tolerant control (FTC of pitch actuators in wind turbines. This is accomplished by combining a disturbance compensator with a controller, both of which are formulated in the discrete time domain. The disturbance compensator has a dual purpose: to estimate the actuator fault (which is used by the FD algorithm and to design the discrete time controller to obtain an FTC. That is, the pitch actuator faults are estimated, and then, the pitch control laws are appropriately modified to achieve an FTC with a comparable behavior to the fault-free case. The performance of the FD and FTC schemes is tested in simulations with the aero-elastic code FAST.
International Nuclear Information System (INIS)
Zhou Tiejun; Liu Yuehua; Li Xiaoping; Liu Yirong
2009-01-01
The discrete-time bidirectional associative memory neural network with periodic coefficients and infinite delays is studied. And not by employing the continuation theorem of coincidence degree theory as other literatures, but by constructing suitable Liapunov function, using fixed point theorem and some analysis techniques, a sufficient criterion is obtained which ensures the existence and global exponential stability of periodic solution for the type of discrete-time BAM neural network. The obtained result is less restrictive to the BAM neural networks than previously known criteria. Furthermore, it can be applied to the BAM neural network which signal transfer functions are neither bounded nor differentiable. In addition, an example and its numerical simulation are given to illustrate the effectiveness of the obtained result
Masuyama, Hiroyuki
2014-01-01
In this paper we study the augmented truncation of discrete-time block-monotone Markov chains under geometric drift conditions. We first present a bound for the total variation distance between the stationary distributions of an original Markov chain and its augmented truncation. We also obtain such error bounds for more general cases, where an original Markov chain itself is not necessarily block monotone but is blockwise dominated by a block-monotone Markov chain. Finally,...
Delay-Dependent Exponential Stability for Discrete-Time BAM Neural Networks with Time-Varying Delays
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Yonggang Chen
2008-01-01
Full Text Available This paper considers the delay-dependent exponential stability for discrete-time BAM neural networks with time-varying delays. By constructing the new Lyapunov functional, the improved delay-dependent exponential stability criterion is derived in terms of linear matrix inequality (LMI. Moreover, in order to reduce the conservativeness, some slack matrices are introduced in this paper. Two numerical examples are presented to show the effectiveness and less conservativeness of the proposed method.
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Albert Corominas
Full Text Available A non-linear discrete-time mathematical program model is proposed to determining the optimal extraction policy for a single primary supplier of a durable non-renewable resource, such as gemstones or some metals. Karush, Kuhn and Tucker conditions allow obtaining analytic solutions and general properties of them in some specific settings. Moreover, provided that the objective function (i.e., the discounted value of the incomes throughout the planning horizon is concave, the model can be easily solved, even using standard commercial solver. However, the analysis of the solutions obtained for different assumptions of the values of the parameters show that the optimal extraction policies and the corresponding prices do not exhibit a general shape. Keywords: Durable non-renewable resources, Single primary supplier, Non-linear programming
Robust Moving Horizon H∞ Control of Discrete Time-Delayed Systems with Interval Time-Varying Delays
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F. Yıldız Tascikaraoglu
2014-01-01
Full Text Available In this study, design of a delay-dependent type moving horizon state-feedback control (MHHC is considered for a class of linear discrete-time system subject to time-varying state delays, norm-bounded uncertainties, and disturbances with bounded energies. The closed-loop robust stability and robust performance problems are considered to overcome the instability and poor disturbance rejection performance due to the existence of parametric uncertainties and time-delay appeared in the system dynamics. Utilizing a discrete-time Lyapunov-Krasovskii functional, some delay-dependent linear matrix inequality (LMI based conditions are provided. It is shown that if one can find a feasible solution set for these LMI conditions iteratively at each step of run-time, then we can construct a control law which guarantees the closed-loop asymptotic stability, maximum disturbance rejection performance, and closed-loop dissipativity in view of the actuator limitations. Two numerical examples with simulations on a nominal and uncertain discrete-time, time-delayed systems, are presented at the end, in order to demonstrate the efficiency of the proposed method.
Forecasting Volatility of USD/MUR Exchange Rate using a GARCH ...
African Journals Online (AJOL)
that both distributions may forecast quite well with a slight advantage to the. GARCH(1 ... Financial time series tend to exhibit certain characteristic features such as volatility ... Heteroscedasticity-adjusted MAE to evaluate the forecasts. Chuanga et .... the Student's-t distribution or the GED with the following probability density.
Masuyama, Hiroyuki
2015-01-01
This paper studies the last-column-block-augmented northwest-corner truncation (LC-block-augmented truncation, for short) of discrete-time block-monotone Markov chains under subgeometric drift conditions. The main result of this paper is to present an upper bound for the total variation distance between the stationary probability vectors of a block-monotone Markov chain and its LC-block-augmented truncation. The main result is extended to Markov chains that themselves may not be block monoton...
Directory of Open Access Journals (Sweden)
O. M. Kwon
2012-01-01
Full Text Available The purpose of this paper is to investigate the delay-dependent stability analysis for discrete-time neural networks with interval time-varying delays. Based on Lyapunov method, improved delay-dependent criteria for the stability of the networks are derived in terms of linear matrix inequalities (LMIs by constructing a suitable Lyapunov-Krasovskii functional and utilizing reciprocally convex approach. Also, a new activation condition which has not been considered in the literature is proposed and utilized for derivation of stability criteria. Two numerical examples are given to illustrate the effectiveness of the proposed method.
Nakamura, Yoshimasa; Sekido, Hiroto
2018-04-01
The finite or the semi-infinite discrete-time Toda lattice has many applications to various areas in applied mathematics. The purpose of this paper is to review how the Toda lattice appears in the Lanczos algorithm through the quotient-difference algorithm and its progressive form (pqd). Then a multistep progressive algorithm (MPA) for solving linear systems is presented. The extended Lanczos parameters can be given not by computing inner products of the extended Lanczos vectors but by using the pqd algorithm with highly relative accuracy in a lower cost. The asymptotic behavior of the pqd algorithm brings us some applications of MPA related to eigenvectors.
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Fei Chen
2013-01-01
Full Text Available This paper deals with the finite-time stabilization problem for discrete-time Markov jump nonlinear systems with time delays and norm-bounded exogenous disturbance. The nonlinearities in different jump modes are parameterized by neural networks. Subsequently, a linear difference inclusion state space representation for a class of neural networks is established. Based on this, sufficient conditions are derived in terms of linear matrix inequalities to guarantee stochastic finite-time boundedness and stochastic finite-time stabilization of the closed-loop system. A numerical example is illustrated to verify the efficiency of the proposed technique.
Leander, Jacob; Lundh, Torbjörn; Jirstrand, Mats
2014-05-01
In this paper we consider the problem of estimating parameters in ordinary differential equations given discrete time experimental data. The impact of going from an ordinary to a stochastic differential equation setting is investigated as a tool to overcome the problem of local minima in the objective function. Using two different models, it is demonstrated that by allowing noise in the underlying model itself, the objective functions to be minimized in the parameter estimation procedures are regularized in the sense that the number of local minima is reduced and better convergence is achieved. The advantage of using stochastic differential equations is that the actual states in the model are predicted from data and this will allow the prediction to stay close to data even when the parameters in the model is incorrect. The extended Kalman filter is used as a state estimator and sensitivity equations are provided to give an accurate calculation of the gradient of the objective function. The method is illustrated using in silico data from the FitzHugh-Nagumo model for excitable media and the Lotka-Volterra predator-prey system. The proposed method performs well on the models considered, and is able to regularize the objective function in both models. This leads to parameter estimation problems with fewer local minima which can be solved by efficient gradient-based methods. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.
