Extreme-Point Symmetric Mode Decomposition Method for Nonlinear and Non-Stationary Signal Processing
Wang, Jin-Liang
2013-01-01
To process nonlinear and non-stationary signals, an extreme-point symmetric mode decomposition (ESMD) method is developed. It can be seen as a new alternate of the well-known Hilbert-Huang transform (HHT) method which is widely used nowadays. There are two parts for it. The first part is the decomposition approach which yields a series of intrinsic mode functions (IMFs) together with an optimal adaptive global mean (AGM) curve, the second part is the direct interpolating (DI) approach which yields instantaneous amplitudes and frequencies for the IMFs together with a time-varying energy. Relative to the HHT method it has five characteristics as follows: (1) Different from constructing 2 outer envelopes, its sifting process is implemented by the aid of 1, 2 or 3 inner interpolating curves; (2) It does not decompose the signal to the last trend curve with at most one extreme point, it optimizes the residual component to be an optimal AGM curve which possesses a certain number of extreme points; (3) Its symmetry ...
Sequential decision analysis for nonstationary stochastic processes
Schaefer, B.
1974-01-01
A formulation of the problem of making decisions concerning the state of nonstationary stochastic processes is given. An optimal decision rule, for the case in which the stochastic process is independent of the decisions made, is derived. It is shown that this rule is a generalization of the Bayesian likelihood ratio test; and an analog to Wald's sequential likelihood ratio test is given, in which the optimal thresholds may vary with time.
An Entropy Measure of Non-Stationary Processes
Directory of Open Access Journals (Sweden)
Ling Feng Liu
2014-03-01
Full Text Available Shannon’s source entropy formula is not appropriate to measure the uncertainty of non-stationary processes. In this paper, we propose a new entropy measure for non-stationary processes, which is greater than or equal to Shannon’s source entropy. The maximum entropy of the non-stationary process has been considered, and it can be used as a design guideline in cryptography.
Conditional least squares estimation in nonstationary nonlinear stochastic regression models
Jacob, Christine
2010-01-01
Let $\\{Z_n\\}$ be a real nonstationary stochastic process such that $E(Z_n|{\\mathcaligr F}_{n-1})\\stackrel{\\mathrm{a.s.}}{<}\\infty$ and $E(Z^2_n|{\\mathcaligr F}_{n-1})\\stackrel{\\mathrm{a.s.}}{<}\\infty$, where $\\{{\\mathcaligr F}_n\\}$ is an increasing sequence of $\\sigma$-algebras. Assuming that $E(Z_n|{\\mathcaligr F}_{n-1})=g_n(\\theta_0,\
Some Results on the Wavelet Packet Decomposition of Nonstationary Processes
Directory of Open Access Journals (Sweden)
Touati Sami
2002-01-01
Full Text Available Wavelet/wavelet packet decomposition has become a very useful tool in describing nonstationary processes. Important examples of nonstationary processes encountered in practice are cyclostationary processes or almost-cyclostationary processes. In this paper, we study the statistical properties of the wavelet packet decomposition of a large class of nonstationary processes, including in particular cyclostationary and almost-cyclostationary processes. We first investigate in a general framework, the existence and some properties of the cumulants of wavelet packet coefficients. We then study more precisely the almost-cyclostationary case, and determine the asymptotic distributions of wavelet packet coefficients. Finally, we particularize some of our results in the cyclostationary case before providing some illustrative simulations.
Huang, Norden E.
2000-04-01
A new method for analyzing nonlinear and nonstationary data has been developed. The key pat of the method is the Empirical Mode Decomposition method with which any complicated data set can be decomposed into a finite and often small number of Intrinsic Mode Functions (IMF). An IMF is define das any function having the same numbers of zero- crossing and extrema, and also having symmetric envelopes defined by the local maxima and minima respectively. The IMF also admits well-behaved Hilbert transform. This decomposition method is adaptive, and therefore, highly efficient. Since the decomposition is based on the local characteristic time scale of het data, it is applicable to nonlinear and nonstationary processes. With the Hilbert transform, the IMF yield instantaneous frequencies as functions of time that give sharp identifications of embedded structures. The final presentation of the result is an energy-frequency-time distribution, designated as the Hilbert Spectrum. Comparisons with Wavelet and window Fourier analysis show the new method offers much better temporal and frequency resolutions.
Stationarizing two classes of nonstationary processes by wavelet
Institute of Scientific and Technical Information of China (English)
TANG Hong-min; XIE Zhong-jie
2006-01-01
The main purpose of this paper is to discuss the stationarity of two classes of nonstationary processes after wavelet transformations.Owing to the fact that the wavelet transformation possesses localization and implicit differencing property,the authors show that after wavelet transformation,the fractionally differenced process and the harmonizable periodically correlated process may be changed into stationary processes.
Simulation of non-stationary ground motion processes (II)
Institute of Scientific and Technical Information of China (English)
LIANG Jian-wen
2005-01-01
This paper proposes a method for simulation of non-stationary ground motion processes having the identical statistical feature, time-dependent power spectrum, with a given ground motion record, on the basis of review of simulation of non-stationary ground motion processes. The method has the following advantages: the sample processes are non-stationary both in amplitude and frequency, and both the amplitude and frequency non-stationarity depend on the target power spectrum; the power spectrum of any sample process does not necessarily accord with the target power spectrum, but statistically, it strictly accords with the target power spectrum. Finally, the method is verified by simulation of one acceleration record in Landers earthquake.
Time reversibility from visibility graphs of non-stationary processes
Lacasa, Lucas
2015-01-01
Visibility algorithms are a family of methods to map time series into networks, with the aim of describing the structure of time series and their underlying dynamical properties in graph-theoretical terms. Here we explore some properties of both natural and horizontal visibility graphs associated to several non-stationary processes, and we pay particular attention to their capacity to assess time irreversibility. Non-stationary signals are (infinitely) irreversible by definition (independently of whether the process is Markovian or producing entropy at a positive rate), and thus the link between entropy production and time series irreversibility has only been explored in non-equilibrium stationary states. Here we show that the visibility formalism naturally induces a new working definition of time irreversibility, which allows to quantify several degrees of irreversibility for stationary and non-stationary series, yielding finite values that can be used to efficiently assess the presence of memory and off-equ...
Simulation of non-stationary ground motion processes (I)
Institute of Scientific and Technical Information of China (English)
LIANG Jian-wen
2005-01-01
This paper presents a spectral representation method for simulation of non-stationary ground motion processes on the basis of Priestley's evolutionary spectral theory. Following this method, sample processes can be generated using a cosine series formula. It is shown that, these sample processes accurately reflect the prescribed characteristics of the evolutionary power spectral density function when the number of the terms in the cosine series is large enough; and the ensemble expected value and the ensemble autocorrelation function approach the corresponding target functions, respectively, as the sample size increases; and these sample processes are asymptotically normal as the number of the terms in the series tends to infinity. Finally, a few special cases of the formula are discussed, one of which is non-stationary white noise process, and other one is reduced to the formula for simulation of stationary stochastic processes.
ARE THE REAL GDP SERIES IN ASIAN COUNTRIES NONSTATIONARY OR NONLINEAR STATIONARY?
Directory of Open Access Journals (Sweden)
Nurun Nahar Jannati
2013-06-01
Full Text Available This paper checks whether per capita real gross domestic product (GDP series in 16 Asian countries are nonstationary or nonlinear and globally stationary during the period from 1970 to 2009, by applying the nonlinear unit root tests developed by Kapitanios, Shin and Snell (2003. In five out of the sixteen countries that is approximately one-third of the countries, the series are found to be stationary with asymmetric or nonlinear mean reversion. Analyses depict that nonlinear unit root test are suitable for some cases compare to the commonly used unit root test, Augmented Dickey-Fuller (ADF and Dickey-Fuller Generalized Least Square (DF-GLS tests.
Band-phase-randomized Surrogates to assess nonlinearity in non-stationary time series
Guarin, Diego; Orozco, Alvaro
2011-01-01
Testing for nonlinearity is one of the most important preprocessing steps in nonlinear time series analysis. Typically, this is done by means of the linear surrogate data methods. But it is a known fact that the validity of the results heavily depends on the stationarity of the time series. Since most physiological signals are non-stationary, it is easy to falsely detect nonlinearity using the linear surrogate data methods. In this document, we propose a methodology to extend the procedure for generating constrained surrogate time series in order to assess nonlinearity in non-stationary data. The method is based on the band-phase-randomized surrogates, which consists (contrary to the linear surrogate data methods) in randomizing only a portion of the Fourier phases in the high frequency band. Analysis of simulated time series showed that in comparison to the linear surrogate data method, our method is able to discriminate between linear stationarity, linear non-stationary and nonlinear time series. When apply...
Local polynomial Whittle estimation covering non-stationary fractional processes
DEFF Research Database (Denmark)
Nielsen, Frank
This paper extends the local polynomial Whittle estimator of Andrews & Sun (2004) to fractionally integrated processes covering stationary and non-stationary regions. We utilize the notion of the extended discrete Fourier transform and periodogram to extend the local polynomial Whittle estimator ...... study illustrates the performance of the proposed estimator compared to the classical local Whittle estimator and the local polynomial Whittle estimator. The empirical justi.cation of the proposed estimator is shown through an analysis of credit spreads....
NONLINEAR GALERKIN METHOD FOR THE EXTERIOR NONSTATIONARY NAVIER-STOKES EQUATIONS
Institute of Scientific and Technical Information of China (English)
何银年; 李开泰
2002-01-01
A new algorithm combining nonlinear Galerkin method and coupling method of finite element and boundary element is introduced to solve the exterior nonstationary Navier-Stokes equations. The regularity of the coupling variational formulation and the convergence of the approximate solution corresponding to the algorithm are proved. If the fine mesh h is choosed as coarse mesh H-sgure, the nonlinear Galerkin method, nonlinearity is only treated on the coarse grid and linearity is treated on the fine grid. Hence, the new algorithm can save a large amount of computational time.
Global sea surface temperature (SST) anomalies can affect terrestrial precipitation via ocean-atmosphere interaction known as climate teleconnection. Non-stationary and non-linear characteristics of the ocean-atmosphere system make the identification of the teleconnection signals...
Nonstationary Feller process with time-varying coefficients
Masoliver, Jaume
2016-01-01
We study the nonstationary Feller process with time varying coefficients. We obtain the exact probability distribution exemplified by its characteristic function and cumulants. In some particular cases we exactly invert the distribution and achieve the probability density function. We show that for sufficiently long times this density approaches a Γ distribution with time-varying shape and scale parameters. Not far from the origin the process obeys a power law with an exponent dependent of time, thereby concluding that accessibility to the origin is not static but dynamic. We finally discuss some possible applications of the process.
The Fourier decomposition method for nonlinear and non-stationary time series analysis.
Singh, Pushpendra; Joshi, Shiv Dutt; Patney, Rakesh Kumar; Saha, Kaushik
2017-03-01
for many decades, there has been a general perception in the literature that Fourier methods are not suitable for the analysis of nonlinear and non-stationary data. In this paper, we propose a novel and adaptive Fourier decomposition method (FDM), based on the Fourier theory, and demonstrate its efficacy for the analysis of nonlinear and non-stationary time series. The proposed FDM decomposes any data into a small number of 'Fourier intrinsic band functions' (FIBFs). The FDM presents a generalized Fourier expansion with variable amplitudes and variable frequencies of a time series by the Fourier method itself. We propose an idea of zero-phase filter bank-based multivariate FDM (MFDM), for the analysis of multivariate nonlinear and non-stationary time series, using the FDM. We also present an algorithm to obtain cut-off frequencies for MFDM. The proposed MFDM generates a finite number of band-limited multivariate FIBFs (MFIBFs). The MFDM preserves some intrinsic physical properties of the multivariate data, such as scale alignment, trend and instantaneous frequency. The proposed methods provide a time-frequency-energy (TFE) distribution that reveals the intrinsic structure of a data. Numerical computations and simulations have been carried out and comparison is made with the empirical mode decomposition algorithms.
Theoretical analysis of radiographic images by nonstationary Poisson processes
Energy Technology Data Exchange (ETDEWEB)
Tanaka, K.; Uchida, S. (Gifu Univ. (Japan)); Yamada, I.
1980-12-01
This paper deals with the noise analysis of radiographic images obtained in the usual fluorescent screen-film system. The theory of nonstationary Poisson processes is applied to the analysis of the radiographic images containing the object information. The ensemble averages, the autocorrelation functions, and the Wiener spectrum densities of the light-energy distribution at the fluorescent screen and of the film optical-density distribution are obtained. The detection characteristics of the system are evaluated theoretically. Numerical examples one-dimensional image are shown and the results are compared with those obtained under the assumption that the object image is related to the background noise by the additive process.
Theoretical Analysis of Radiographic Images by Nonstationary Poisson Processes
Tanaka, Kazuo; Yamada, Isao; Uchida, Suguru
1980-12-01
This paper deals with the noise analysis of radiographic images obtained in the usual fluorescent screen-film system. The theory of nonstationary Poisson processes is applied to the analysis of the radiographic images containing the object information. The ensemble averages, the autocorrelation functions, and the Wiener spectrum densities of the light-energy distribution at the fluorescent screen and of the film optical-density distribution are obtained. The detection characteristics of the system are evaluated theoretically. Numerical examples of the one-dimensional image are shown and the results are compared with those obtained under the assumption that the object image is related to the background noise by the additive process.
Robust Nonlinear Causality Analysis of Non-Stationary Multivariate Physiological Time Series.