Xiao, Mengli; Zhang, Yongbo; Wang, Zhihua; Fu, Huimin
2018-04-01
Considering the performances of conventional Kalman filter may seriously degrade when it suffers stochastic faults and unknown input, which is very common in engineering problems, a new type of adaptive three-stage extended Kalman filter (AThSEKF) is proposed to solve state and fault estimation in nonlinear discrete-time system under these conditions. The three-stage UV transformation and adaptive forgetting factor are introduced for derivation, and by comparing with the adaptive augmented state extended Kalman filter, it is proven to be uniformly asymptotically stable. Furthermore, the adaptive three-stage extended Kalman filter is applied to a two-dimensional radar tracking scenario to illustrate the effect, and the performance is compared with that of conventional three stage extended Kalman filter (ThSEKF) and the adaptive two-stage extended Kalman filter (ATEKF). The results show that the adaptive three-stage extended Kalman filter is more effective than these two filters when facing the nonlinear discrete-time systems with information of unknown inputs not perfectly known. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.
Herzog, W; Schellberg, D; Deter, H C
1997-02-01
The results of a 12-year follow-up study of occurrence and timing of first recovery in 69 hospitalized patients with severe anorexia nervosa (AN) are presented. For the first time discrete-time survival analysis methods were used to determine the likelihood of recovery in AN patients. Furthermore, predictors gleaned from pretreatment-posttreatment studies of long-term outcome in AN could be evaluated as to their effect on a change in the time course structure of the likelihood of first recovery. Results show that AN condition did not improve until after 6 years after the first inpatient treatment in 50% of patients. However, a restricter-type AN and low serum creatinine levels were predictors for earlier recovery. One specific effect was that AN patients who show purging behavior in combination with additional social disturbances have a lower chance of recovering. The use of discrete-time survival analysis methodology in further prospective studies will contribute to the development of more tailored treatment of AN, which also takes the individual phase of illness and specific aspects of the symptomatology into account.
Liu, Yan-Jun; Tong, Shaocheng
2015-03-01
In the paper, an adaptive tracking control design is studied for a class of nonlinear discrete-time systems with dead-zone input. The considered systems are of the nonaffine pure-feedback form and the dead-zone input appears nonlinearly in the systems. The contributions of the paper are that: 1) it is for the first time to investigate the control problem for this class of discrete-time systems with dead-zone; 2) there are major difficulties for stabilizing such systems and in order to overcome the difficulties, the systems are transformed into an n-step-ahead predictor but nonaffine function is still existent; and 3) an adaptive compensative term is constructed to compensate for the parameters of the dead-zone. The neural networks are used to approximate the unknown functions in the transformed systems. Based on the Lyapunov theory, it is proven that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded and the tracking error converges to a small neighborhood of zero. Two simulation examples are provided to verify the effectiveness of the control approach in the paper.
Qi, Donglian; Liu, Meiqin; Qiu, Meikang; Zhang, Senlin
2010-08-01
This brief studies exponential H(infinity) synchronization of a class of general discrete-time chaotic neural networks with external disturbance. On the basis of the drive-response concept and H(infinity) control theory, and using Lyapunov-Krasovskii (or Lyapunov) functional, state feedback controllers are established to not only guarantee exponential stable synchronization between two general chaotic neural networks with or without time delays, but also reduce the effect of external disturbance on the synchronization error to a minimal H(infinity) norm constraint. The proposed controllers can be obtained by solving the convex optimization problems represented by linear matrix inequalities. Most discrete-time chaotic systems with or without time delays, such as Hopfield neural networks, cellular neural networks, bidirectional associative memory networks, recurrent multilayer perceptrons, Cohen-Grossberg neural networks, Chua's circuits, etc., can be transformed into this general chaotic neural network to be H(infinity) synchronization controller designed in a unified way. Finally, some illustrated examples with their simulations have been utilized to demonstrate the effectiveness of the proposed methods.
GOOD NEWS, BAD NEWS AND GARCH EFFECTS IN STOCK RETURN DATA
Craig A. Depken II
2001-01-01
It is shown that the volume of trade can be decomposed into proportional proxies for stochastic flows of good news and bad news into the market. Positive (good) information flows are assumed to increase the price of a financial vehicle while negative (bad) information flows decrease the price. For the majority of a sample of ten split-stocks it is shown that the proposed decomposition explains more GARCH than volume itself. Using the proposed decomposition, the variance of returns for younger...
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Vasile Dr ̆agan
2017-06-01
Full Text Available We investigate the problem for solving a discrete-time periodic gen- eralized Riccati equation with an indefinite sign of the quadratic term. A necessary condition for the existence of bounded and stabilizing solution of the discrete-time Riccati equation with an indefinite quadratic term is derived. The stabilizing solution is positive semidefinite and satisfies the introduced sign conditions. The proposed condition is illustrated via a numerical example.
Trivial dynamics in discrete-time systems: carrying simplex and translation arcs
Niu, Lei; Ruiz-Herrera, Alfonso
2018-06-01
In this paper we show that the dynamical behavior in (first octant) of the classical Kolmogorov systems of competitive type admitting a carrying simplex can be sometimes determined completely by the number of fixed points on the boundary and the local behavior around them. Roughly speaking, T has trivial dynamics (i.e. the omega limit set of any orbit is a connected set contained in the set of fixed points) provided T has exactly four hyperbolic nontrivial fixed points in with local attractors on the carrying simplex and local repellers on the carrying simplex; and there exists a unique hyperbolic fixed point in Int. Our results are applied to some classical models including the Leslie–Gower models, Atkinson-Allen systems and Ricker maps.
Nonlinear discrete-time multirate adaptive control of non-linear vibrations of smart beams
Georgiou, Georgios; Foutsitzi, Georgia A.; Stavroulakis, Georgios E.
2018-06-01
The nonlinear adaptive digital control of a smart piezoelectric beam is considered. It is shown that in the case of a sampled-data context, a multirate control strategy provides an appropriate framework in order to achieve vibration regulation, ensuring the stability of the whole control system. Under parametric uncertainties in the model parameters (damping ratios, frequencies, levels of non linearities and cross coupling, control input parameters), the scheme is completed with an adaptation law deduced from hyperstability concepts. This results in the asymptotic satisfaction of the control objectives at the sampling instants. Simulation results are presented.
Adaptive Control of Nonlinear Discrete-Time Systems by Using OS-ELM Neural Networks
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Xiao-Li Li
2014-01-01
Full Text Available As a kind of novel feedforward neural network with single hidden layer, ELM (extreme learning machine neural networks are studied for the identification and control of nonlinear dynamic systems. The property of simple structure and fast convergence of ELM can be shown clearly. In this paper, we are interested in adaptive control of nonlinear dynamic plants by using OS-ELM (online sequential extreme learning machine neural networks. Based on data scope division, the problem that training process of ELM neural network is sensitive to the initial training data is also solved. According to the output range of the controlled plant, the data corresponding to this range will be used to initialize ELM. Furthermore, due to the drawback of conventional adaptive control, when the OS-ELM neural network is used for adaptive control of the system with jumping parameters, the topological structure of the neural network can be adjusted dynamically by using multiple model switching strategy, and an MMAC (multiple model adaptive control will be used to improve the control performance. Simulation results are included to complement the theoretical results.
International Nuclear Information System (INIS)
Franzè, Giuseppe; Lucia, Walter; Tedesco, Francesco
2014-01-01
This paper proposes a Model Predictive Control (MPC) strategy to address regulation problems for constrained polytopic Linear Parameter Varying (LPV) systems subject to input and state constraints in which both plant measurements and command signals in the loop are sent through communication channels subject to time-varying delays (Networked Control System (NCS)). The results here proposed represent a significant extension to the LPV framework of a recent Receding Horizon Control (RHC) scheme developed for the so-called robust case. By exploiting the parameter availability, the pre-computed sequences of one- step controllable sets inner approximations are less conservative than the robust counterpart. The resulting framework guarantees asymptotic stability and constraints fulfilment regardless of plant uncertainties and time-delay occurrences. Finally, experimental results on a laboratory two-tank test-bed show the effectiveness of the proposed approach
Stability analysis and synchronization in discrete-time complex networks with delayed coupling
Cheng, Ranran; Peng, Mingshu; Yu, Weibin; Sun, Bo; Yu, Jinchen
2013-12-01
A new network of coupled maps is proposed in which the connections between units involve no delays but the intra-neural communication does, whereas in the work of Atay et al. [Phys. Rev. Lett. 92, 144101 (2004)], the focus is on information processing delayed by the inter-neural communication. We show that the synchronization of the network depends on not only the intrinsic dynamical features and inter-connection topology (characterized by the spectrum of the graph Laplacian) but also the delays and the coupling strength. There are two main findings: (i) the more neighbours, the easier to be synchronized; (ii) odd delays are easier to be synchronized than even ones. In addition, compared with those discussed by Atay et al. [Phys. Rev. Lett. 92, 144101 (2004)], our model has a better synchronizability for regular networks and small-world variants.