Schaeck, Tim; Muma, Michael; Feng, Mengling; Guan, Cuntai; Zoubir, Abdelhak
2017-05-26
An important research area in biomedical signal processing is that of quantifying the relationship between simultaneously observed time series and to reveal interactions between the signals. Since biomedical signals are potentially non-stationary and the measurements may contain outliers and artifacts, we introduce a robust time-varying generalized partial directed coherence (rTV-gPDC) function. The proposed method, which is based on a robust estimator of the timevarying autoregressive (TVAR) parameters, is capable of revealing directed interactions between signals. By definition, the rTV-gPDC only displays the linear relationships between the signals. We therefore suggest to approximate the residuals of the TVAR process, which potentially carry information about the nonlinear causality by a piece-wise linear time-varying moving-average (TVMA) model. The performance of the proposed method is assessed via extensive simulations. To illustrate the method's applicability to real-world problems, it is applied to a neurophysiological study that involves intracranial pressure (ICP), arterial blood pressure (ABP), and brain tissue oxygenation level (PtiO2) measurements. The rTV-gPDC reveals causal patterns that are in accordance with expected cardiosudoral meachanisms and potentially provides new insights regarding traumatic brain injuries (TBI). The rTV-gPDC is not restricted to the above problem but can be useful in revealing interactions in a broad range of applications.
Um, Myoung-Jin; Kim, Yeonjoo; Markus, Momcilo; Wuebbles, Donald J.
2017-09-01
Climate extremes, such as heavy precipitation events, have become more common in recent decades, and nonstationarity concepts have increasingly been adopted to model hydrologic extremes. Various issues are associated with applying nonstationary modeling to extremes, and in this study, we focus on assessing the need for different forms of nonlinear functions in a nonstationary generalized extreme value (GEV) model of different annual maximum precipitation (AMP) time series. Moreover, we suggest an efficient approach for selecting the nonlinear functions of a nonstationary GEV model. Based on observed and multiple projected AMP data for eight cities across the U.S., three separate tasks are proposed. First, we conduct trend and stationarity tests for the observed and projected data. Second, AMP series are fit with thirty different nonlinear functions, and the best functions among these are selected. Finally, the selected nonlinear functions are used to model the location parameter of a nonstationary GEV model and stationary and nonstationary GEV models with a linear function. Our results suggest that the simple use of nonlinear functions might prove useful with nonstationary GEV models of AMP for different locations with different types of model results.
Testing for long memory in potentially nonstationary perturbed fractional processes
DEFF Research Database (Denmark)
Nielsen, Frank; Frederiksen, Per S.
In this paper, we propose new tests for long memory in stationary and nonstationary time series possibly perturbed by short-run noise which may be serially correlated. The tests are all based on semiparametric estimators and exploit the self-similarity property of long memory processes. We o......¤er simulation results that show good size properties of the tests, with power against spurious long memory. An empirical study of daily log-squared returns series of exchange rates and DJIA30 stocks shows that indeed there is long memory in exchange rate volatility and stock return volatility....
Sequential reconstruction of driving-forces from nonlinear nonstationary dynamics
Güntürkün, Ulaş
2010-07-01
This paper describes a functional analysis-based method for the estimation of driving-forces from nonlinear dynamic systems. The driving-forces account for the perturbation inputs induced by the external environment or the secular variations in the internal variables of the system. The proposed algorithm is applicable to the problems for which there is too little or no prior knowledge to build a rigorous mathematical model of the unknown dynamics. We derive the estimator conditioned on the differentiability of the unknown system’s mapping, and smoothness of the driving-force. The proposed algorithm is an adaptive sequential realization of the blind prediction error method, where the basic idea is to predict the observables, and retrieve the driving-force from the prediction error. Our realization of this idea is embodied by predicting the observables one-step into the future using a bank of echo state networks (ESN) in an online fashion, and then extracting the raw estimates from the prediction error and smoothing these estimates in two adaptive filtering stages. The adaptive nature of the algorithm enables to retrieve both slowly and rapidly varying driving-forces accurately, which are illustrated by simulations. Logistic and Moran-Ricker maps are studied in controlled experiments, exemplifying chaotic state and stochastic measurement models. The algorithm is also applied to the estimation of a driving-force from another nonlinear dynamic system that is stochastic in both state and measurement equations. The results are judged by the posterior Cramer-Rao lower bounds. The method is finally put into test on a real-world application; extracting sun’s magnetic flux from the sunspot time series.
Non-stationary resonance dynamics of a nonlinear sonic vacuum with grounding supports
Koroleva (Kikot), I. P.; Manevitch, L. I.; Vakakis, Alexander F.
2015-11-01
In a recent work [L.I. Manevitch, A.F.Vakakis, Nonlinear oscillatory acoustic vacuum, SIAM Journal of Applied Mathematics 74(6) (2014), 1742-1762] it was shown that a periodic chain of linearly coupled particles performing low-energy in-plane transverse oscillations behaves as a strongly nonlinear sonic vacuum (with corresponding speed of sound equal to zero). In this work we consider the grounded version of this system by coupling each particle to the ground through lateral springs in order to study the effect of the grounding stiffness on the strongly nonlinear dynamics. In that context we consider the simplest possible such system consisting of two coupled particles and present analytical and numerical studies of the non-stationary planar dynamics. The most significant limiting case corresponding to predominant low energy transversal excitations is considered by taking into account leading order geometric nonlinearities. Then we show that the grounded system behaves as a nonlinear sonic vacuum due to the purely cubic stiffness nonlinearities in the governing equations of motion and the complete absence of any linear stiffness terms. Under certain assumptions the nonlinear normal modes (i.e., the time-periodic nonlinear oscillations) in the configuration space of this system coincide with those of the corresponding linear one, so they obey the same orthogonality relations. Moreover, we analytically find that there are two transitions in the dynamics of this system, with the parameter governing these transitions being the relation between the lateral (grounding) and the interchain stiffnesses. The first transition concerns a bifurcation of one of the nonlinear normal modes (NNMs), whereas the second provides conditions for intense energy transfers and mixing between the NNMs. The drastic effects of these bifurcations on the non-stationary resonant dynamics are discussed. Specifically, the second transition relates to strongly non-stationary dynamics, and signifies
Huang, Norden E.
1999-01-01
A new method for analyzing nonlinear and nonstationary data has been developed. The key part of the method is the Empirical Mode Decomposition method with which any complicated data set can be decomposed into a finite and often small number of Intrinsic Mode Functions (IMF). An IMF is defined as any function having the same numbers of zero-crossing and extrema, and also having symmetric envelopes defined by the local maxima and minima respectively. The IMF also admits well-behaved Hilbert transform. This decomposition method is adaptive, and, therefore, highly efficient. Since the decomposition is based on the local characteristic time scale of the data, it is applicable to nonlinear and nonstationary processes. With the Hilbert transform, the Intrinsic Mode Functions yield instantaneous frequencies as functions of time that give sharp identifications of imbedded structures. The final presentation of the results is an energy-frequency-time distribution, designated as the Hilbert Spectrum, Example of application of this method to earthquake and building response will be given. The results indicate those low frequency components, totally missed by the Fourier analysis, are clearly identified by the new method. Comparisons with Wavelet and window Fourier analysis show the new method offers much better temporal and frequency resolutions.
A New Method for Non-linear and Non-stationary Time Series Analysis:
The Hilbert Spectral Analysis
CERN. Geneva
2000-01-01
A new method for analysing non-linear and non-stationary data has been developed. The key part of the method is the Empirical Mode Decomposition method with which any complicated data set can be decomposed into a finite and often small number of Intrinsic Mode Functions (IMF). An IMF is defined as any function having the same numbers of zero crossing and extreme, and also having symmetric envelopes defined by the local maximal and minima respectively. The IMF also admits well-behaved Hilbert transform. This decomposition method is adaptive, and, therefore, highly efficient. Since the decomposition is based on the local characteristic time scale of the data, it is applicable to non-linear and non-stationary processes. With the Hilbert transform, the Intrinsic Mode Functions yield instantaneous frequencies as functions of time that give sharp identifications of imbedded structures. The final presentation of the results is an energy-frequency-time distribution, designated as the Hilbert Spectrum. Classical non-l...
Wavelet-Based Methodology for Evolutionary Spectra Estimation of Nonstationary Typhoon Processes
Directory of Open Access Journals (Sweden)
Guang-Dong Zhou
2015-01-01
Full Text Available Closed-form expressions are proposed to estimate the evolutionary power spectral density (EPSD of nonstationary typhoon processes by employing the wavelet transform. Relying on the definition of the EPSD and the concept of the wavelet transform, wavelet coefficients of a nonstationary typhoon process at a certain time instant are interpreted as the Fourier transform of a new nonstationary oscillatory process, whose modulating function is equal to the modulating function of the nonstationary typhoon process multiplied by the wavelet function in time domain. Then, the EPSD of nonstationary typhoon processes is deduced in a closed form and is formulated as a weighted sum of the squared moduli of time-dependent wavelet functions. The weighted coefficients are frequency-dependent functions defined by the wavelet coefficients of the nonstationary typhoon process and the overlapping area of two shifted wavelets. Compared with the EPSD, defined by a sum of the squared moduli of the wavelets in frequency domain in literature, this paper provides an EPSD estimation method in time domain. The theoretical results are verified by uniformly modulated nonstationary typhoon processes and non-uniformly modulated nonstationary typhoon processes.
Uma Maheswari, R.; Umamaheswari, R.
2017-02-01
Condition Monitoring System (CMS) substantiates potential economic benefits and enables prognostic maintenance in wind turbine-generator failure prevention. Vibration Monitoring and Analysis is a powerful tool in drive train CMS, which enables the early detection of impending failure/damage. In variable speed drives such as wind turbine-generator drive trains, the vibration signal acquired is of non-stationary and non-linear. The traditional stationary signal processing techniques are inefficient to diagnose the machine faults in time varying conditions. The current research trend in CMS for drive-train focuses on developing/improving non-linear, non-stationary feature extraction and fault classification algorithms to improve fault detection/prediction sensitivity and selectivity and thereby reducing the misdetection and false alarm rates. In literature, review of stationary signal processing algorithms employed in vibration analysis is done at great extent. In this paper, an attempt is made to review the recent research advances in non-linear non-stationary signal processing algorithms particularly suited for variable speed wind turbines.
Nonlinear stability of non-stationary cross-flow vortices in compressible boundary layers
Gajjar, J. S. B.
1995-01-01
The nonlinear evolution of long wavelength non-stationary cross-flow vortices in a compressible boundary layer is investigated and the work extends that of Gajjar (1994) to flows involving multiple critical layers. The basic flow profile considered in this paper is that appropriate for a fully three-dimensional boundary layer with O(1) Mach number and with wall heating or cooling. The governing equations for the evolution of the cross-flow vortex are obtained and some special cases are discussed. One special case includes linear theory where exact analytic expressions for the growth rate of the vortices are obtained. Another special case is a generalization of the Bassom & Gajjar (1988) results for neutral waves to compressible flows. The viscous correction to the growth rate is derived and it is shown how the unsteady nonlinear critical layer structure merges with that for a Haberman type of viscous critical layer.
Spurious cross-frequency amplitude-amplitude coupling in nonstationary, nonlinear signals
Yeh, Chien-Hung; Lo, Men-Tzung; Hu, Kun
2016-07-01
Recent studies of brain activities show that cross-frequency coupling (CFC) plays an important role in memory and learning. Many measures have been proposed to investigate the CFC phenomenon, including the correlation between the amplitude envelopes of two brain waves at different frequencies - cross-frequency amplitude-amplitude coupling (AAC). In this short communication, we describe how nonstationary, nonlinear oscillatory signals may produce spurious cross-frequency AAC. Utilizing the empirical mode decomposition, we also propose a new method for assessment of AAC that can potentially reduce the effects of nonlinearity and nonstationarity and, thus, help to avoid the detection of artificial AACs. We compare the performances of this new method and the traditional Fourier-based AAC method. We also discuss the strategies to identify potential spurious AACs.
DEFF Research Database (Denmark)
Harrod, Steven; Kelton, W. David
2006-01-01
Nonstationary Poisson processes are appropriate in many applications, including disease studies, transportation, finance, and social policy. The authors review the risks of ignoring nonstationarity in Poisson processes and demonstrate three algorithms for generation of Poisson processes with piec......Nonstationary Poisson processes are appropriate in many applications, including disease studies, transportation, finance, and social policy. The authors review the risks of ignoring nonstationarity in Poisson processes and demonstrate three algorithms for generation of Poisson processes...
Cappell, M S; Spray, D C; Bennett, M V
1988-06-28
Protractor muscles in the gastropod mollusc Navanax inermis exhibit typical spontaneous miniature end plate potentials with mean amplitude 1.71 +/- 1.19 (standard deviation) mV. The evoked end plate potential is quantized, with a quantum equal to the miniature end plate potential amplitude. When their rate is stationary, occurrence of miniature end plate potentials is a random, Poisson process. When non-stationary, spontaneous miniature end plate potential occurrence is a non-stationary Poisson process, a Poisson process with the mean frequency changing with time. This extends the random Poisson model for miniature end plate potentials to the frequently observed non-stationary occurrence. Reported deviations from a Poisson process can sometimes be accounted for by the non-stationary Poisson process and more complex models, such as clustered release, are not always needed.
Cicone, Antonio; Zhou, Haomin; Piersanti, Mirko; Materassi, Massimo; Spogli, Luca
2017-04-01
Nonlinear and nonstationary signals are ubiquitous in real life. Their decomposition and analysis is of crucial importance in many research fields. Traditional techniques, like Fourier and wavelet Transform have been proved to be limited in this context. In the last two decades new kind of nonlinear methods have been developed which are able to unravel hidden features of these kinds of signals. In this talk we will review the state of the art and present a new method, called Adaptive Local Iterative Filtering (ALIF). This method, developed originally to study mono-dimensional signals, unlike any other technique proposed so far, can be easily generalized to study two or higher dimensional signals. Furthermore, unlike most of the similar methods, it does not require any a priori assumption on the signal itself, so that the method can be applied as it is to any kind of signals. Applications of ALIF algorithm to real life signals analysis will be presented. Like, for instance, the behavior of the water level near the coastline in presence of a Tsunami, the length of the day signal, the temperature and pressure measured at ground level on a global grid, and the radio power scintillation from GNSS signals.
Seismic response of structures: from non-stationary to non-linear effects
Carlo Ponzo, Felice; Ditommaso, Rocco; Mucciarelli, Marco; Smith, Tobias
2013-04-01
cases it is possible to confuse apparent frequencies variations with real ones (related to nonlinear phenomena) which could lead to an incorrect assessment of the structural safety. In this paper a new theoretical approach is proposed to discriminate non-stationary from non-linear effects, it was tested on both numerical and experimental accelerometric recordings respectively retrieved from one degree of freedom oscillator and one timber framed structure monitored during the 2011 Canterbury Seismic Sequence.
Faes, Luca; Zhao, He; Chon, Ki H; Nollo, Giandomenico
2009-03-01
We propose a method to extend to time-varying (TV) systems the procedure for generating typical surrogate time series, in order to test the presence of nonlinear dynamics in potentially nonstationary signals. The method is based on fitting a TV autoregressive (AR) model to the original series and then regressing the model coefficients with random replacements of the model residuals to generate TV AR surrogate series. The proposed surrogate series were used in combination with a TV sample entropy (SE) discriminating statistic to assess nonlinearity in both simulated and experimental time series, in comparison with traditional time-invariant (TIV) surrogates combined with the TIV SE discriminating statistic. Analysis of simulated time series showed that using TIV surrogates, linear nonstationary time series may be erroneously regarded as nonlinear and weak TV nonlinearities may remain unrevealed, while the use of TV AR surrogates markedly increases the probability of a correct interpretation. Application to short (500 beats) heart rate variability (HRV) time series recorded at rest (R), after head-up tilt (T), and during paced breathing (PB) showed: 1) modifications of the SE statistic that were well interpretable with the known cardiovascular physiology; 2) significant contribution of nonlinear dynamics to HRV in all conditions, with significant increase during PB at 0.2 Hz respiration rate; and 3) a disagreement between TV AR surrogates and TIV surrogates in about a quarter of the series, suggesting that nonstationarity may affect HRV recordings and bias the outcome of the traditional surrogate-based nonlinearity test.
He, Fei; Wei, Hua-Liang; Billings, Stephen A.
2015-08-01
This paper introduces a new approach for nonlinear and non-stationary (time-varying) system identification based on time-varying nonlinear autoregressive moving average with exogenous variable (TV-NARMAX) models. The challenging model structure selection and parameter tracking problems are solved by combining a multiwavelet basis function expansion of the time-varying parameters with an orthogonal least squares algorithm. Numerical examples demonstrate that the proposed approach can track rapid time-varying effects in nonlinear systems more accurately than the standard recursive algorithms. Based on the identified time domain model, a new frequency domain analysis approach is introduced based on a time-varying generalised frequency response function (TV-GFRF) concept, which enables the analysis of nonlinear, non-stationary systems in the frequency domain. Features in the TV-GFRFs which depend on the TV-NARMAX model structure and time-varying parameters are investigated. It is shown that the high-dimensional frequency features can be visualised in a low-dimensional time-frequency space.
Meerson, Baruch; Fouxon, Itzhak; Vilenkin, Arkady
2008-02-01
We employ hydrodynamic equations to investigate nonstationary channel flows of freely cooling dilute gases of hard and smooth spheres with nearly elastic particle collisions. This work focuses on the regime where the sound travel time through the channel is much shorter than the characteristic cooling time of the gas. As a result, the gas pressure rapidly becomes almost homogeneous, while the typical Mach number of the flow drops well below unity. Eliminating the acoustic modes and employing Lagrangian coordinates, we reduce the hydrodynamic equations to a single nonlinear and nonlocal equation of a reaction-diffusion type. This equation describes a broad class of channel flows and, in particular, can follow the development of the clustering instability from a weakly perturbed homogeneous cooling state to strongly nonlinear states. If the heat diffusion is neglected, the reduced equation becomes exactly soluble, and the solution develops a finite-time density blowup. The blowup has the same local features at singularity as those exhibited by the recently found family of exact solutions of the full set of ideal hydrodynamic equations [I. Fouxon, Phys. Rev. E 75, 050301(R) (2007); I. Fouxon,Phys. Fluids 19, 093303 (2007)]. The heat diffusion, however, always becomes important near the attempted singularity. It arrests the density blowup and brings about previously unknown inhomogeneous cooling states (ICSs) of the gas, where the pressure continues to decay with time, while the density profile becomes time-independent. The ICSs represent exact solutions of the full set of granular hydrodynamic equations. Both the density profile of an ICS and the characteristic relaxation time toward it are determined by a single dimensionless parameter L that describes the relative role of the inelastic energy loss and heat diffusion. At L>1 the intermediate cooling dynamics proceeds as a competition between "holes": low-density regions of the gas. This competition resembles Ostwald
Modelling non-stationary dynamic gene regulatory processes with the BGM model
Grzegorczyk, Marco; Husmeier, Dirk; Rahnenfuehrer, Joerg
2011-01-01
Recently, a Bayesian network model for inferring non-stationary regulatory processes from gene expression time series has been proposed. The Bayesian Gaussian Mixture (BGM) Bayesian network model divides the data into disjunct compartments (data subsets) by a free allocation model, and infers networ
A two dimensional power spectral estimate for some nonstationary processes. M.S. Thesis
Smith, Gregory L.
1989-01-01
A two dimensional estimate for the power spectral density of a nonstationary process is being developed. The estimate will be applied to helicopter noise data which is clearly nonstationary. The acoustic pressure from the isolated main rotor and isolated tail rotor is known to be periodically correlated (PC) and the combined noise from the main and tail rotors is assumed to be correlation autoregressive (CAR). The results of this nonstationary analysis will be compared with the current method of assuming that the data is stationary and analyzing it as such. Another method of analysis is to introduce a random phase shift into the data as shown by Papoulis to produce a time history which can then be accurately modeled as stationary. This method will also be investigated for the helicopter data. A method used to determine the period of a PC process when the period is not know is discussed. The period of a PC process must be known in order to produce an accurate spectral representation for the process. The spectral estimate is developed. The bias and variability of the estimate are also discussed. Finally, the current method for analyzing nonstationary data is compared to that of using a two dimensional spectral representation. In addition, the method of phase shifting the data is examined.
Matérn-based nonstationary cross-covariance models for global processes
Jun, Mikyoung
2014-07-01
Many spatial processes in environmental applications, such as climate variables and climate model errors on a global scale, exhibit complex nonstationary dependence structure, in not only their marginal covariance but also their cross-covariance. Flexible cross-covariance models for processes on a global scale are critical for an accurate description of each spatial process as well as the cross-dependences between them and also for improved predictions. We propose various ways to produce cross-covariance models, based on the Matérn covariance model class, that are suitable for describing prominent nonstationary characteristics of the global processes. In particular, we seek nonstationary versions of Matérn covariance models whose smoothness parameters vary over space, coupled with a differential operators approach for modeling large-scale nonstationarity. We compare their performance to the performance of some existing models in terms of the aic and spatial predictions in two applications: joint modeling of surface temperature and precipitation, and joint modeling of errors in climate model ensembles. © 2014 Elsevier Inc.
Gradient radial basis function networks for nonlinear and nonstationary time series prediction.
Chng, E S; Chen, S; Mulgrew, B
1996-01-01
We present a method of modifying the structure of radial basis function (RBF) network to work with nonstationary series that exhibit homogeneous nonstationary behavior. In the original RBF network, the hidden node's function is to sense the trajectory of the time series and to respond when there is a strong correlation between the input pattern and the hidden node's center. This type of response, however, is highly sensitive to changes in the level and trend of the time series. To counter these effects, the hidden node's function is modified to one which detects and reacts to the gradient of the series. We call this new network the gradient RBF (GRBF) model. Single and multistep predictive performance for the Mackey-Glass chaotic time series were evaluated using the classical RBF and GRBF models. The simulation results for the series without and with a tine-varying mean confirm the superior performance of the GRBF predictor over the RBF predictor.
Faster Simulation Methods for the Non-Stationary Random Vibrations of Non-Linear MDOF Systems
DEFF Research Database (Denmark)
Askar, A.; Köylüoglu, H. U.; Nielsen, Søren R. K.;
In this paper semi-analytical forward-difference Monte Carlo simulation procedures are proposed for the determination of the lower order statistics and the Joint Probability Density Function (JPDF) of the stochastic response of geometrically nonlinear multi-degree-of-freedom structural systems....... Such a treatment offers higher rates of convergence, faster speed and higher accuracy. These procedures are compared to the direct Monte Carlo simulation procedure, which uses a fourth order Runge-Kutta scheme with the white noise process approximated by a broad band Ruiz-Penzien broken line process...
Segmentation algorithm for non-stationary compound Poisson processes
Toth, Bence; Farmer, J Doyne
2010-01-01
We introduce an algorithm for the segmentation of a class of regime switching processes. The segmentation algorithm is a non parametric statistical method able to identify the regimes (patches) of the time series. The process is composed of consecutive patches of variable length, each patch being described by a stationary compound Poisson process, i.e. a Poisson process where each count is associated to a fluctuating signal. The parameters of the process are different in each patch and therefore the time series is non stationary. Our method is a generalization of the algorithm introduced by Bernaola-Galvan, et al., Phys. Rev. Lett., 87, 168105 (2001). We show that the new algorithm outperforms the original one for regime switching compound Poisson processes. As an application we use the algorithm to segment the time series of the inventory of market members of the London Stock Exchange and we observe that our method finds almost three times more patches than the original one.
Modeling of non-stationary autoregressive alpha-stable processe
National Aeronautics and Space Administration — In the literature, impulsive signals are mostly modeled by symmetric alpha-stable processes. To represent their temporal dependencies, usually autoregressive models...
Distinguishing Stationary/Nonstationary Scaling Processes Using Wavelet Tsallis q-Entropies
Directory of Open Access Journals (Sweden)
Julio Ramirez Pacheco
2012-01-01
Full Text Available Classification of processes as stationary or nonstationary has been recognized as an important and unresolved problem in the analysis of scaling signals. Stationarity or nonstationarity determines not only the form of autocorrelations and moments but also the selection of estimators. In this paper, a methodology for classifying scaling processes as stationary or nonstationary is proposed. The method is based on wavelet Tsallis q-entropies and particularly on the behaviour of these entropies for scaling signals. It is demonstrated that the observed wavelet Tsallis q-entropies of 1/f signals can be modeled by sum-cosh apodizing functions which allocates constant entropies to a set of scaling signals and varying entropies to the rest and that this allocation is controlled by q. The proposed methodology, therefore, differentiates stationary signals from non-stationary ones based on the observed wavelet Tsallis entropies for 1/f signals. Experimental studies using synthesized signals confirm that the proposed method not only achieves satisfactorily classifications but also outperforms current methods proposed in the literature.
Nonstationary random acoustic and electromagnetic fields as wave diffusion processes
Arnaut, L R
2007-01-01
We investigate the effects of relatively rapid variations of the boundaries of an overmoded cavity on the stochastic properties of its interior acoustic or electromagnetic field. For quasi-static variations, this field can be represented as an ideal incoherent and statistically homogeneous isotropic random scalar or vector field, respectively. A physical model is constructed showing that the field dynamics can be characterized as a generalized diffusion process. The Langevin--It\\^{o} and Fokker--Planck equations are derived and their associated statistics and distributions for the complex analytic field, its magnitude and energy density are computed. The energy diffusion parameter is found to be proportional to the square of the ratio of the standard deviation of the source field to the characteristic time constant of the dynamic process, but is independent of the initial energy density, to first order. The energy drift vanishes in the asymptotic limit. The time-energy probability distribution is in general n...
DEFF Research Database (Denmark)
Köylüoglu, H. U.; Nielsen, Søren R. K.; Cakmak, A. S.
Geometrically non-linear multi-degree-of-freedom (MDOF) systems subject to random excitation are considered. New semi-analytical approximate forward difference equations for the lower order non-stationary statistical moments of the response are derived from the stochastic differential equations...... of motion, and, the accuracy of these equations is numerically investigated. For stationary excitations, the proposed method computes the stationary statistical moments of the response from the solution of non-linear algebraic equations....
Goychuk, I
2001-08-01
Stochastic resonance in a simple model of information transfer is studied for sensory neurons and ensembles of ion channels. An exact expression for the information gain is obtained for the Poisson process with the signal-modulated spiking rate. This result allows one to generalize the conventional stochastic resonance (SR) problem (with periodic input signal) to the arbitrary signals of finite duration (nonstationary SR). Moreover, in the case of a periodic signal, the rate of information gain is compared with the conventional signal-to-noise ratio. The paper establishes the general nonequivalence between both measures notwithstanding their apparent similarity in the limit of weak signals.
Goychuk, Igor
2001-08-01
Stochastic resonance in a simple model of information transfer is studied for sensory neurons and ensembles of ion channels. An exact expression for the information gain is obtained for the Poisson process with the signal-modulated spiking rate. This result allows one to generalize the conventional stochastic resonance (SR) problem (with periodic input signal) to the arbitrary signals of finite duration (nonstationary SR). Moreover, in the case of a periodic signal, the rate of information gain is compared with the conventional signal-to-noise ratio. The paper establishes the general nonequivalence between both measures notwithstanding their apparent similarity in the limit of weak signals.
Directory of Open Access Journals (Sweden)
A. V. Aliev
2015-01-01
Full Text Available The paper considers the two approach-based techniques for calculating the non-stationary intra-chamber processes in solid-propellant rocket engine (SPRE. The first approach assumes that the combustion products are a mechanical mix while the other one supposes it to be the mix, which is in chemical equilibrium. To enhance reliability of solution of the intra ballistic tasks, which assume a chemical equilibrium of combustion products, the computing algorithms to calculate a structure of the combustion products are changed. The algorithm for solving a system of the nonlinear equations of chemical equilibrium, when determining the iterative amendments, uses the orthogonal QR method instead of a method of Gauss. Besides, a possibility to apply genetic algorithms in a task about a structure of combustion products is considered.It is shown that in the tasks concerning the prediction of non-stationary intra ballistic characteristics in a solid propellant rocket engine, application of models of mechanical mix and chemically equilibrium structure of combustion products leads to qualitatively and quantitatively coinciding results. The maximum difference in parameters is 5-10%, at most. In tasks concerning the starting operation of a solid sustainer engine with high-temperature products of combustion difference in results is more essential, and can reach 20% and more.A technique to calculate the intra ballistic parameters, in which flotation of combustion products is considered in the light of a spatial statement, requires using the high-performance computer facilities. For these tasks it is offered to define structure of products of combustion and its thermo-physical characteristics, using the polynoms coefficients of which should be predefined.