On the Two-Moment Approximation of the Discrete-Time GI/G/1 Queue with a Single Vacation
Directory of Open Access Journals (Sweden)
Doo Ho Lee
2016-01-01
Full Text Available We consider a discrete-time GI/G/1 queue in which the server takes exactly one vacation each time the system becomes empty. The interarrival times of arriving customers, the service times, and the vacation times are all generic discrete random variables. Under our study, we derive an exact transform-free expression for the stationary system size distribution through the modified supplementary variable technique. Utilizing obtained results, we introduce a simple two-moment approximation for the system size distribution. From this, approximations for the mean system size along with the system size distribution could be obtained. Finally, some numerical examples are given to validate the proposed approximation method.
International Nuclear Information System (INIS)
Kaslik, E.; Balint, St.
2009-01-01
In this paper, a bifurcation analysis is undertaken for a discrete-time Hopfield neural network of two neurons with two different delays and self-connections. Conditions ensuring the asymptotic stability of the null solution are found, with respect to two characteristic parameters of the system. It is shown that for certain values of these parameters, Fold or Neimark-Sacker bifurcations occur, but Flip and codimension 2 (Fold-Neimark-Sacker, double Neimark-Sacker, resonance 1:1 and Flip-Neimark-Sacker) bifurcations may also be present. The direction and the stability of the Neimark-Sacker bifurcations are investigated by applying the center manifold theorem and the normal form theory
International Nuclear Information System (INIS)
Goharrizi, Amin Yazdanpanah; Khaki-Sedigh, Ali; Sepehri, Nariman
2009-01-01
A new approach to adaptive control of chaos in a class of nonlinear discrete-time-varying systems, using a delayed state feedback scheme, is presented. It is discussed that such systems can show chaotic behavior as their parameters change. A strategy is employed for on-line calculation of the Lyapunov exponents that will be used within an adaptive scheme that decides on the control effort to suppress the chaotic behavior once detected. The scheme is further augmented with a nonlinear observer for estimation of the states that are required by the controller but are hard to measure. Simulation results for chaotic control problem of Jin map are provided to show the effectiveness of the proposed scheme.
Mehraeen, Shahab; Dierks, Travis; Jagannathan, S; Crow, Mariesa L
2013-12-01
In this paper, the nearly optimal solution for discrete-time (DT) affine nonlinear control systems in the presence of partially unknown internal system dynamics and disturbances is considered. The approach is based on successive approximate solution of the Hamilton-Jacobi-Isaacs (HJI) equation, which appears in optimal control. Successive approximation approach for updating control and disturbance inputs for DT nonlinear affine systems are proposed. Moreover, sufficient conditions for the convergence of the approximate HJI solution to the saddle point are derived, and an iterative approach to approximate the HJI equation using a neural network (NN) is presented. Then, the requirement of full knowledge of the internal dynamics of the nonlinear DT system is relaxed by using a second NN online approximator. The result is a closed-loop optimal NN controller via offline learning. A numerical example is provided illustrating the effectiveness of the approach.
Xie, Xiangpeng; Yue, Dong; Zhang, Huaguang; Xue, Yusheng
2016-03-01
This paper deals with the problem of control synthesis of discrete-time Takagi-Sugeno fuzzy systems by employing a novel multiinstant homogenous polynomial approach. A new multiinstant fuzzy control scheme and a new class of fuzzy Lyapunov functions, which are homogenous polynomially parameter-dependent on both the current-time normalized fuzzy weighting functions and the past-time normalized fuzzy weighting functions, are proposed for implementing the object of relaxed control synthesis. Then, relaxed stabilization conditions are derived with less conservatism than existing ones. Furthermore, the relaxation quality of obtained stabilization conditions is further ameliorated by developing an efficient slack variable approach, which presents a multipolynomial dependence on the normalized fuzzy weighting functions at the current and past instants of time. Two simulation examples are given to demonstrate the effectiveness and benefits of the results developed in this paper.
International Nuclear Information System (INIS)
Shah, S.A.; Shah, W.; Shaikh, F.K.
2012-01-01
Flow time analysis is a powerful concept to analyze the flow time of any arriving customer in any system at any instant. A load management mechanism can be employed very effectively in any queueing system by utilizing a system which provides probability of dual service rate. In this paper, we develop and demonstrate the flow and service processes transition diagram to determine the flow time of a customer in a load management late arrival state dependent finite discrete time queueing system with dual service rate where customers are hypo geometrically distributed. We compute the probability mass function of each starting state and total probability mass function. The obtained analytical results are validated with simulation results for varying values of arrival and service probabilities. (author)
Directory of Open Access Journals (Sweden)
Huiying Sun
2014-01-01
Full Text Available We mainly consider the stability of discrete-time Markovian jump linear systems with state-dependent noise as well as its linear quadratic (LQ differential games. A necessary and sufficient condition involved with the connection between stochastic Tn-stability of Markovian jump linear systems with state-dependent noise and Lyapunov equation is proposed. And using the theory of stochastic Tn-stability, we give the optimal strategies and the optimal cost values for infinite horizon LQ stochastic differential games. It is demonstrated that the solutions of infinite horizon LQ stochastic differential games are concerned with four coupled generalized algebraic Riccati equations (GAREs. Finally, an iterative algorithm is presented to solve the four coupled GAREs and a simulation example is given to illustrate the effectiveness of it.
Zhang, Huaguang; Jiang, He; Luo, Chaomin; Xiao, Geyang
2017-10-01
In this paper, we investigate the nonzero-sum games for a class of discrete-time (DT) nonlinear systems by using a novel policy iteration (PI) adaptive dynamic programming (ADP) method. The main idea of our proposed PI scheme is to utilize the iterative ADP algorithm to obtain the iterative control policies, which not only ensure the system to achieve stability but also minimize the performance index function for each player. This paper integrates game theory, optimal control theory, and reinforcement learning technique to formulate and handle the DT nonzero-sum games for multiplayer. First, we design three actor-critic algorithms, an offline one and two online ones, for the PI scheme. Subsequently, neural networks are employed to implement these algorithms and the corresponding stability analysis is also provided via the Lyapunov theory. Finally, a numerical simulation example is presented to demonstrate the effectiveness of our proposed approach.
Directory of Open Access Journals (Sweden)
Pablo Soto-Quiros
2015-01-01
Full Text Available This paper presents a parallel implementation of a kind of discrete Fourier transform (DFT: the vector-valued DFT. The vector-valued DFT is a novel tool to analyze the spectra of vector-valued discrete-time signals. This parallel implementation is developed in terms of a mathematical framework with a set of block matrix operations. These block matrix operations contribute to analysis, design, and implementation of parallel algorithms in multicore processors. In this work, an implementation and experimental investigation of the mathematical framework are performed using MATLAB with the Parallel Computing Toolbox. We found that there is advantage to use multicore processors and a parallel computing environment to minimize the high execution time. Additionally, speedup increases when the number of logical processors and length of the signal increase.
Cluster consensus in discrete-time networks of multiagents with inter-cluster nonidentical inputs.