Liepmann, H. W.; Torczynski, J. R.
1983-01-01
Second sound techniques were used to study superfluid helium. Second sound shock waves produced relative velocities in the bulk fluid. Maximum counterflow velocities produced in this way are found to follow the Langer-Fischer prediction for the fundamental critical velocity in its functional dependence on temperature and pressure. Comparison of successive shock and rotating experiments provides strong evidence that breakdown results in vorticity production in the flow behind the shock. Schlieren pictures have verified the planar nature of second sound shocks even after multiple reflections. The nonlinear theory of second sound was repeatedly verified in its prediction of double shocks and other nonlinear phenomena.
A hybrid AR-EMD-SVR model for the short-term prediction of nonlinear and non-stationary ship motion
Institute of Scientific and Technical Information of China (English)
Wen-yang DUAN; Li-min HUANG; Yang HAN; Ya-hui ZHANG; Shuo HUANG
2015-01-01
题目：用于非线性非平稳船舶运动极短期预报的一种复合自回归经验模态分解支持向量机回归模型 目的：基于支持向量机回归（SVR）模型在非线时间序列的预测能力及经验模态分解（EMD）方法在处理非线性非平稳性的优势，提出一种复合自回归经验模态分解支持向量机回归（AR-EMD-SVR）模型，提高非线性非平稳船舶运动极短期预报精度。 创新点：1.研究非线性非平稳船舶运动的极短期预报问题，提出一种复合的预报方法；2.基于不同层次的预报模型和模型试验数据，分析非线性非平稳性对极短期预报精度的影响。 方法：1.在SVR模型中引入基于自回归（AR）预报端点延拓的 EMD 方法，形成复合的 AR-EMD-SVR 预报模型；2.基于集装箱船模水池试验运动数据将 AR-EMD-SVR 模型与 AR、SVR 和EMD-AR 三种模型进行比较，分析非线性非平稳性对极短期预报的影响以及不同模型的预报性能。 结论：1. AR-EMD 方法能够有效的克服非平稳对极短期预报模型（AR和 SVR）在精度上所带来的不良影响；2.基于船模试验数据的预报结果表明：相较于 AR、SVR 和 EMD-AR 三种预报模型，基于 AR-EMD-SVR模型的非线性非平稳船舶运动极短期预报结果具有更高的精度。%Accurate and reliable short-term prediction of ship motions offers improvements in both safety and control quality in ship motion sensitive maritime operations. Inspired by the satisfactory nonlinear learning capability of a support vector re-gression (SVR) model and the strong non-stationary processing ability of empirical mode decomposition (EMD), this paper develops a hybrid autoregressive (AR)-EMD-SVR model for the short-term forecast of nonlinear and non-stationary ship motion. The proposed hybrid model is designed by coupling the SVR model with an AR-EMD technique, which employs an AR model in ends
Electronic excitation energy transfer and nonstationary processes in KH2PO4:Tl crystals
Ogorodnikov, I. N.; Pustovarov, V. A.
2017-04-01
We report the results of our experimental study and numerical simulation of the electronic excitation energy transfer to impurity centers under conditions where nonstationary processes take place in the hydrogen sublattice of potassium dihydrogen phosphate (KH2PO4) single crystals doped with mercury-like Tl+ ions (KDP:Tl). We present the experimental results of our investigation of the decay kinetics of the transient optical absorption (100 ns-50 s) of intrinsic defects in the hydrogen sublattice of KDP:Tl obtained by pulsed absorption spectroscopy and the results of our study of the dynamics of the change in steady-state luminescence intensity with irradiation time (1-5000 s). To explain the transfer of the energy being released during electron recombination involving intrinsic KDP:Tl lattice defects, we formulate a mathematical model for the transfer of this energy to impurity Tl+ luminescence centers. Within the model being developed, we present the systems of differential balance equations describing the nonstationary processes in the electron subsystem and the hydrogen sublattice; provide a technique for calculating the pair correlation functions Y( r, t) of dissimilar defects based on the solution of the Smoluchowski equation for the system of mobile hydrogen sublattice defects; calculate the time-dependent reaction rate constants K( t) for various experimental conditions; and outline the peculiarities and results of the model parametrization based on our experimental data. Based on our investigation, the dramatic and significant effect of a gradual inertial increase by a factor of 50-100 in steady-state luminescence intensity in the 4.5-eV band in KDP:Tl crystals due to the luminescence of mercury-like Tl+ ions has been explained qualitatively and quantitatively.
Energy Technology Data Exchange (ETDEWEB)
Caceres, Manuel O [Abdus Salam International Centre for Theoretical Physics, Strada Costiera, 11-34014 Trieste (Italy); Lobos, Alejandro M [Centro Atomico Bariloche, Instituto Balseiro, CNEA, Universidad Nacional de Cuyo, and CONICET, Av E Bustillo Km 9.5, 8400 Bariloche (Argentina)
2006-02-17
We present an eigenvalue theory to study the stochastic dynamics of non-stationary time-periodic Markov processes. The analysis is carried out by solving an integral operator of the Fredholm type, i.e. considering complex-valued functions fulfilling the Kolmogorov compatibility condition. We show that the asymptotic behaviour of the stochastic process is characterized by the smaller time-scale associated with the spectrum of the Kolmogorov operator. The presence of time-periodic elements in the evolution equation for the semigroup leads to a Floquet analysis. The first non-trivial Kolmogorov's eigenvalue is interpreted from a physical point of view. This non-trivial characteristic time-scale strongly depends on the interplay between the stochastic behaviour of the process and the time-periodic structure of the Fokker-Planck equation for continuous processes, or the periodically modulated master equation for discrete Markov processes. We present pedagogical examples in a finite-dimensional vector space to calculate the Kolmogorov characteristic time-scale for discrete Markov processes.
Solving nonlinear nonstationary problem of heat-conductivity by finite element method
Directory of Open Access Journals (Sweden)
Антон Янович Карвацький
2016-11-01
Full Text Available Methodology and effective solving algorithm of non-linear dynamic problems of thermal and electric conductivity with significant temperature dependence of thermal and physical properties are given on the basis of finite element method (FEM and Newton linearization method. Discrete equations system FEM was obtained with the use of Galerkin method, where the main function is the finite element form function. The methodology based on successive solving problems of thermal and electrical conductivity has been examined in the work in order to minimize the requirements for calculating resources (RAM. in particular. Having used Mathcad software original programming code was developed to solve the given problem. After investigation of the received results, comparative analyses of accurate solution data and results of numerical solutions, obtained with the use of Matlab programming products, was held. The geometry of one fourth part of the finite sized cylinder was used to test the given numerical model. The discretization of the calculation part was fulfilled using the open programming software for automated Gmsh nets with tetrahedral units, while ParaView, which is an open programming code as well, was used to visualize the calculation results. It was found out that the maximum value violation of potential and temperature determination doesn`t exceed 0,2-0,83% in the given work according to the problem conditions
Faster Simulation Methods for the Nonstationary Random Vibrations of Non-linear MDOF Systems
DEFF Research Database (Denmark)
Askar, A.; Köylüo, U.; Nielsen, Søren R.K.
1996-01-01
. Such a treatment offers higher rates of convergence, faster speed and higher accuracy. These procedures are compared to the direct Monte Carlo simulation procedure, which uses a fourth order Runge-Kutta scheme with the white noise process approximated by a broad band Ruiz-Penzien broken line process...
Faster Simulation Methods for the Non-Stationary Random Vibrations of Non-Linear MDOF Systems
DEFF Research Database (Denmark)
Askar, A.; Köylüoglu, H. U.; Nielsen, Søren R. K.
. Such a treatment offers higher rates of convergence, faster speed and higher accuracy. These procedures are compared to the direct Monte Carlo simulation procedure, which uses a fourth order Runge-Kutta scheme with the white noise process approximated by a broad band Ruiz-Penzien broken line process...
Das, Moumita; Bhattacharya, Sourabh
2014-01-01
In this paper, using kernel convolution of order based dependent Dirichlet process (Griffin & Steel (2006)) we construct a nonstationary, nonseparable, nonparametric space-time process, which, as we show, satisfies desirable properties, and includes the stationary, separable, parametric processes as special cases. We also investigate the smoothness properties of our proposed model. Since our model entails an infinite random series, for Bayesian model fitting purpose we must either truncate th...
Speech Detection in Non-Stationary Noise Based on the 1/f Process
Institute of Scientific and Technical Information of China (English)
WANG Fan(王帆); ZHENG Fang(郑方); WUWenhx (吴文虎)
2002-01-01
In this paper, an effective and robust active speech detection method is proposed based on the 1/f process technique for signals under non-stationary noisy environments.The Gaussian 1/f process, a mathematical model for statistically self-similar random processes based on fractals, is selected to model both the speech and the background noise. An optimal Bayesian two-class classifier is developed to discriminate them by their 1/f wavelet coefficients with Karhunen-Loeve-type properties. Multiple templates are trained for the speech signal, and the parameters of the background noise can be dynamically adapted in runtime to model the variation of both the speech and the noise. In our experiments, a 10-minute long speech with different types of noises ranging from 20dB to 5dB is tested using this new detection method.A high performance with over 90% detection accuracy is achieved when average SNR is about 10dB.
Li, Chuan; Wang, Linghua; Su, Wei; Fang, Cheng
2014-01-01
We present a study of the waiting time distributions (WTDs) of solar energetic particle (SEP) events observed with the spacecraft $WIND$ and $GOES$. Both the WTDs of solar electron events (SEEs) and solar proton events (SPEs) display a power-law tail $\\sim \\Delta t^{-\\gamma}$. The SEEs display a broken power-law WTD. The power-law index is $\\gamma_{1} =$ 0.99 for the short waiting times ($$100 hours). The break of the WTD of SEEs is probably due to the modulation of the corotating interaction regions (CIRs). The power-law index $\\gamma \\sim$ 1.82 is derived for the WTD of SPEs that is consistent with the WTD of type II radio bursts, indicating a close relationship between the shock wave and the production of energetic protons. The WTDs of SEP events can be modeled with a non-stationary Poisson process which was proposed to understand the waiting time statistics of solar flares (Wheatland 2000; Aschwanden $\\&$ McTiernan 2010). We generalize the method and find that, if the SEP event rate $\\lambda = 1/\\Delt...
Institute of Scientific and Technical Information of China (English)
Chen Yu-Dong; Li Li; Zhang Yi; Hu Jian-Ming
2009-01-01
In the study of complex networks(systems),the scaling phenomenon of flow fluctuations rears to a certain power law between the mean flux(activity)(Fi)of the i-th node and its variance σi as σi ∝((Fi)α.Such scaling laws are found to be prevalent both in natural and man-made network systems,but the understanding of their origins still remains limited.This paper proposes a non-stationary Poisson process model to give an analytical explanation of the non-universal scaling phenomenon:the exponent α varies between 1/2 and 1 depending on the size of sampling time window and the relative strength of the external/internal driven forces of the systems.The crossover behaviour and the relation of fluctuation scaling with pseudo long range dependence are also accounted for by the model.Numerical experiments show that the proposed model can recover the multi-scaling phenomenon.
Franco, Glaura C.; Reisen, Valderio A.
2007-03-01
This paper deals with different bootstrap approaches and bootstrap confidence intervals in the fractionally autoregressive moving average (ARFIMA(p,d,q)) process [J. Hosking, Fractional differencing, Biometrika 68(1) (1981) 165-175] using parametric and semi-parametric estimation techniques for the memory parameter d. The bootstrap procedures considered are: the classical bootstrap in the residuals of the fitted model [B. Efron, R. Tibshirani, An Introduction to the Bootstrap, Chapman and Hall, New York, 1993], the bootstrap in the spectral density function [E. Paparoditis, D.N Politis, The local bootstrap for periodogram statistics. J. Time Ser. Anal. 20(2) (1999) 193-222], the bootstrap in the residuals resulting from the regression equation of the semi-parametric estimators [G.C Franco, V.A Reisen, Bootstrap techniques in semiparametric estimation methods for ARFIMA models: a comparison study, Comput. Statist. 19 (2004) 243-259] and the Sieve bootstrap [P. Bühlmann, Sieve bootstrap for time series, Bernoulli 3 (1997) 123-148]. The performance of these procedures and confidence intervals for d in the stationary and non-stationary ranges are empirically obtained through Monte Carlo experiments. The bootstrap confidence intervals here proposed are alternative procedures with some accuracy to obtain confidence intervals for d.
Learning dynamics from nonstationary time series: Analysis of electroencephalograms
Gribkov, Dmitrii; Gribkova, Valentina
2000-06-01
We propose an empirical modeling technique for a nonstationary time series analysis. Proposed methods include a high-dimensional (N>3) dynamical model construction in the form of delay differential equations, a nonparametric method of respective time delay calculation, the detection of quasistationary regions of the process by reccurence analysis in the space of model coefficients, and final fitting of the model to quasistationary segments of observed time series. We also demonstrate the effectiveness of our approach for nonstationary signal classification in the space of model coefficients. Applying the empirical modeling technique to electroencephalogram (EEG) records analysis, we find evidence of high-dimensional nonlinear dynamics in quasistationary EEG segments. Reccurence analysis of model parameters reveals long-term correlations in nonstationary EEG records. Using the dynamical model as a nonlinear filter, we find that different emotional states of subjects can be clearly distinguished in the space of model coefficients.
A high-frequency kriging approach for non-stationary environmental processes
Energy Technology Data Exchange (ETDEWEB)
Fuentes, M. [North Carolina State Univ., Raleigh, NC (United States). Dept. of Statistics
2001-07-01
Emission reductions were mandated in the Clean Air Act Amendments of 1990 with the expectation that they would result in major reductions in the concentrations of atmospherically transported pollutants. The emission reductions are intended to reduce public health risks and to protect sensitive ecosystems. To determine whether the emission reductions are having the intended effect on atmospheric concentrations, monitoring data must be analyzed taking into consideration the spatial structure shown by the data. Maps of pollutant concentrations and fluxes are useful over different geopolitical boundaries, to discover when, where, and to what extent the U.S. Nation's air quality is improving or declining. Since the spatial covariance structure shown by the data changes with location, the standard kriging methodology for spatial interpolation cannot be used because it assumes stationarity of the process. We present a new methodology for spatial interpolation of non-stationary processes. In this method the field is represented locally as a stationary isotropic random field, but the parameters of the stationary random field are allowed to vary across space. A procedure for interpolation is presented that uses an expression for the spectral density at high frequencies. New fitting algorithms are developed using spectral approaches. In cases where the data are distributed exactly or approximately on a lattice, it is argued that spectral approaches have potentially enormous computational benefits compared with maximum likelihood. The methods are extended to interpolation questions using approximate Bayesian approaches to account for parameter uncertainty. We develop applications to obtain the total loading of pollutant concentrations and fluxes over different geo-political boundaries. (author)
CMOS Nonlinear Signal Processing Circuits
2010-01-01
The chapter describes various nonlinear signal processing CMOS circuits, including a high reliable WTA/LTA, simple MED cell, and low-voltage arbitrary order extractor. We focus the discussion on CMOS analog circuit design with reliable, programmable capability, and low voltage operation. It is a practical problem when the multiple identical cells are required to match and realized within a single chip using a conventional process. Thus, the design of high-reliable circuit is indeed needed. Th...
Directory of Open Access Journals (Sweden)
Alexey M. Lipanov
1997-10-01
Full Text Available In this paper, the laws of the unstable wave processes accompanying the combustion abnormal mode in the large-sized solid propellant rocket motor {SPRM pyrotechnical ignition system {IS are investigated by numerical method. The IS contains the main {cylindrical channel (MC having uniform perforation over the lateral surface, The left MC boundary is blocked and the right boundary is uniformly perforated. The whole perforation is hermetically sealed from outside. The additional {cylindrical channel {AC {an initial impulse amplifier with uniform perforation over the lateral surface is installed into the MC cavity, coaxially to MC. The right AC boundary is blocked, and the time-varying high-temperature gas flow, containing incandescent 'particles is supplied from initiator, equipped with a fast burning compound, through AC left perforated boundary. To imitate the exploitation conditions, the IS is placed in cylindrical imitation chamber {imitative SPRM. In a number of cases, before the beginning of the IS operation, a situation can be realised when the pelletised solid propellant {PSP mass is non-uniformly distributed along the IS AC length, and the greater part of the AC lateral perforation is blocked by the PSP inserted in the IS MC. Under these conditions, the effect of abnormal strengthening of the pressure waves at the AC boundaries is possible. For describing the abnormal nonstationary physico-chemical processes, a mathematical model is developed. For the check-up of this complex model, the numerical calculation results have been compared with the results of the fire stand tests for the regular IS and the engine. The numerical analysis of the unstable wave process development in the AC has shown that the rise of the pressure with an ever increasing amplitude is realised at the moment, when a shock wave reflects alternately, on the left and on the right AC boundaries. The effect of the pressure waves' abnormal strengthening can result in the
Dynamics of non-stationary processes that follow the maximum of the Rényi entropy principle.
Shalymov, Dmitry S; Fradkov, Alexander L
2016-01-01
We propose dynamics equations which describe the behaviour of non-stationary processes that follow the maximum Rényi entropy principle. The equations are derived on the basis of the speed-gradient principle originated in the control theory. The maximum of the Rényi entropy principle is analysed for discrete and continuous cases, and both a discrete random variable and probability density function (PDF) are used. We consider mass conservation and energy conservation constraints and demonstrate the uniqueness of the limit distribution and asymptotic convergence of the PDF for both cases. The coincidence of the limit distribution of the proposed equations with the Rényi distribution is examined.
Fu, Zening; Chan, Shing-Chow; Di, Xin; Biswal, Bharat; Zhang, Zhiguo
2014-04-01
Time-varying covariance is an important metric to measure the statistical dependence between non-stationary biological processes. Time-varying covariance is conventionally estimated from short-time data segments within a window having a certain bandwidth, but it is difficult to choose an appropriate bandwidth to estimate covariance with different degrees of non-stationarity. This paper introduces a local polynomial regression (LPR) method to estimate time-varying covariance and performs an asymptotic analysis of the LPR covariance estimator to show that both the estimation bias and variance are functions of the bandwidth and there exists an optimal bandwidth to minimize the mean square error (MSE) locally. A data-driven variable bandwidth selection method, namely the intersection of confidence intervals (ICI), is adopted in LPR for adaptively determining the local optimal bandwidth that minimizes the MSE. Experimental results on simulated signals show that the LPR-ICI method can achieve robust and reliable performance in estimating time-varying covariance with different degrees of variations and under different noise scenarios, making it a powerful tool to study the dynamic relationship between non-stationary biomedical signals. Further, we apply the LPR-ICI method to estimate time-varying covariance of functional magnetic resonance imaging (fMRI) signals in a visual task for the inference of dynamic functional brain connectivity. The results show that the LPR-ICI method can effectively capture the transient connectivity patterns from fMRI.
Nonlinear filtering for LIDAR signal processing
Directory of Open Access Journals (Sweden)
D. G. Lainiotis
1996-01-01
Full Text Available LIDAR (Laser Integrated Radar is an engineering problem of great practical importance in environmental monitoring sciences. Signal processing for LIDAR applications involves highly nonlinear models and consequently nonlinear filtering. Optimal nonlinear filters, however, are practically unrealizable. In this paper, the Lainiotis's multi-model partitioning methodology and the related approximate but effective nonlinear filtering algorithms are reviewed and applied to LIDAR signal processing. Extensive simulation and performance evaluation of the multi-model partitioning approach and its application to LIDAR signal processing shows that the nonlinear partitioning methods are very effective and significantly superior to the nonlinear extended Kalman filter (EKF, which has been the standard nonlinear filter in past engineering applications.
Multiorder nonlinear diffraction in frequency doubling processes
DEFF Research Database (Denmark)
Saltiel, Solomon M.; Neshev, Dragomir N.; Krolikowski, Wieslaw
2009-01-01
We analyze experimentally light scattering from 2 nonlinear gratings and observe two types of second-harmonic frequency-scattering processes. The first process is identified as Raman–Nath type nonlinear diffraction that is explained by applying only transverse phase-matching conditions. The angular...... position of this type of diffraction is defined by the ratio of the second-harmonic wavelength and the grating period. In contrast, the second type of nonlinear scattering process is explained by the longitudinal phase matching only, being insensitive to the nonlinear grating...
Digital signal processing for fiber nonlinearities [Invited
DEFF Research Database (Denmark)
Cartledge, John C.; Guiomar, Fernando P.; Kschischang, Frank R.
2017-01-01
This paper reviews digital signal processing techniques that compensate, mitigate, and exploit fiber nonlinearities in coherent optical fiber transmission systems......This paper reviews digital signal processing techniques that compensate, mitigate, and exploit fiber nonlinearities in coherent optical fiber transmission systems...
Young, Hsu-Wen Vincent; Hsu, Ke-Hsin; Pham, Van-Truong; Tran, Thi-Thao; Lo, Men-Tzung
2017-09-01
A new method for signal decomposition is proposed and tested. Based on self-consistent nonlinear wave equations with self-sustaining physical mechanisms in mind, the new method is adaptive and particularly effective for dealing with synthetic signals consisting of components of multiple time scales. By formulating the method into an optimization problem and developing the corresponding algorithm and tool, we have proved its usefulness not only for analyzing simulated signals, but, more importantly, also for real clinical data.
Azemi, Ghasem; Boubchir, Larbi; Boashash, B
2003-01-01
This article presents a general methodology for processing non-stationary signals for the purpose of classification and localization. The methodology combines methods adapted from three complementary areas: time-frequency signal analysis, multichannel signal analysis and image processing. The latter three combine in a new methodology referred to as multichannel time-frequency image processing which is applied to the problem of classifying electroencephalogram (EEG) abnormalities in both adult...
Kerr, Thomas H., III
2001-11-01
We alert the reader here to an apparent vulnerability in recent adaptive antenna processing that claims increased GPS jammer resistance via use of lucrative new approaches to adaptive beamforming and/or null-steering, but unfortunately, presumes only simplistic unsophisticated wideband barrage WGN jammers as threats. When jammers are less cooperative by being statistically non-stationary (e.g., by exhibiting time-varying means or biases, by being synchronized blinking jammer pairs, or by varying the total power output with time), then statistics on the jammers can apparently no longer be successfully extracted fro the time-averages (even in post-processing mode using long blocks of received data that was saved) because ergodicity of the underlying intermediate covariance estimate is lost. This unpleasant situation arises or exists for abstracted, idealized STAP or SLC algorithms making use of the, by now, familiar fundamental STAP-related equation: R-1υ, where this necessary intermediate covariance estimate R=R1+R2+R3 has the three indicated constituent components due to thermal/environmental noise, clutter, and jammers, respectively. Without an ability to accurately estimate R3, the appropriate jammer nullings apparently can no longer be activated successfully. Such systems susceptible to jamming can be revealed by in-situ tests with simple equipment. Topics herein include updates to PRN generation, updates to statistical tests in general and to CLT in particular and all three updates being new to most engineers.
Input saturation in nonlinear multivariable processes resolved by nonlinear decoupling
Directory of Open Access Journals (Sweden)
Jens G. Balchen
1995-04-01
Full Text Available A new method is presented for the resolution of the problem of input saturation in nonlinear multivariable process control by means of elementary nonlinear decoupling (END. Input saturation can have serious consequences particularly in multivariable control because it may lead to very undesirable system behaviour and quite often system instability. Many authors have searched for systematic techniques for designing multivariable control systems in which saturation may occur in any of the control variables (inputs, manipulated variables. No generally accepted method seems to have been presented so far which gives a solution in closed form. The method of elementary nonlinear decoupling (END can be applied directly to the case of saturation control variables by deriving as many control strategies as there are combinations of saturating control variables. The method is demonstrated by the multivariable control of a simulated Fluidized Catalytic Cracker (FCC with very convincing results.
Lo, Men-Tzung; Novak, Vera; Peng, C-K; Liu, Yanhui; Hu, Kun
2009-06-01
Phase interactions among signals of physical and physiological systems can provide useful information about the underlying control mechanisms of the systems. Physical and biological recordings are often noisy and exhibit nonstationarities that can affect the estimation of phase interactions. We systematically studied effects of nonstationarities on two phase analyses including (i) the widely used transfer function analysis (TFA) that is based on Fourier decomposition and (ii) the recently proposed multimodal pressure flow (MMPF) analysis that is based on Hilbert-Huang transform (HHT)-an advanced nonlinear decomposition algorithm. We considered three types of nonstationarities that are often presented in physical and physiological signals: (i) missing segments of data, (ii) linear and step-function trends embedded in data, and (iii) multiple chaotic oscillatory components at different frequencies in data. By generating two coupled oscillatory signals with an assigned phase shift, we quantify the change in the estimated phase shift after imposing artificial nonstationarities into the oscillatory signals. We found that all three types of nonstationarities affect the performances of the Fourier-based and the HHT-based phase analyses, introducing bias and random errors in the estimation of the phase shift between two oscillatory signals. We also provided examples of nonstationarities in real physiological data (cerebral blood flow and blood pressure) and showed how nonstationarities can complicate result interpretation. Furthermore, we propose certain strategies that can be implemented in the TFA and the MMPF methods to reduce the effects of nonstationarities, thus improving the performances of the two methods.
Golubev, Vladimir S.; Banishev, Alexander F.; Azharonok, V. V.; Zabelin, Alexandre M.
1994-09-01
A qualitative analysis of the role of some hydrodynamic flows and instabilities by the process of laser beam-metal sample deep penetration interaction is presented. The forces of vapor pressure, melt surface tension and thermocapillary forces can determined a number of oscillatory and nonstationary phenomena in keyhole and weld pool. Dynamics of keyhole formation in metal plates has been studied under laser beam pulse effect ((lambda) equals 1.06 micrometers ). Velocities of the keyhole bottom motion have been determined at 0.5 X 105 - 106 W/cm2 laser power densities. Oscillatory regime of plate break- down has been found out. Small-dimensional structures with d-(lambda) period was found on the frozen cavity walls, which, in our opinion, can contribute significantly to laser beam absorption. A new form of periodic structure on the frozen pattern being a helix-shaped modulation of the keyhole walls and bottom relief has been revealed. Temperature oscillations related to capillary oscillations in the melt layer were discovered in the cavity. Interaction of the CW CO2 laser beam and the matter by beam penetration into a moving metal sample has been studied. The pulsed and thermodynamic parameters of the surface plasma were investigated by optical and spectroscopic methods. The frequencies of plasma jets pulsations (in 10 - 105 Hz range) are related to possible melt surface instabilities of the keyhole.
Sensor Network Design for Nonlinear Processes
Institute of Scientific and Technical Information of China (English)
李博; 陈丙珍
2003-01-01
This paper presents a method to design a cost-optimal nonredundant sensor network to observe all variables in a general nonlinear process. A mixed integer linear programming model was used to minimize the cost with data classification to check the observability of all unmeasured variables. This work is a starting point for designing sensor networks for general nonlinear processes based on various criteria, such as reliability and accuracy.