Han, Yujuan; Lu, Wenlian; Chen, Tianping
2013-04-01
In this paper, cluster consensus of multiagent systems is studied via inter-cluster nonidentical inputs. Here, we consider general graph topologies, which might be time-varying. The cluster consensus is defined by two aspects: intracluster synchronization, the state at which differences between each pair of agents in the same cluster converge to zero, and inter-cluster separation, the state at which agents in different clusters are separated. For intra-cluster synchronization, the concepts and theories of consensus, including the spanning trees, scramblingness, infinite stochastic matrix product, and Hajnal inequality, are extended. As a result, it is proved that if the graph has cluster spanning trees and all vertices self-linked, then the static linear system can realize intra-cluster synchronization. For the time-varying coupling cases, it is proved that if there exists T > 0 such that the union graph across any T-length time interval has cluster spanning trees and all graphs has all vertices self-linked, then the time-varying linear system can also realize intra-cluster synchronization. Under the assumption of common inter-cluster influence, a sort of inter-cluster nonidentical inputs are utilized to realize inter-cluster separation, such that each agent in the same cluster receives the same inputs and agents in different clusters have different inputs. In addition, the boundedness of the infinite sum of the inputs can guarantee the boundedness of the trajectory. As an application, we employ a modified non-Bayesian social learning model to illustrate the effectiveness of our results.
Yan, Huaicheng; Zhang, Hao; Yang, Fuwen; Zhan, Xisheng; Peng, Chen
2017-08-18
This paper is concerned with the guaranteed cost control problem for a class of Markov jump discrete-time neural networks (NNs) with event-triggered mechanism, asynchronous jumping, and fading channels. The Markov jump NNs are introduced to be close to reality, where the modes of the NNs and guaranteed cost controller are determined by two mutually independent Markov chains. The asynchronous phenomenon is considered, which increases the difficulty of designing required mode-dependent controller. The event-triggered mechanism is designed by comparing the relative measurement error with the last triggered state at the process of data transmission, which is used to eliminate dispensable transmission and reduce the networked energy consumption. In addition, the signal fading is considered for the effect of signal reflection and shadow in wireless networks, which is modeled by the novel Rice fading models. Some novel sufficient conditions are obtained to guarantee that the closed-loop system reaches a specified cost value under the designed jumping state feedback control law in terms of linear matrix inequalities. Finally, some simulation results are provided to illustrate the effectiveness of the proposed method.
Feng, Zhixin; Jones, Kelvyn; Wang, Wenfei Winnie
2015-01-01
This study undertakes a survival analysis of elderly persons in China using Chinese Longitudinal Healthy Longevity Survey 2002–2008. Employing discrete-time multilevel models, we explored the effect of social support on the survival of elderly people in China. This study focuses on objective (living arrangements and received support) and subjective activities (perceived support) of social support, finding that the effect of different activities of social support on the survival of elderly people varies according to the availability of different support resources. Specifically, living with a spouse, financial independence, perceiving care support from any resource is associated with higher survival rates for elderly people. Separate analysis focusing on urban elderly and rural elderly revealed broadly similar results. There is a larger difference between those perceiving care support from family or social service and not perceiving care support in urban areas comparing to those in rural areas. Those who cannot pay medical expenses are the least likely to survive. The higher level of economic development in province has no significant effect on the survival of elderly people for the whole sample model and the elderly people in urban areas; however, there is a negative influence on the survival of the rural elderly people. PMID:25703671
Indian Academy of Sciences (India)
A Ramakalyan1 P Kavitha2 S Harini Vijayalakshmi3. Department of Instrumentation and Control Engineering, Regional Engineering College, Tiruchirapalli 620 015, India. Hindustan Computers Ltd. at Chennai. Texas A & M University. Resonance – Journal of Science Education. Current Issue : Vol. 23, Issue 4.
Xie, Xiangpeng; Yue, Dong; Zhang, Huaguang; Peng, Chen
2017-09-01
The augmented multi-indexed matrix approach acts as a powerful tool in reducing the conservatism of control synthesis of discrete-time Takagi-Sugeno fuzzy systems. However, its computational burden is sometimes too heavy as a tradeoff. Nowadays, reducing the conservatism whilst alleviating the computational burden becomes an ideal but very challenging problem. This paper is toward finding an efficient way to achieve one of satisfactory answers. Different from the augmented multi-indexed matrix approach in the literature, we aim to design a more efficient slack variable approach under a general framework of homogenous matrix polynomials. Thanks to the introduction of a new extended representation for homogeneous matrix polynomials, related matrices with the same coefficient are collected together into one sole set and thus those redundant terms of the augmented multi-indexed matrix approach can be removed, i.e., the computational burden can be alleviated in this paper. More importantly, due to the fact that more useful information is involved into control design, the conservatism of the proposed approach as well is less than the counterpart of the augmented multi-indexed matrix approach. Finally, numerical experiments are given to show the effectiveness of the proposed approach.
Jiang, Guangli; Liu, Leibo; Zhu, Wenping; Yin, Shouyi; Wei, Shaojun
2015-09-04
This paper proposes a real-time feature extraction VLSI architecture for high-resolution images based on the accelerated KAZE algorithm. Firstly, a new system architecture is proposed. It increases the system throughput, provides flexibility in image resolution, and offers trade-offs between speed and scaling robustness. The architecture consists of a two-dimensional pipeline array that fully utilizes computational similarities in octaves. Secondly, a substructure (block-serial discrete-time cellular neural network) that can realize a nonlinear filter is proposed. This structure decreases the memory demand through the removal of data dependency. Thirdly, a hardware-friendly descriptor is introduced in order to overcome the hardware design bottleneck through the polar sample pattern; a simplified method to realize rotation invariance is also presented. Finally, the proposed architecture is designed in TSMC 65 nm CMOS technology. The experimental results show a performance of 127 fps in full HD resolution at 200 MHz frequency. The peak performance reaches 181 GOPS and the throughput is double the speed of other state-of-the-art architectures.
Directory of Open Access Journals (Sweden)
Guangli Jiang
2015-09-01
Full Text Available This paper proposes a real-time feature extraction VLSI architecture for high-resolution images based on the accelerated KAZE algorithm. Firstly, a new system architecture is proposed. It increases the system throughput, provides flexibility in image resolution, and offers trade-offs between speed and scaling robustness. The architecture consists of a two-dimensional pipeline array that fully utilizes computational similarities in octaves. Secondly, a substructure (block-serial discrete-time cellular neural network that can realize a nonlinear filter is proposed. This structure decreases the memory demand through the removal of data dependency. Thirdly, a hardware-friendly descriptor is introduced in order to overcome the hardware design bottleneck through the polar sample pattern; a simplified method to realize rotation invariance is also presented. Finally, the proposed architecture is designed in TSMC 65 nm CMOS technology. The experimental results show a performance of 127 fps in full HD resolution at 200 MHz frequency. The peak performance reaches 181 GOPS and the throughput is double the speed of other state-of-the-art architectures.
Liu, Yan-Jun; Gao, Ying; Tong, Shaocheng; Chen, C L Philip
2016-01-01
In this paper, an effective adaptive control approach is constructed to stabilize a class of nonlinear discrete-time systems, which contain unknown functions, unknown dead-zone input, and unknown control direction. Different from linear dead zone, the dead zone, in this paper, is a kind of nonlinear dead zone. To overcome the noncausal problem, which leads to the control scheme infeasible, the systems can be transformed into a m -step-ahead predictor. Due to nonlinear dead-zone appearance, the transformed predictor still contains the nonaffine function. In addition, it is assumed that the gain function of dead-zone input and the control direction are unknown. These conditions bring about the difficulties and the complicacy in the controller design. Thus, the implicit function theorem is applied to deal with nonaffine dead-zone appearance, the problem caused by the unknown control direction can be resolved through applying the discrete Nussbaum gain, and the neural networks are used to approximate the unknown function. Based on the Lyapunov theory, all the signals of the resulting closed-loop system are proved to be semiglobal uniformly ultimately bounded. Moreover, the tracking error is proved to be regulated to a small neighborhood around zero. The feasibility of the proposed approach is demonstrated by a simulation example.