Central Limit Theorem for Nonlinear Hawkes Processes
Zhu, Lingjiong
2012-01-01
Hawkes process is a self-exciting point process with clustering effect whose jump rate depends on its entire past history. It has wide applications in neuroscience, finance and many other fields. Linear Hawkes process has an immigration-birth representation and can be computed more or less explicitly. It has been extensively studied in the past and the limit theorems are well understood. On the contrary, nonlinear Hawkes process lacks the immigration-birth representation and is much harder to analyze. In this paper, we obtain a functional central limit theorem for nonlinear Hawkes process.
Institute of Scientific and Technical Information of China (English)
罗璇; 靳艳飞
2013-01-01
This paper studied the non-stationary stochastic response and the optimal control of a half-car dynamical model with nonlinear active suspension under the excitation of random road surface.Using the method of equivalent linearization,the response statistics and stochastic optimal control of the nonlinear suspension were obtained.The comparison and analysis of the non-stationary response of active and passive suspension show that the nonlinear active suspension is better than the passive suspension.Finally,the accuracy of the equivalent linearization technique was verified by Monte Carlo simulation.%研究了1/2车非线性悬架模型在路面随机激励下的非平稳振动响应,并基于随机最优控制理论对其进行主动控制.首先利用等效线性化方法将具有非线性阻尼及迟滞刚度的非线性悬架模型线性化,然后将主动、被动悬架非平稳随机响应进行比较,结果表明非线性主动悬架的性能要优于被动悬架.最后,通过Monte-Carlo数值模拟验证了理论结果.
Computational homogenization of non-stationary transport processes in masonry structures
Sykora, J; Kruis, J; Sejnoha, M
2011-01-01
A fully coupled transient heat and moisture transport in a masonry structure is examined in this paper. Supported by several successful applications in civil engineering the nonlinear diffusion model proposed by K\\"{u}nzel is adopted in the present study. A strong material heterogeneity together with a significant dependence of the model parameters on initial conditions as well as the gradients of heat and moisture fields vindicates the use of a hierarchical modeling strategy to solve the problem of this kind. Attention is limited to the classical first order homogenization in a spatial domain developed here in the framework of a two step (meso-macro) multi-scale computational scheme (FE^2 problem). Several illustrative examples are presented to investigate the influence of transient flow at the level of constituents (meso-scale) on the macroscopic response including the effect of macro-scale boundary conditions. A two-dimensional section of Charles Bridge subjected to actual climatic conditions is analyzed n...
Broadband Nonlinear Signal Processing in Silicon Nanowires
DEFF Research Database (Denmark)
Yvind, Kresten; Pu, Minhao; Hvam, Jørn Märcher;
The fast non-linearity of silicon allows Tbit/s optical signal processing. By choosing suitable dimensions of silicon nanowires their dispersion can be tailored to ensure a high nonlinearity at power levels low enough to avoid significant two-photon abso We have fabricated low insertion and propa......The fast non-linearity of silicon allows Tbit/s optical signal processing. By choosing suitable dimensions of silicon nanowires their dispersion can be tailored to ensure a high nonlinearity at power levels low enough to avoid significant two-photon abso We have fabricated low insertion...... and propagation loss silicon nanowires and use them to demonstrate the broadband capabilities of silicon....
Grzegorczyk, Marco; Husmeier, Dirk; Edwards, Kieron D.; Ghazal, Peter; Millar, Andrew J.
2008-01-01
Method: The objective of the present article is to propose and evaluate a probabilistic approach based on Bayesian networks for modelling non-homogeneous and non-linear gene regulatory processes. The method is based on a mixture model, using latent variables to assign individual measurements to diff
Grzegorczyk, Marco; Husmeier, Dirk; Edwards, Kieron D.; Ghazal, Peter; Millar, Andrew J.
2008-01-01
Method: The objective of the present article is to propose and evaluate a probabilistic approach based on Bayesian networks for modelling non-homogeneous and non-linear gene regulatory processes. The method is based on a mixture model, using latent variables to assign individual measurements to
The maximal process of nonlinear shot noise
Eliazar, Iddo; Klafter, Joseph
2009-05-01
In the nonlinear shot noise system-model shots’ statistics are governed by general Poisson processes, and shots’ decay-dynamics are governed by general nonlinear differential equations. In this research we consider a nonlinear shot noise system and explore the process tracking, along time, the system’s maximal shot magnitude. This ‘maximal process’ is a stationary Markov process following a decay-surge evolution; it is highly robust, and it is capable of displaying both a wide spectrum of statistical behaviors and a rich variety of random decay-surge sample-path trajectories. A comprehensive analysis of the maximal process is conducted, including its Markovian structure, its decay-surge structure, and its correlation structure. All results are obtained analytically and in closed-form.
Non-stationary probabilities for the asymmetric exclusion process on a ring
Indian Academy of Sciences (India)
V B Priezzhev
2005-06-01
A solution of the master equation for a system of interacting particles for finite time and particle density is presented. By using a new form of the Bethe ansatz, the totally asymmetric exclusion process on a ring is solved for arbitrary initial conditions and time intervals.
Szabo, Zoltan
2010-01-01
The goal of this paper is to extend independent subspace analysis (ISA) to the case of (i) nonparametric, not strictly stationary source dynamics and (ii) unknown source component dimensions. We make use of functional autoregressive (fAR) processes to model the temporal evolution of the hidden sources. An extension of the ISA separation principle--which states that the ISA problem can be solved by traditional independent component analysis (ICA) and clustering of the ICA elements--is derived for the solution of the defined fAR independent process analysis task (fAR-IPA): applying fAR identification we reduce the problem to ISA. A local averaging approach, the Nadaraya-Watson kernel regression technique is adapted to obtain strongly consistent fAR estimation. We extend the Amari-index to different dimensional components and illustrate the efficiency of the fAR-IPA approach by numerical examples.
A Novel Method for Generating Non-Stationary Gaussian Processes for Use in Digital Radar Simulators
2007-03-01
penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number. PLEASE DO NOT RETURN...noise generator divided by the simulation bandwidth. Thus, the simulation noise density is ( Dsim − σsim)δt, where the simulation sample time is δt...transient response of the complex system to stochastic processes. Does this hold in general? Since both responses are control by the eigenvalues, a
Analysis of Real Overvoltage Disturbances by Using Nonstationary Signal Processing Techniques
Directory of Open Access Journals (Sweden)
VUJOSEVIC, S.
2015-08-01
Full Text Available Switching surges can cause voltage conditions degradation, and this paper presents a new approach in their analysis. Besides the amplitude properties, regarding to power quality, it is important to know the structure of their harmonic spectrum. For that purpose, characteristic surges (energization and deenergization of an unloaded 35 kV underground cable, energization of an unloaded 10 kV underground cable and deenergization of a 10 kV overhead line, with a multiple appearance of the arc between the circuit breaker contacts were analyzed. The signals were obtained by an experiment, so the occurrence of noise makes them much more complex to analyze than the simulated ones. Their harmonic decomposition was performed by digital signal processing methods - Empirical Mode Decomposition and Short Time Fourier Transform. The obtained results were compared to the calculated ones, which allowed us to draw conclusions related to applied methods efficiency and characteristic harmonics values that occur during the switching surges. The performed analysis allows us to get a deeper insight into transient processes in the real transmission power lines. The obtained results can be especially useful to detect the locations of occurrence of various types of surges and for development of real-time power quality monitoring systems.
Jansen, Rob T P; Laeven, Mark; Kardol, Wim
2002-06-01
The analytical processes in clinical laboratories should be considered to be non-stationary, non-ergodic and probably non-stochastic processes. Both the process mean and the process standard deviation vary. The variation can be different at different levels of concentration. This behavior is shown in five examples of different analytical systems: alkaline phosphatase on the Hitachi 911 analyzer (Roche), vitamin B12 on the Access analyzer (Beckman), prothrombin time and activated partial thromboplastin time on the STA Compact analyzer (Roche) and PO2 on the ABL 520 analyzer (Radiometer). A model is proposed to assess the status of a process. An exponentially weighted moving average and standard deviation was used to estimate process mean and standard deviation. Process means were estimated overall and for each control level. The process standard deviation was estimated in terms of within-run standard deviation. Limits were defined in accordance with state of the art- or biological variance-derived cut-offs. The examples given are real, not simulated, data. Individual control sample results were normalized to a target value and target standard deviation. The normalized values were used in the exponentially weighted algorithm. The weighting factor was based on a process time constant, which was estimated from the period between two calibration or maintenance procedures. The proposed system was compared with Westgard rules. The Westgard rules perform well, despite the underlying presumption of ergodicity. This is mainly caused by the introduction of the starting rule of 12s, which proves essential to prevent a large number of rule violations. The probability of reporting a test result with an analytical error that exceeds the total allowable error was calculated for the proposed system as well as for the Westgard rules. The proposed method performed better. The proposed algorithm was implemented in a computer program running on computers to which the analyzers were
Ultrafast Nonlinear Signal Processing in Silicon Waveguides
DEFF Research Database (Denmark)
Oxenløwe, Leif Katsuo; Mulvad, Hans Christian Hansen; Hu, Hao;
2012-01-01
We describe recent demonstrations of exploiting highly nonlinear silicon waveguides for ultrafast optical signal processing. We describe wavelength conversion and serial-to-parallel conversion of 640 Gbit/s data signals and 1.28 Tbit/s demultiplexing and all-optical sampling.......We describe recent demonstrations of exploiting highly nonlinear silicon waveguides for ultrafast optical signal processing. We describe wavelength conversion and serial-to-parallel conversion of 640 Gbit/s data signals and 1.28 Tbit/s demultiplexing and all-optical sampling....
Non-stationary Effects In Space-charge Dominated Electron Beams
Agafonov, A V; Tarakanov, V P
2004-01-01
Problems of non-linear dynamics of space charge dominated electron beams in plane and in coaxial electron guns are discussed from the point of view of non-stationary behaviour of beams. The results of computer simulations of beam formation are presented for several simple plane diode geometries and for the gun with large compression of annular beam. Emphasised is non-stationary behaviour combined with edge and hysteresis effects. Non-stationary effects in crossed electron and magnetic field are considered from the point of view a development of schemes of intense electron beam formation for compact accelerators and RF-devices. The results of computer simulation of beam formation inside coaxial guns are described under condition of secondary self-sustaining emission. Possibilities of electron storage and capture due to transient processes are discussed. Work supported by RFBR under grant 03-02-17301.
Non-stationary dynamo & magnetospheric accretion processes of the classical T Tauri star V2129 Oph
Donati, JF; Walter, FM; Gregory, SG; Skelly, MB; Hussain, GAJ; Flaccomio, E; Argiroffi, C; Grankin, KN; Jardine, MM; Menard, F; Dougados, C; Romanova, MM
2010-01-01
We report here the first results of a multi-wavelength campaign focussing on magnetospheric accretion processes of the classical TTauri star (cTTS) V2129Oph. In this paper, we present spectropolarimetric observations collected in 2009 July with ESPaDOnS at the Canada-France-Hawaii Telescope (CFHT). Circularly polarised Zeeman signatures are clearly detected, both in photospheric absorption and accretion-powered emission lines, from time-series of which we reconstruct new maps of the magnetic field, photospheric brightness and accretion-powered emission at the surface of V2129Oph using our newest tomographic imaging tool -- to be compared with those derived from our old 2005 June data set, reanalyzed in the exact same way. We find that in 2009 July, V2129Oph hosts octupolar & dipolar field components of about 2.1 & 0.9kG respectively, both tilted by about 20deg with respect to the rotation axis; we conclude that the large-scale magnetic topology changed significantly since 2005 June (when the octupole ...
Almosallam, Ibrahim A.; Jarvis, Matt J.; Roberts, Stephen J.
2016-10-01
The next generation of cosmology experiments will be required to use photometric redshifts rather than spectroscopic redshifts. Obtaining accurate and well-characterized photometric redshift distributions is therefore critical for Euclid, the Large Synoptic Survey Telescope and the Square Kilometre Array. However, determining accurate variance predictions alongside single point estimates is crucial, as they can be used to optimize the sample of galaxies for the specific experiment (e.g. weak lensing, baryon acoustic oscillations, supernovae), trading off between completeness and reliability in the galaxy sample. The various sources of uncertainty in measurements of the photometry and redshifts put a lower bound on the accuracy that any model can hope to achieve. The intrinsic uncertainty associated with estimates is often non-uniform and input-dependent, commonly known in statistics as heteroscedastic noise. However, existing approaches are susceptible to outliers and do not take into account variance induced by non-uniform data density and in most cases require manual tuning of many parameters. In this paper, we present a Bayesian machine learning approach that jointly optimizes the model with respect to both the predictive mean and variance we refer to as Gaussian processes for photometric redshifts (GPZ). The predictive variance of the model takes into account both the variance due to data density and photometric noise. Using the Sloan Digital Sky Survey (SDSS) DR12 data, we show that our approach substantially outperforms other machine learning methods for photo-z estimation and their associated variance, such as TPZ and ANNZ2. We provide a MATLAB and PYTHON implementations that are available to download at https://github.com/OxfordML/GPz.
Parametric modelling of nonstationary platform deck motions
Digital Repository Service at National Institute of Oceanography (India)
Mandal, S.
-sense-stationary processes. Then the time series are modelled by the maximum entropy method which is formulated here for spectral estimation of platform deck displacements. The lower order maximum entropy spectra of nonstationary platform deck displacements are compared...
Chen, Yun; Yang, Hui
2016-06-01
Many real-world systems are evolving over time and exhibit dynamical behaviors. In order to cope with system complexity, sensing devices are commonly deployed to monitor system dynamics. Online sensing brings the proliferation of big data that are nonlinear and nonstationary. Although there is rich information on nonlinear dynamics, significant challenges remain in realizing the full potential of sensing data for system control. This paper presents a new approach of heterogeneous recurrence analysis for online monitoring and anomaly detection in nonlinear dynamic processes. A partition scheme, named as Q-tree indexing, is firstly introduced to delineate local recurrence regions in the multi-dimensional continuous state space. Further, we design a new fractal representation of state transitions among recurrence regions, and then develop new measures to quantify heterogeneous recurrence patterns. Finally, we develop a multivariate detection method for on-line monitoring and predictive control of process recurrences. Case studies show that the proposed approach not only captures heterogeneous recurrence patterns in the transformed space, but also provides effective online control charts to monitor and detect dynamical transitions in the underlying nonlinear processes.
Rak, Josef
2016-03-01
An induction heating problem can be described by a parabolic differential equation. For this equation, specific Joule looses must be computed. It can be done by solving the Fredholm Integral Equation of the second kind for the eddy current of density. When we use the Nyström method with the singularity subtraction, the computation time is rapidly reduced. This paper shows the method for finding non-stationary temperature distribution in the metal body with illustrative examples.
Energy Technology Data Exchange (ETDEWEB)
Wachter, E.M.
2005-07-01
The flamelet method makes it possible to separate numeric treatment of turbulence from chemical calculations in the simulation of turbulent difusion flames. The author investigated various flamelet methods. The advantages and shortcomings of stationary and nonstationary flamelet methods are compared. First, the application of the stationary flamelet method and its applicability are demonstrated for concrete examples using flamelet tables. The main part of the investigation focused on the calculation of the cheemical components using the nonstationary flamelet method combined with flow fields determined by the LES method. Using three different free jet configurations, advantages and drawbacks of chemical calculations by the nonstationary flamelet method after flow field investigation are gone into. (orig.)
Recent advances in nonlinear speech processing
Faundez-Zanuy, Marcos; Esposito, Antonietta; Cordasco, Gennaro; Drugman, Thomas; Solé-Casals, Jordi; Morabito, Francesco
2016-01-01
This book presents recent advances in nonlinear speech processing beyond nonlinear techniques. It shows that it exploits heuristic and psychological models of human interaction in order to succeed in the implementations of socially believable VUIs and applications for human health and psychological support. The book takes into account the multifunctional role of speech and what is “outside of the box” (see Björn Schuller’s foreword). To this aim, the book is organized in 6 sections, each collecting a small number of short chapters reporting advances “inside” and “outside” themes related to nonlinear speech research. The themes emphasize theoretical and practical issues for modelling socially believable speech interfaces, ranging from efforts to capture the nature of sound changes in linguistic contexts and the timing nature of speech; labors to identify and detect speech features that help in the diagnosis of psychological and neuronal disease, attempts to improve the effectiveness and performa...
Quantum Information Processing using Nonlinear Optical Effects
DEFF Research Database (Denmark)
Andersen, Lasse Mejling
of the converted idler depends on the other pump. This allows for temporal-mode-multiplexing. When the effects of nonlinear phase modulation (NPM) are included, the phases of the natural input and output modes are changed, reducing the separability. These effects are to some degree mediated by pre......This PhD thesis treats applications of nonlinear optical effects for quantum information processing. The two main applications are four-wave mixing in the form of Bragg scattering (BS) for quantum-state-preserving frequency conversion, and sum-frequency generation (SFG) in second-order nonlinear...... to obtain a 100 % conversion efficiency is to use multiple stages of frequency conversion, but this setup suffers from the combined effects of NPM. This problem is circumvented by using asymmetrically pumped BS, where one pump is continuous wave. For this setup, NPM is found to only lead to linear phase...
Directory of Open Access Journals (Sweden)
Matviychuk K.S.
2012-06-01
Full Text Available The conditions of technical stability by measure of the dynamical states of the non-stationary control systems with variable structure are investigated in presence of filtration process of the control signals. The suitable systems of the differential equations have the changing coefficients, which are altering in time and by jumplike together with jumplike changing of the control function of the process and with simultaneous jumplike changing at the direction of the suitable phase velocity vector of the process. The criteria of technical stability by measure on finite and infinite intervals of time, asymptotical technical stability by measure, and also the criterion of the technical instability by measure of given, inwardly dependent on quality of filtering of control signals of non-stationary dynamical systems with variable structure are determiner under base of the differential inequalities method at combination with properties of the class of the absolutely positive functions, for all feasible initial disturbances from the pre-assigned by measure set of initial states of the process.
Yankovskii, A. P.
2017-03-01
The nonlinear problem of non-stationary heat conductivity of the layered anisotropic heat-sensitive shells was formulated taking into account the linear dependence of thermal-physical characteristics of the materials of phase compositions on the temperature. The initial-boundary-value problem is formulated in the dimensionless form, and four small parameters are identified: thermal-physical, characterizing the degree of heat sensitivity of the layer material; geometric, characterizing the relative thickness of the thin-walled structure, and two small Biot numbers on the front surfaces of shells. A sequential recursion of dimensionless equations is carried out, at first, using the thermalphysical small parameter, then, small Biot numbers and, finally, geometrical small parameter. The first type of recursion allowed us to linearize the problem of heat conductivity, and on the basis of two latter types of recursion, the outer asymptotic expansion of solution to the problem of non-stationary heat conductivity of the layered anisotropic non-uniform shells and plates under boundary conditions of the II and III kind and small Biot numbers on the facial surfaces was built, taking into account heat sensitivity of the layer materials. The resulting two-dimensional boundary problems were analyzed, and asymptotic properties of solutions to the heat conductivity problem were studied. The physical explanation was given to some aspects of asymptotic temperature decomposition.
Internal Decoupling in Nonlinear Process Control
Directory of Open Access Journals (Sweden)
Jens G. Balchen
1988-07-01
Full Text Available A simple method has been investigated for the total or partial removal of the effect of non-linear process phenomena in multi-variable feedback control systems. The method is based upon computing the control variables which will drive the process at desired rates. It is shown that the effect of model errors in the linearization of the process can be partly removed through the use of large feedback gains. In practice there will be limits on how large gains can he used. The sensitivity to parameter errors is less pronounced and the transient behaviour is superior to that of ordinary PI controllers.
用小波实现两类非平稳过程的平稳化%Stationarizing Two Classes of Nonstationary Processes by Wavelet
Institute of Scientific and Technical Information of China (English)
唐洪敏; 谢衷洁
2004-01-01
主要讨论了两类非平稳过程小波变换后的平稳性.利用小波的局部性及暗含的差分性质,证明了在小波变换后,分数差分平稳过程和可调和周期相关过程是平稳的.%The main purpose is to discuss the stationarity of two classes of nonstationary processes after wavelet transformations.Owing to the fact that the wavelet transformation possesses localization and implicit difference property,the authors show that after wavelet transformation,the fractionally differenced process and the harmonizable periodically correlated process may be changed into stationary processes.
Robust Nonstationary Regression
1993-01-01
This paper provides a robust statistical approach to nonstationary time series regression and inference. Fully modified extensions of traditional robust statistical procedures are developed which allow for endogeneities in the nonstationary regressors and serial dependence in the shocks that drive the regressors and the errors that appear in the equation being estimated. The suggested estimators involve semiparametric corrections to accommodate these possibilities and they belong to the same ...
Processing Approach of Non-linear Adjustment Models in the Space of Non-linear Models
Institute of Scientific and Technical Information of China (English)
LI Chaokui; ZHU Qing; SONG Chengfang
2003-01-01
This paper investigates the mathematic features of non-linear models and discusses the processing way of non-linear factors which contributes to the non-linearity of a nonlinear model. On the basis of the error definition, this paper puts forward a new adjustment criterion, SGPE.Last, this paper investigates the solution of a non-linear regression model in the non-linear model space and makes the comparison between the estimated values in non-linear model space and those in linear model space.
Nonlinearly perturbed semi-Markov processes
Silvestrov, Dmitrii
2017-01-01
The book presents new methods of asymptotic analysis for nonlinearly perturbed semi-Markov processes with a finite phase space. These methods are based on special time-space screening procedures for sequential phase space reduction of semi-Markov processes combined with the systematical use of operational calculus for Laurent asymptotic expansions. Effective recurrent algorithms are composed for getting asymptotic expansions, without and with explicit upper bounds for remainders, for power moments of hitting times, stationary and conditional quasi-stationary distributions for nonlinearly perturbed semi-Markov processes. These results are illustrated by asymptotic expansions for birth-death-type semi-Markov processes, which play an important role in various applications. The book will be a useful contribution to the continuing intensive studies in the area. It is an essential reference for theoretical and applied researchers in the field of stochastic processes and their applications that will cont...
Nonlinear Process Fault Diagnosis Based on Serial Principal Component Analysis.
Deng, Xiaogang; Tian, Xuemin; Chen, Sheng; Harris, Chris J
2016-12-22
Many industrial processes contain both linear and nonlinear parts, and kernel principal component analysis (KPCA), widely used in nonlinear process monitoring, may not offer the most effective means for dealing with these nonlinear processes. This paper proposes a new hybrid linear-nonlinear statistical modeling approach for nonlinear process monitoring by closely integrating linear principal component analysis (PCA) and nonlinear KPCA using a serial model structure, which we refer to as serial PCA (SPCA). Specifically, PCA is first applied to extract PCs as linear features, and to decompose the data into the PC subspace and residual subspace (RS). Then, KPCA is performed in the RS to extract the nonlinear PCs as nonlinear features. Two monitoring statistics are constructed for fault detection, based on both the linear and nonlinear features extracted by the proposed SPCA. To effectively perform fault identification after a fault is detected, an SPCA similarity factor method is built for fault recognition, which fuses both the linear and nonlinear features. Unlike PCA and KPCA, the proposed method takes into account both linear and nonlinear PCs simultaneously, and therefore, it can better exploit the underlying process's structure to enhance fault diagnosis performance. Two case studies involving a simulated nonlinear process and the benchmark Tennessee Eastman process demonstrate that the proposed SPCA approach is more effective than the existing state-of-the-art approach based on KPCA alone, in terms of nonlinear process fault detection and identification.
Nonlinear Markov Control Processes and Games
2012-11-15
further research we indicated possible extensions to state spaces with nontrivial geometry, to the controlled nonlinear quantum dynamic semigroups and...space nonlinear Markov semigroup is a one-parameter semigroup of (possibly nonlinear) transformations of the unit simplex in n-dimensional Euclidean...certain mixing property of nonlinear transition probabilities. In case of the semigroup parametrized by continuous time one defines its generator as the
Nonlinear biochemical signal processing via noise propagation.
Kim, Kyung Hyuk; Qian, Hong; Sauro, Herbert M
2013-10-14
Single-cell studies often show significant phenotypic variability due to the stochastic nature of intra-cellular biochemical reactions. When the numbers of molecules, e.g., transcription factors and regulatory enzymes, are in low abundance, fluctuations in biochemical activities become significant and such "noise" can propagate through regulatory cascades in terms of biochemical reaction networks. Here we develop an intuitive, yet fully quantitative method for analyzing how noise affects cellular phenotypes based on identifying a system's nonlinearities and noise propagations. We observe that such noise can simultaneously enhance sensitivities in one behavioral region while reducing sensitivities in another. Employing this novel phenomenon we designed three biochemical signal processing modules: (a) A gene regulatory network that acts as a concentration detector with both enhanced amplitude and sensitivity. (b) A non-cooperative positive feedback system, with a graded dose-response in the deterministic case, that serves as a bistable switch due to noise-induced ultra-sensitivity. (c) A noise-induced linear amplifier for gene regulation that requires no feedback. The methods developed in the present work allow one to understand and engineer nonlinear biochemical signal processors based on fluctuation-induced phenotypes.
Recombination Processes and Nonlinear Markov Chains.
Pirogov, Sergey; Rybko, Alexander; Kalinina, Anastasia; Gelfand, Mikhail
2016-09-01
Bacteria are known to exchange genetic information by horizontal gene transfer. Since the frequency of homologous recombination depends on the similarity between the recombining segments, several studies examined whether this could lead to the emergence of subspecies. Most of them simulated fixed-size Wright-Fisher populations, in which the genetic drift should be taken into account. Here, we use nonlinear Markov processes to describe a bacterial population evolving under mutation and recombination. We consider a population structure as a probability measure on the space of genomes. This approach implies the infinite population size limit, and thus, the genetic drift is not assumed. We prove that under these conditions, the emergence of subspecies is impossible.
Tóth, B.; Lillo, F.; Farmer, J. D.
2010-11-01
We introduce an algorithm for the segmentation of a class of regime switching processes. The segmentation algorithm is a non parametric statistical method able to identify the regimes (patches) of a time series. The process is composed of consecutive patches of variable length. In each patch the process is described by a stationary compound Poisson process, i.e. a Poisson process where each count is associated with a fluctuating signal. The parameters of the process are different in each patch and therefore the time series is non-stationary. Our method is a generalization of the algorithm introduced by Bernaola-Galván, et al. [Phys. Rev. Lett. 87, 168105 (2001)]. We show that the new algorithm outperforms the original one for regime switching models of compound Poisson processes. As an application we use the algorithm to segment the time series of the inventory of market members of the London Stock Exchange and we observe that our method finds almost three times more patches than the original one.
Global satisfactory control for nonlinear integrator processes with long delay
Institute of Scientific and Technical Information of China (English)
Yiqun YANG; Guobo XIANG
2007-01-01
Integrator processes with long delay are difficult to control. Nonlinear characteristics of actuators make the control problem more challenging. A technique is proposed in this paper for global satisfactory control (GSC) of such processes with relay-type nonlinearity. An oscillatory control signal is injected into the nonlinear process; the amplitude and frequency of the oscillatory signal are designed to linearise the nonlinear process in the sense of harmonic analysis; and a state feedback controller is configured to implement GSC over the linearised process. An illustrative example is given to demonstrate the effectiveness of the proposed method.