Directory of Open Access Journals (Sweden)
Peidong Liang
2016-01-01
Full Text Available We have developed a new discrete-time algorithm of stiffness extraction from muscle surface electromyography (sEMG collected from human operator’s arms and have applied it for antidisturbance control in robot teleoperation. The variation of arm stiffness is estimated from sEMG signals and transferred to a telerobot under variable impedance control to imitate human motor control behaviours, particularly for disturbance attenuation. In comparison to the estimation of stiffness from sEMG, the proposed algorithm is able to reduce the nonlinear residual error effect and to enhance robustness and to simplify stiffness calibration. In order to extract a smoothing stiffness enveloping from sEMG signals, two enveloping methods are employed in this paper, namely, fast linear enveloping based on low pass filtering and moving average and amplitude monocomponent and frequency modulating (AM-FM method. Both methods have been incorporated into the proposed stiffness variance estimation algorithm and are extensively tested. The test results show that stiffness variation extraction based on the two methods is sensitive and robust to attenuation disturbance. It could potentially be applied for teleoperation in the presence of hazardous surroundings or human robot physical cooperation scenarios.
Tognetti, Eduardo S.; Oliveira, Ricardo C. L. F.; Peres, Pedro L. D.
2015-01-01
The problem of state feedback control design for discrete-time Takagi-Sugeno (TS) (T-S) fuzzy systems is investigated in this paper. A Lyapunov function, which is quadratic in the state and presents a multi-polynomial dependence on the fuzzy weighting functions at the current and past instants of time, is proposed.This function contains, as particular cases, other previous Lyapunov functions already used in the literature, being able to provide less conservative conditions of control design for TS fuzzy systems. The structure of the proposed Lyapunov function also motivates the design of a new stabilising compensator for Takagi-Sugeno fuzzy systems. The main novelty of the proposed state feedback control law is that the gain is composed of matrices with multi-polynomial dependence on the fuzzy weighting functions at a set of past instants of time, including the current one. The conditions for the existence of a stabilising state feedback control law that minimises an upper bound to the ? or ? norms are given in terms of linear matrix inequalities. Numerical examples show that the approach can be less conservative and more efficient than other methods available in the literature.
Luo, Biao; Liu, Derong; Wu, Huai-Ning
2018-06-01
Reinforcement learning has proved to be a powerful tool to solve optimal control problems over the past few years. However, the data-based constrained optimal control problem of nonaffine nonlinear discrete-time systems has rarely been studied yet. To solve this problem, an adaptive optimal control approach is developed by using the value iteration-based Q-learning (VIQL) with the critic-only structure. Most of the existing constrained control methods require the use of a certain performance index and only suit for linear or affine nonlinear systems, which is unreasonable in practice. To overcome this problem, the system transformation is first introduced with the general performance index. Then, the constrained optimal control problem is converted to an unconstrained optimal control problem. By introducing the action-state value function, i.e., Q-function, the VIQL algorithm is proposed to learn the optimal Q-function of the data-based unconstrained optimal control problem. The convergence results of the VIQL algorithm are established with an easy-to-realize initial condition . To implement the VIQL algorithm, the critic-only structure is developed, where only one neural network is required to approximate the Q-function. The converged Q-function obtained from the critic-only VIQL method is employed to design the adaptive constrained optimal controller based on the gradient descent scheme. Finally, the effectiveness of the developed adaptive control method is tested on three examples with computer simulation.
Sivak, David A; Chodera, John D; Crooks, Gavin E
2014-06-19
When simulating molecular systems using deterministic equations of motion (e.g., Newtonian dynamics), such equations are generally numerically integrated according to a well-developed set of algorithms that share commonly agreed-upon desirable properties. However, for stochastic equations of motion (e.g., Langevin dynamics), there is still broad disagreement over which integration algorithms are most appropriate. While multiple desiderata have been proposed throughout the literature, consensus on which criteria are important is absent, and no published integration scheme satisfies all desiderata simultaneously. Additional nontrivial complications stem from simulating systems driven out of equilibrium using existing stochastic integration schemes in conjunction with recently developed nonequilibrium fluctuation theorems. Here, we examine a family of discrete time integration schemes for Langevin dynamics, assessing how each member satisfies a variety of desiderata that have been enumerated in prior efforts to construct suitable Langevin integrators. We show that the incorporation of a novel time step rescaling in the deterministic updates of position and velocity can correct a number of dynamical defects in these integrators. Finally, we identify a particular splitting (related to the velocity Verlet discretization) that has essentially universally appropriate properties for the simulation of Langevin dynamics for molecular systems in equilibrium, nonequilibrium, and path sampling contexts.
Liu, Yan-Jun; Tang, Li; Tong, Shaocheng; Chen, C L Philip; Li, Dong-Juan
2015-01-01
Based on the neural network (NN) approximator, an online reinforcement learning algorithm is proposed for a class of affine multiple input and multiple output (MIMO) nonlinear discrete-time systems with unknown functions and disturbances. In the design procedure, two networks are provided where one is an action network to generate an optimal control signal and the other is a critic network to approximate the cost function. An optimal control signal and adaptation laws can be generated based on two NNs. In the previous approaches, the weights of critic and action networks are updated based on the gradient descent rule and the estimations of optimal weight vectors are directly adjusted in the design. Consequently, compared with the existing results, the main contributions of this paper are: 1) only two parameters are needed to be adjusted, and thus the number of the adaptation laws is smaller than the previous results and 2) the updating parameters do not depend on the number of the subsystems for MIMO systems and the tuning rules are replaced by adjusting the norms on optimal weight vectors in both action and critic networks. It is proven that the tracking errors, the adaptation laws, and the control inputs are uniformly bounded using Lyapunov analysis method. The simulation examples are employed to illustrate the effectiveness of the proposed algorithm.
Yang, Xiong; Liu, Derong; Wang, Ding; Wei, Qinglai
2014-07-01
In this paper, a reinforcement-learning-based direct adaptive control is developed to deliver a desired tracking performance for a class of discrete-time (DT) nonlinear systems with unknown bounded disturbances. We investigate multi-input-multi-output unknown nonaffine nonlinear DT systems and employ two neural networks (NNs). By using Implicit Function Theorem, an action NN is used to generate the control signal and it is also designed to cancel the nonlinearity of unknown DT systems, for purpose of utilizing feedback linearization methods. On the other hand, a critic NN is applied to estimate the cost function, which satisfies the recursive equations derived from heuristic dynamic programming. The weights of both the action NN and the critic NN are directly updated online instead of offline training. By utilizing Lyapunov's direct method, the closed-loop tracking errors and the NN estimated weights are demonstrated to be uniformly ultimately bounded. Two numerical examples are provided to show the effectiveness of the present approach. Copyright © 2014 Elsevier Ltd. All rights reserved.
Recent developments in volatility modeling and applications
Directory of Open Access Journals (Sweden)
A. Thavaneswaran
2006-01-01
Full Text Available In financial modeling, it has been constantly pointed out that volatility clustering and conditional nonnormality induced leptokurtosis observed in high frequency data. Financial time series data are not adequately modeled by normal distribution, and empirical evidence on the non-normality assumption is well documented in the financial literature (details are illustrated by Engle (1982 and Bollerslev (1986. An ARMA representation has been used by Thavaneswaran et al., in 2005, to derive the kurtosis of the various class of GARCH models such as power GARCH, non-Gaussian GARCH, nonstationary and random coefficient GARCH. Several empirical studies have shown that mixture distributions are more likely to capture heteroskedasticity observed in high frequency data than normal distribution. In this paper, some results on moment properties are generalized to stationary ARMA process with GARCH errors. Application to volatility forecasts and option pricing are also discussed in some detail.
Kepper, Annelies; Koning, Ina; Vollebergh, Wilma; Monshouwer, Karin
2014-01-01
This study investigated the age of onset of substance use among 536 students with mild academic disabilities and 906 students without academic disabilities, and the extent to which emotional, conduct, and hyperactivity problems explain the differences between these two groups. Using discrete-time
Noise behavior of the Garching 30-meter prototype gravitational-wave detector
International Nuclear Information System (INIS)
Shoemaker, D.; Schilling, R.; Schnupp, L.; Winkler, W.; Maischberger, K.; Ruediger, A.
1988-01-01
The prototype gravitational-wave detector at Garching is described: in a laser-illuminated Michelson interferometer having arms 30 m in length, a folded optical path of 3 km is realized. The origin, action, and magnitude of possible noise sources are given. The agreement between the expected and measured noise is good. For a band of astrophysical interest, extending from 1 to 6 kHz, the quantum shot noise corresponding to a light power of P = 0.23 W is dominant. In terms of the dimensionless strain h the best sensitivity in a 1-kHz bandwidth is h = 3 x 10/sup -18/, comparable to the most sensitive Weber-bar-type antennas
NASA and ESA astronauts visit ESO. Hubble repair team meets European astronomers in Garching.
1994-02-01
On Wednesday, February 16, 1994, seven NASA and ESA astronauts and their spouses will spend a day at the Headquarters of the European Southern Observatory. They are the members of the STS-61 crew that successfully repaired the Hubble Space Telescope during a Space Shuttle mission in December 1993. This will be the only stop in Germany during their current tour of various European countries. ESO houses the Space Telescope European Coordinating Facility (ST/ECF), a joint venture by the European Space Agency and ESO. This group of astronomers and computer specialists provide all services needed by European astronomers for observations with the Space Telescope. Currently, the European share is about 20 of the total time available at this telescope. During this visit, a Press Conference will be held on Wednesday, February 16, 11:45 - 12:30 at the ESO Headquarters Karl-Schwarzschild-Strasse 2 D-85748 Garching bei Munchen. Please note that participation in this Press Conference is by invitation only. Media representatives may obtain invitations from Mrs. E. Volk, ESO Information Service at this address (Tel.: +49-89-32006276; Fax.: +49-89-3202362), until Friday, February 11, 1994. After the Press Conference, between 12:30 - 14:00, a light refreshment will be served at the ESO Headquarters to all participants. >From 14:00 - 15:30, the astronauts will meet with students and teachers from the many scientific institutes in Garching in the course of an open presentation at the large lecture hall of the Physics Department of the Technical University. It is a 10 minute walk from ESO to the hall. Later the same day, the astronauts will be back at ESO for a private discussion of various space astronomy issues with their astronomer colleagues, many of whom are users of the Hubble Space Telescope, as well as ground-based telescopes at the ESO La Silla Observatory and elsewhere. The astronauts continue to Switzerland in the evening.
Directory of Open Access Journals (Sweden)
2006-01-01
Full Text Available RF circuits for multi-GHz frequencies have recently migrated to low-cost digital deep-submicron CMOS processes. Unfortunately, this process environment, which is optimized only for digital logic and SRAM memory, is extremely unfriendly for conventional analog and RF designs. We present fundamental techniques recently developed that transform the RF and analog circuit design complexity to digitally intensive domain for a wireless RF transceiver, so that it enjoys benefits of digital and switched-capacitor approaches. Direct RF sampling techniques allow great flexibility in reconfigurable radio design. Digital signal processing concepts are used to help relieve analog design complexity, allowing one to reduce cost and power consumption in a reconfigurable design environment. The ideas presented have been used in Texas Instruments to develop two generations of commercial digital RF processors: a single-chip Bluetooth radio and a single-chip GSM radio. We further present details of the RF receiver front end for a GSM radio realized in a 90-nm digital CMOS technology. The circuit consisting of low-noise amplifier, transconductance amplifier, and switching mixer offers 32.5 dB dynamic range with digitally configurable voltage gain of 40 dB down to 7.5 dB. A series of decimation and discrete-time filtering follows the mixer and performs a highly linear second-order lowpass filtering to reject close-in interferers. The front-end gains can be configured with an automatic gain control to select an optimal setting to form a trade-off between noise figure and linearity and to compensate the process and temperature variations. Even under the digital switching activity, noise figure at the 40 dB maximum gain is 1.8 dB and +50 dBm IIP2 at the 34 dB gain. The variation of the input matching versus multiple gains is less than 1 dB. The circuit in total occupies 3.1 mm 2 . The LNA, TA, and mixer consume less than 15.3 mA at a supply voltage of 1.4 V.
Directory of Open Access Journals (Sweden)
Ho Yo-Chuol
2006-01-01
Full Text Available RF circuits for multi-GHz frequencies have recently migrated to low-cost digital deep-submicron CMOS processes. Unfortunately, this process environment, which is optimized only for digital logic and SRAM memory, is extremely unfriendly for conventional analog and RF designs. We present fundamental techniques recently developed that transform the RF and analog circuit design complexity to digitally intensive domain for a wireless RF transceiver, so that it enjoys benefits of digital and switched-capacitor approaches. Direct RF sampling techniques allow great flexibility in reconfigurable radio design. Digital signal processing concepts are used to help relieve analog design complexity, allowing one to reduce cost and power consumption in a reconfigurable design environment. The ideas presented have been used in Texas Instruments to develop two generations of commercial digital RF processors: a single-chip Bluetooth radio and a single-chip GSM radio. We further present details of the RF receiver front end for a GSM radio realized in a 90-nm digital CMOS technology. The circuit consisting of low-noise amplifier, transconductance amplifier, and switching mixer offers dB dynamic range with digitally configurable voltage gain of 40 dB down to dB. A series of decimation and discrete-time filtering follows the mixer and performs a highly linear second-order lowpass filtering to reject close-in interferers. The front-end gains can be configured with an automatic gain control to select an optimal setting to form a trade-off between noise figure and linearity and to compensate the process and temperature variations. Even under the digital switching activity, noise figure at the 40 dB maximum gain is 1.8 dB and dBm IIP2 at the 34 dB gain. The variation of the input matching versus multiple gains is less than 1 dB. The circuit in total occupies 3.1 . The LNA, TA, and mixer consume less than mA at a supply voltage of 1.4 V.
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Marcos Rocha
2011-08-01
, in a inflation targeting regime context, should be made by controlling the effects of the effective exchange rate regime; the analysis to be made is, therefore, one of the conditional volatility. This paper analyzes the conditional volatility by estimating a model of exponential PANEL-GARCH for 20 countries that officially adopted the inflation targeting. The different exchange regimes are added in the explanation of the volatility as control variables, following the acute classification of exchange regimes proposed by Reinhart and Rogoff (2002. The results that arise in this work are contrary to many already crystallized ideas in the literature. In the case of the emerging countries, differently of the result for developed countries, it was found that the IT adoption, ceteris paribus, reduces the conditional volatility of the real exchange rate. In spite of this at first seemingly disconcerting result, it follows a logic explained in the paper, which suggests credibility problems as an answer for the singular behavior of the exchange rate volatility of these countries. In this context, it is outlined the link among stability, fear of floating, and other emerging countries specificities, like the dimension of the exchange rate pass-trough on the prices.
DEFF Research Database (Denmark)
Silvennoinen, Annastiina; Terasvirta, Timo
The topic of this paper is testing the hypothesis of constant unconditional variance in GARCH models against the alternative that the unconditional variance changes deterministically over time. Tests of this hypothesis have previously been performed as misspecification tests after fitting a GARCH...... models. An application to exchange rate returns is included....
International Nuclear Information System (INIS)
Minesaki, Yukitaka
2013-01-01
For the restricted three-body problem, we propose an accurate orbital integration scheme that retains all conserved quantities of the two-body problem with two primaries and approximately preserves the Jacobi integral. The scheme is obtained by taking the limit as mass approaches zero in the discrete-time general three-body problem. For a long time interval, the proposed scheme precisely reproduces various periodic orbits that cannot be accurately computed by other generic integrators
Liao, Bolin; Zhang, Yunong; Jin, Long
2016-02-01
In this paper, a new Taylor-type numerical differentiation formula is first presented to discretize the continuous-time Zhang neural network (ZNN), and obtain higher computational accuracy. Based on the Taylor-type formula, two Taylor-type discrete-time ZNN models (termed Taylor-type discrete-time ZNNK and Taylor-type discrete-time ZNNU models) are then proposed and discussed to perform online dynamic equality-constrained quadratic programming. For comparison, Euler-type discrete-time ZNN models (called Euler-type discrete-time ZNNK and Euler-type discrete-time ZNNU models) and Newton iteration, with interesting links being found, are also presented. It is proved herein that the steady-state residual errors of the proposed Taylor-type discrete-time ZNN models, Euler-type discrete-time ZNN models, and Newton iteration have the patterns of O(h(3)), O(h(2)), and O(h), respectively, with h denoting the sampling gap. Numerical experiments, including the application examples, are carried out, of which the results further substantiate the theoretical findings and the efficacy of Taylor-type discrete-time ZNN models. Finally, the comparisons with Taylor-type discrete-time derivative model and other Lagrange-type discrete-time ZNN models for dynamic equality-constrained quadratic programming substantiate the superiority of the proposed Taylor-type discrete-time ZNN models once again.
Kamihigashi, Takashi
2017-01-01
Given a sequence [Formula: see text] of measurable functions on a σ -finite measure space such that the integral of each [Formula: see text] as well as that of [Formula: see text] exists in [Formula: see text], we provide a sufficient condition for the following inequality to hold: [Formula: see text] Our condition is considerably weaker than sufficient conditions known in the literature such as uniform integrability (in the case of a finite measure) and equi-integrability. As an application, we obtain a new result on the existence of an optimal path for deterministic infinite-horizon optimization problems in discrete time.
International Nuclear Information System (INIS)
Khorrami, M.
1995-01-01
A general formulation for discrete-time quantum mechanics, based on Feynman's method in ordinary quantum mechanics, is presented. It is shown that the ambiguities present in ordinary quantum mechanics (due to noncommutativity of the operators), are no longer present here. Then the criteria for the unitarity of the evolution operator are examined. It is shown that the unitarity of the evolution operator puts restrictions on the form of the action, and also implies the existence of a solution for the classical initial-value problem. 13 refs
Liu, Tao; Huang, Jie
2017-04-17
This paper presents a discrete-time recurrent neural network approach to solving systems of linear equations with two features. First, the system of linear equations may not have a unique solution. Second, the system matrix is not known precisely, but a sequence of matrices that converges to the unknown system matrix exponentially is known. The problem is motivated from solving the output regulation problem for linear systems. Thus, an application of our main result leads to an online solution to the output regulation problem for linear systems.
DEFF Research Database (Denmark)
Tabatabaeipour, Mojtaba
2013-01-01
Active fault detection and isolation (AFDI) is used for detection and isolation of faults that are hidden in the normal operation because of a low excitation signal or due to the regulatory actions of the controller. In this paper, a new AFDI method based on set-membership approaches is proposed...... un-falsified, the AFDI method is used to generate an auxiliary signal that is injected into the system for detection and isolation of faults that remain otherwise hidden or non-isolated using passive FDI (PFDI) methods. Having the set-valued estimation of the states for each model, the proposed AFDI...... method finds an optimal input signal that guarantees FDI in a finite time horizon. The input signal is updated at each iteration in a decreasing receding horizon manner based on the set-valued estimation of the current states and un-falsified models at the current sample time. The problem is solved...
Giulio PALOMBA
2006-01-01
In a typical tactical asset allocation set up managers generally make their investment decisions by inserting private information in an optimisation mechanism used to beat a benchmark portfolio; in this context the sole approach a' la Markowitz (1959) does not use all the available information about expected excess return and especially it does not take two main factors into account: first, asset returns often show changes in volatility, and second, the manager's private information plays no ...
Hudson, Christopher D; Bradley, Andrew J; Breen, James E; Green, Martin J
2015-04-01
Probabilistic sensitivity analysis (PSA) is a simulation-based technique for evaluating the relative importance of different inputs to a complex process model. It is commonly employed in decision analysis and for evaluation of the potential impact of uncertainty in research findings on clinical practice, but has a wide variety of other possible applications. In this example, it was used to evaluate the association between herd-level udder health and reproductive performance in dairy herds. Although several recent studies have found relatively large associations between mastitis and fertility at the level of individual inseminations or lactations, the current study demonstrated that herd-level intramammary infection status is highly unlikely to have a clinically significant impact on the overall reproductive performance of a dairy herd under typical conditions. For example, a large increase in incidence rate of clinical mastitis (from 92 to 131 cases per 100 cows per year) would be expected to increase a herd's modified FERTEX score (a cost-based measure of overall reproductive performance) by just £4.50(1) per cow per year. The herd's background level of submission rate (proportion of eligible cows served every 21 days) and pregnancy risk (proportion of inseminations leading to a pregnancy) correlated strongly with overall reproductive performance and explained a large proportion of the between-herd variation in performance. PSA proved to be a highly useful technique to aid understanding of results from a complex statistical model, and has great potential for a wide variety of applications within the field of veterinary science. Copyright © 2015 Elsevier Ltd. All rights reserved.
International Nuclear Information System (INIS)
Song, Qiankun; Wang, Zidong
2007-01-01
In this Letter, the analysis problem for the existence and stability of periodic solutions is investigated for a class of general discrete-time recurrent neural networks with time-varying delays. For the neural networks under study, a generalized activation function is considered, and the traditional assumptions on the boundedness, monotony and differentiability of the activation functions are removed. By employing the latest free-weighting matrix method, an appropriate Lyapunov-Krasovskii functional is constructed and several sufficient conditions are established to ensure the existence, uniqueness, and globally exponential stability of the periodic solution for the addressed neural network. The conditions are dependent on both the lower bound and upper bound of the time-varying time delays. Furthermore, the conditions are expressed in terms of the linear matrix inequalities (LMIs), which can be checked numerically using the effective LMI toolbox in MATLAB. Two simulation examples are given to show the effectiveness and less conservatism of the proposed criteria
Figueiredo, Danilo Zucolli; Costa, Oswaldo Luiz do Valle
2017-10-01
This paper deals with the H2 optimal control problem of discrete-time Markov jump linear systems (MJLS) considering the case in which the Markov chain takes values in a general Borel space ?. It is assumed that the controller has access only to an output variable and to the jump parameter. The goal, in this case, is to design a dynamic Markov jump controller such that the H2-norm of the closed-loop system is minimised. It is shown that the H2-norm can be written as the sum of two H2-norms, such that one of them does not depend on the control, and the other one is obtained from the optimal filter for an infinite-horizon filtering problem. This result can be seen as a separation principle for MJLS with Markov chain in a Borel space ? considering the infinite time horizon case.
Wang, Jun-Sheng; Yang, Guang-Hong
2017-07-25
This paper studies the optimal output-feedback control problem for unknown linear discrete-time systems with stochastic measurement and process noise. A dithered Bellman equation with the innovation covariance matrix is constructed via the expectation operator given in the form of a finite summation. On this basis, an output-feedback-based approximate dynamic programming method is developed, where the terms depending on the innovation covariance matrix are available with the aid of the innovation covariance matrix identified beforehand. Therefore, by iterating the Bellman equation, the resulting value function can converge to the optimal one in the presence of the aforementioned noise, and the nearly optimal control laws are delivered. To show the effectiveness and the advantages of the proposed approach, a simulation example and a velocity control experiment on a dc machine are employed.
Directory of Open Access Journals (Sweden)
Seung-Jin Yoon
2018-02-01
Full Text Available Inductive-capacitive-inductive (LCL-type filters are currently preferred as a replacement for L-type filters in distributed generation (DG power systems, due to their superior harmonic attenuation capability. However, the third-order dynamics introduced by LCL filters pose a challenge to design a satisfactory controller for such a system. Conventionally, an LCL-filtered grid-connected inverter can be effectively controlled by using a full-state feedback control. However, this control approach requires the measurement of all system state variables, which brings about more complexity for the inverter system. To address this issue, this paper presents a systematic procedure to design an observer-based integral state feedback control for a LCL-filtered grid-connected inverter in the discrete-time domain. The proposed control scheme consists of an integral state feedback controller and a full-state observer which uses the control input, grid-side currents, and grid voltages to predict all the system state variables. Therefore, only the grid-side current sensors and grid voltage sensors are required to implement the proposed control scheme. Due to the discrete-time integrator incorporated in the state feedback controller, the proposed control scheme ensures both the reference tracking and disturbance rejection performance of the inverter system in a practical and simple way. As a result, superior control performance can be achieved by using the reduced number of sensors, which significantly reduces the cost and complexity of the LCL-filtered grid-connected inverter system in DG applications. To verify the practical usefulness of the proposed control scheme, a 2 kW three-phase prototype grid-connected inverter has been constructed, and the proposed control system has been implemented based on 32-bit floating-point digital signal processor (DSP TMS320F28335. The effectiveness of the proposed scheme is demonstrated through the comprehensive simulation
Shih, Peter; Kaul, Brian C; Jagannathan, Sarangapani; Drallmeier, James A
2009-10-01
A novel reinforcement-learning-based output adaptive neural network (NN) controller, which is also referred to as the adaptive-critic NN controller, is developed to deliver the desired tracking performance for a class of nonlinear discrete-time systems expressed in nonstrict feedback form in the presence of bounded and unknown disturbances. The adaptive-critic NN controller consists of an observer, a critic, and two action NNs. The observer estimates the states and output, and the two action NNs provide virtual and actual control inputs to the nonlinear discrete-time system. The critic approximates a certain strategic utility function, and the action NNs minimize the strategic utility function and control inputs. All NN weights adapt online toward minimization of a performance index, utilizing the gradient-descent-based rule, in contrast with iteration-based adaptive-critic schemes. Lyapunov functions are used to show the stability of the closed-loop tracking error, weights, and observer estimates. Separation and certainty equivalence principles, persistency of excitation condition, and linearity in the unknown parameter assumption are not needed. Experimental results on a spark ignition (SI) engine operating lean at an equivalence ratio of 0.75 show a significant (25%) reduction in cyclic dispersion in heat release with control, while the average fuel input changes by less than 1% compared with the uncontrolled case. Consequently, oxides of nitrogen (NO(x)) drop by 30%, and unburned hydrocarbons drop by 16% with control. Overall, NO(x)'s are reduced by over 80% compared with stoichiometric levels.
Orsini, Caitlin A; Hernandez, Caesar M; Singhal, Sarthak; Kelly, Kyle B; Frazier, Charles J; Bizon, Jennifer L; Setlow, Barry
2017-11-29
Decision making is a multifaceted process, consisting of several distinct phases that likely require different cognitive operations. Previous work showed that the basolateral amygdala (BLA) is a critical substrate for decision making involving risk of punishment; however, it is unclear how the BLA is recruited at different stages of the decision process. To this end, the current study used optogenetics to inhibit the BLA during specific task phases in a model of risky decision making (risky decision-making task) in which rats choose between a small, "safe" reward and a large reward accompanied by varying probabilities of footshock punishment. Male Long-Evans rats received intra-BLA microinjections of viral vectors carrying either halorhodopsin (eNpHR3.0-mCherry) or mCherry alone (control) followed by optic fiber implants and were trained in the risky decision-making task. Laser delivery during the task occurred during intertrial interval, deliberation, or reward outcome phases, the latter of which was further divided into the three possible outcomes (small, safe; large, unpunished; large, punished). Inhibition of the BLA selectively during the deliberation phase decreased choice of the large, risky outcome (decreased risky choice). In contrast, BLA inhibition selectively during delivery of the large, punished outcome increased risky choice. Inhibition had no effect during the other phases, nor did laser delivery affect performance in control rats. Collectively, these data indicate that the BLA can either inhibit or promote choice of risky options, depending on the phase of the decision process in which it is active. SIGNIFICANCE STATEMENT To date, most behavioral neuroscience research on neural mechanisms of decision making has used techniques that preclude assessment of distinct phases of the decision process. Here we show that optogenetic inhibition of the BLA has opposite effects on choice behavior in a rat model of risky decision making, depending on the phase
Xie, Xiang-Peng; Yue, Dong; Park, Ju H
2018-02-01
The paper provides relaxed designs of fault estimation observer for nonlinear dynamical plants in the Takagi-Sugeno form. Compared with previous theoretical achievements, a modified version of fuzzy fault estimation observer is implemented with the aid of the so-called maximum-priority-based switching law. Given each activated switching status, the appropriate group of designed matrices can be provided so as to explore certain key properties of the considered plants by means of introducing a set of matrix-valued variables. Owing to the reason that more abundant information of the considered plants can be updated in due course and effectively exploited for each time instant, the conservatism of the obtained result is less than previous theoretical achievements and thus the main defect of those existing methods can be overcome to some extent in practice. Finally, comparative simulation studies on the classical nonlinear truck-trailer model are given to certify the benefits of the theoretic achievement which is obtained in our study. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
Khan, Pathan Fayaz; Sengottuvel, S; Patel, Rajesh; Gireesan, K; Baskaran, R; Mani, Awadhesh
2018-05-01
Contact heat evoked potentials (CHEPs) are recorded from the brain by giving thermal stimulations through heating pads kept on the surface of the skin. CHEP signals have crucial diagnostic implications in human pain activation studies. This work proposes a novel design of a digital proportional integral (PI) controller based on Arduino microcontroller with a view to explore the suitability of an electric heating pad for use as a thermode in a custom-made, cost-effective CHEP stimulator. The purpose of PI controller is to set, regulate, and deliver desired temperatures on the surface of the heating pad in a user-defined pattern. The transfer function of the heating system has been deduced using the parametric system identification method, and the design parameters of the controller have been identified using the root locus technique. The efficiency of the proposed PI controller in circumventing the well-known integrator windup problem (error in the integral term builds excessively, leading to large transients in the controller output) in tracking the reference input and the controller effort (CE) in rejecting output disturbances to maintain the set temperature of the heating pad have been found to be superior compared with the conventional PI controller and two of the existing anti-windup models.
Multivariate Term Structure Models with Level and Heteroskedasticity Effects
DEFF Research Database (Denmark)
Christiansen, Charlotte
2005-01-01
The paper introduces and estimates a multivariate level-GARCH model for the long rate and the term-structure spread where the conditional volatility is proportional to the ãth power of the variable itself (level effects) and the conditional covariance matrix evolves according to a multivariate GA...... and the level model. GARCH effects are more important than level effects. The results are robust to the maturity of the interest rates. Udgivelsesdato: MAY...
Directory of Open Access Journals (Sweden)
Doo Ho Lee
Full Text Available This work studies the optimal pricing strategy in a discrete-time Geo/Geo/1 queuing system under the sojourn time-dependent reward. We consider two types of pricing schemes. The first one is called the ex-post payment scheme where the server charges a price that is proportional to the time a customer spends in the system, and the second one is called ex-ante payment scheme where the server charges a flat price for all services. In each pricing scheme, a departing customer receives the reward that is inversely proportional to his/her sojourn time. The server should make the optimal pricing decisions in order to maximize its expected profits per time unit in each pricing scheme. This work also investigates customer's equilibrium joining or balking behavior under server's optimal pricing strategy. Numerical experiments are also conducted to validate our analysis. Keywords: Optimal pricing, Equilibrium behavior, Geo/Geo/1 queue, Sojourn time-dependent reward