Melanson, Alexandre; Mejias, Jorge F; Jun, James J; Maler, Leonard; Longtin, André
2017-01-01
The neural basis of spontaneous movement generation is a fascinating open question. Long-term monitoring of fish, swimming freely in a constant sensory environment, has revealed a sequence of behavioral states that alternate randomly and spontaneously between periods of activity and inactivity. We show that key dynamical features of this sequence are captured by a 1-D diffusion process evolving in a nonlinear double well energy landscape, in which a slow variable modulates the relative depth of the wells. This combination of stochasticity, nonlinearity, and nonstationary forcing correctly captures the vastly different timescales of fluctuations observed in the data (∼1 to ∼1000 s), and yields long-tailed residence time distributions (RTDs) also consistent with the data. In fact, our model provides a simple mechanism for the emergence of long-tailed distributions in spontaneous animal behavior. We interpret the stochastic variable of this dynamical model as a decision-like variable that, upon reaching a threshold, triggers the transition between states. Our main finding is thus the identification of a threshold crossing process as the mechanism governing spontaneous movement initiation and termination, and to infer the presence of underlying nonstationary agents. Another important outcome of our work is a dimensionality reduction scheme that allows similar segments of data to be grouped together. This is done by first extracting geometrical features in the dataset and then applying principal component analysis over the feature space. Our study is novel in its ability to model nonstationary behavioral data over a wide range of timescales.
Boashash, Boualem; Boubchir, Larbi; Azemi, Ghasem
2012-12-01
This article presents a general methodology for processing non-stationary signals for the purpose of classification and localization. The methodology combines methods adapted from three complementary areas: time-frequency signal analysis, multichannel signal analysis and image processing. The latter three combine in a new methodology referred to as multichannel time-frequency image processing which is applied to the problem of classifying electroencephalogram (EEG) abnormalities in both adults and newborns. A combination of signal related features and image related features are used by merging key instantaneous frequency descriptors which characterize the signal non-stationarities. The results obtained show that, firstly, the features based on time-frequency image processing techniques such as image segmentation, improve the performance of EEG abnormalities detection in the classification systems based on multi-SVM and neural network classifiers. Secondly, these discriminating features are able to better detect the correlation between newborn EEG signals in a multichannel-based newborn EEG seizure detection for the purpose of localizing EEG abnormalities on the scalp.
On non-stationary threshold autoregressive models
Liu, Weidong; Shao, Qi-Man; 10.3150/10-BEJ306
2011-01-01
In this paper we study the limiting distributions of the least-squares estimators for the non-stationary first-order threshold autoregressive (TAR(1)) model. It is proved that the limiting behaviors of the TAR(1) process are very different from those of the classical unit root model and the explosive AR(1).
Krishnaswamy, Jagdish; Vaidyanathan, Srinivas; Rajagopalan, Balaji; Bonell, Mike; Sankaran, Mahesh; Bhalla, R. S.; Badiger, Shrinivas
2015-07-01
The El Nino Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) are widely recognized as major drivers of inter-annual variability of the Indian monsoon (IM) and extreme rainfall events (EREs). We assess the time-varying strength and non-linearity of these linkages using dynamic linear regression and Generalized Additive Models. Our results suggest that IOD has evolved independently of ENSO, with its influence on IM and EREs strengthening in recent decades when compared to ENSO, whose relationship with IM seems to be weakening and more uncertain. A unit change in IOD currently has a proportionately greater impact on IM. ENSO positively influences EREs only below a threshold of 100 mm day-1. Furthermore, there is a non-linear and positive relationship between IOD and IM totals and the frequency of EREs (>100 mm day-1). Improvements in modeling this complex system can enhance the forecasting accuracy of the IM and EREs.
Non-stationary Operation Regimes of the Gas Bearings
Directory of Open Access Journals (Sweden)
Ilina Tamara Evgenevna
2014-07-01
Full Text Available This review provides of basic information on non-stationary operation regimes of the gas bearings. The causes and mechanisms of maintaining the oscillation of the rotor’s gas suspensions are discussed. A brief review of linear, nonlinear and resonant vibrational effect is given. The questions on the oscillations in the layer of gas and liquid lubrication in the bearings are elaborated. A classification of non-stationary processes in gas bearings is given. Brief information on issues such as "frequency capture", "Sommerfeld effect", "a half-speed and fraction-speed vortex", "pneumatic hammer", "consumption oscillations in nozzles". The main tasks for the gas-static bearing’s control system are formulated. The results of calculations of the reaction in gas-static rotor bearings on a single external influence. It is shown that when the external load, the impact of external forces and the gas pressure in the lubricating gap rotor motion seeks to limit discrete trajectories. Thus, the radius is changed stepwise precession and not continuously. Increasing supply pressure in the lubricating gap fluctuations can be suppressed by decreasing the diameter of the precession.
Generalized Mass Action Law and Thermodynamics of Nonlinear Markov Processes
Gorban, A N
2015-01-01
The nonlinear Markov processes are the measure-valued dynamical systems which preserve positivity. They can be represented as the law of large numbers limits of general Markov models of interacting particles. In physics, the kinetic equations allow Lyapunov functionals (entropy, free energy, etc.). This may be considered as a sort of inheritance of the Lyapunov functionals from the microscopic master equations. We study nonlinear Markov processes that inherit thermodynamic properties from the microscopic linear Markov processes. We develop the thermodynamics of nonlinear Markov processes and analyze the asymptotic assumption, which are sufficient for this inheritance.
Nonlinear spectral unmixing of hyperspectral images using Gaussian processes
Altmann, Yoann; McLaughlin, Steve; Tourneret, Jean-Yves
2012-01-01
This paper presents an unsupervised algorithm for nonlinear unmixing of hyperspectral images. The proposed model assumes that the pixel reflectances result from a nonlinear function of the abundance vectors associated with the pure spectral components. We assume that the spectral signatures of the pure components and the nonlinear function are unknown. The first step of the proposed method consists of the Bayesian estimation of the abundance vectors for all the image pixels and the nonlinear function relating the abundance vectors to the observations. The endmembers are subsequently estimated using Gaussian process regression. The performance of the unmixing strategy is evaluated with simulations conducted on synthetic and real data.
Bubble nonlinear dynamics and stimulated scattering process
Jie, Shi; De-Sen, Yang; Sheng-Guo, Shi; Bo, Hu; Hao-Yang, Zhang; Shi-Yong, Hu
2016-02-01
A complete understanding of the bubble dynamics is deemed necessary in order to achieve their full potential applications in industry and medicine. For this purpose it is first needed to expand our knowledge of a single bubble behavior under different possible conditions including the frequency and pressure variations of the sound field. In addition, stimulated scattering of sound on a bubble is a special effect in sound field, and its characteristics are associated with bubble oscillation mode. A bubble in liquid can be considered as a representative example of nonlinear dynamical system theory with its resonance, and its dynamics characteristics can be described by the Keller-Miksis equation. The nonlinear dynamics of an acoustically excited gas bubble in water is investigated by using theoretical and numerical analysis methods. Our results show its strongly nonlinear behavior with respect to the pressure amplitude and excitation frequency as the control parameters, and give an intuitive insight into stimulated sound scattering on a bubble. It is seen that the stimulated sound scattering is different from common dynamical behaviors, such as bifurcation and chaos, which is the result of the nonlinear resonance of a bubble under the excitation of a high amplitude acoustic sound wave essentially. The numerical analysis results show that the threshold of stimulated sound scattering is smaller than those of bifurcation and chaos in the common condition. Project supported by the Program for Changjiang Scholars and Innovative Research Team in University, China (Grant No. IRT1228) and the Young Scientists Fund of the National Natural Science Foundation of China (Grant Nos. 11204050 and 11204049).
Appropriate model selection methods for nonstationary generalized extreme value models
Kim, Hanbeen; Kim, Sooyoung; Shin, Hongjoon; Heo, Jun-Haeng
2017-04-01
Several evidences of hydrologic data series being nonstationary in nature have been found to date. This has resulted in the conduct of many studies in the area of nonstationary frequency analysis. Nonstationary probability distribution models involve parameters that vary over time. Therefore, it is not a straightforward process to apply conventional goodness-of-fit tests to the selection of an appropriate nonstationary probability distribution model. Tests that are generally recommended for such a selection include the Akaike's information criterion (AIC), corrected Akaike's information criterion (AICc), Bayesian information criterion (BIC), and likelihood ratio test (LRT). In this study, the Monte Carlo simulation was performed to compare the performances of these four tests, with regard to nonstationary as well as stationary generalized extreme value (GEV) distributions. Proper model selection ratios and sample sizes were taken into account to evaluate the performances of all the four tests. The BIC demonstrated the best performance with regard to stationary GEV models. In case of nonstationary GEV models, the AIC proved to be better than the other three methods, when relatively small sample sizes were considered. With larger sample sizes, the AIC, BIC, and LRT presented the best performances for GEV models which have nonstationary location and/or scale parameters, respectively. Simulation results were then evaluated by applying all four tests to annual maximum rainfall data of selected sites, as observed by the Korea Meteorological Administration.
Does the cerebral cortex exploit high dimensional, non-linear dynamics for information processing?
Directory of Open Access Journals (Sweden)
Wolf Singer
2016-09-01
Full Text Available The discovery of stimulus induced synchronisation in the visual cortex suggested the possibility that the relations among low-level stimulus features are encoded by the temporal relationship between neuronal discharges. In this framework, temporal coherence is considered a signature of perceptual grouping. This insight triggered a large number of experimental studies which sought to investigate the relationship between temporal coordination and cognitive functions. While some core predictions derived from the initial hypothesis were confirmed, these studies, also revealed a rich dynamical landscape beyond simple coherence whose role in signal processing is still poorly understood. In this paper a framework is presented which establishes links between the various manifestations of cortical dynamics by assigning specific coding functions to low dimensional dynamic features such as synchronized oscillations and phase shifts on the one hand and high dimensional non-linear, non-stationary dynamics on the other. The data serving as basis for this synthetic approach have been obtained with chronic multisite recordings from the visual cortex of anesthetized cats and from monkeys trained to solve cognitive tasks. It is proposed that the low dimensional dynamics characterized by synchronized oscillations and large-scale correlations are sub-states that represent the results of computations performed in the high dimensional state space provided by recurrently coupled networks.
Spectral Analysis of Nonstationary Spacecraft Vibration Data
1965-11-01
the instantaneous power spectral density function for the process (y(t)). This spectral function can take on negative values for certain cases...power spectral density function is not directly measurable in the frequency domain. An experimental estimate for the function can be obtained only by...called the generalized power spectral density function for the process (y(t)) . This spectral description for nonstationary data is of great value for
NONLINEAR MODEL PREDICTIVE CONTROL OF CHEMICAL PROCESSES
Directory of Open Access Journals (Sweden)
R. G. SILVA
1999-03-01
Full Text Available A new algorithm for model predictive control is presented. The algorithm utilizes a simultaneous solution and optimization strategy to solve the model's differential equations. The equations are discretized by equidistant collocation, and along with the algebraic model equations are included as constraints in a nonlinear programming (NLP problem. This algorithm is compared with the algorithm that uses orthogonal collocation on finite elements. The equidistant collocation algorithm results in simpler equations, providing a decrease in computation time for the control moves. Simulation results are presented and show a satisfactory performance of this algorithm.
Coupled parametric processes in binary nonlinear photonic structures
Saygin, M Yu
2016-01-01
We study parametric interactions in a new type of nonlinear photonic structures, which is realized in the vicinity of a pair of nonlinear crystals. In this kind of structure, which we call binary, multiple nonlinear optical processes can be implemented simultaneously, owing to multiple phase-matching conditions, fulfilled separately in the constituent crystals. The coupling between the nonlinear processes by means of modes sharing similar frequency is attained by the spatially-broadband nature of the parametric fields. We investigate the spatial properties of the fields generated in the binary structure constructed from periodically poled crystals for the two examples: 1) single parametric down-conversion, and 2) coupled parametric down-conversion and up-conversion processes. The efficacy of the fields' generation in these examples is analyzed through comparison with the cases of traditional single periodically poled crystal and aperiodic photonic structure, respectively. It has been shown that the relative s...
Yashkir, O. V.; Yashkir, Yu N.
1987-11-01
An investigation is made of nonlinear optical interaction of light propagating in a planar waveguide with surface polaritons. Reduced wave equations for the amplitudes of the waveguide modes and surface polaritons are used to study the characteristics of generation of surface polaritons of difference frequency, parametric frequency up-conversion of the polaritons, and stimulated Raman scattering by the polaritons. An analysis is made of the characteristic properties of the investigated nonlinear optical processes.
Si-rich Silicon Nitride for Nonlinear Signal Processing Applications.
Lacava, Cosimo; Stankovic, Stevan; Khokhar, Ali Z; Bucio, T Dominguez; Gardes, F Y; Reed, Graham T; Richardson, David J; Petropoulos, Periklis
2017-02-02
Nonlinear silicon photonic devices have attracted considerable attention thanks to their ability to show large third-order nonlinear effects at moderate power levels allowing for all-optical signal processing functionalities in miniaturized components. Although significant efforts have been made and many nonlinear optical functions have already been demonstrated in this platform, the performance of nonlinear silicon photonic devices remains fundamentally limited at the telecom wavelength region due to the two photon absorption (TPA) and related effects. In this work, we propose an alternative CMOS-compatible platform, based on silicon-rich silicon nitride that can overcome this limitation. By carefully selecting the material deposition parameters, we show that both of the device linear and nonlinear properties can be tuned in order to exhibit the desired behaviour at the selected wavelength region. A rigorous and systematic fabrication and characterization campaign of different material compositions is presented, enabling us to demonstrate TPA-free CMOS-compatible waveguides with low linear loss (~1.5 dB/cm) and enhanced Kerr nonlinear response (Re{γ} = 16 Wm(-1)). Thanks to these properties, our nonlinear waveguides are able to produce a π nonlinear phase shift, paving the way for the development of practical devices for future optical communication applications.
Gaussian semiparametric estimation of non-stationary time series
Velasco, Carlos
1998-01-01
Generalizing the definition of the memory parameter d in terms of the differentiated series, we showed in Velasco (Non-stationary log-periodogram regression, Forthcoming J. Economet., 1997) that it is possible to estimate consistently the memory of non-stationary processes using methods designed for stationary long-range-dependent time series. In this paper we consider the Gaussian semiparametric estimate analysed by Robinson (Gaussian semiparametric estimation of long range dependence. Ann. ...
Saturation process of nonlinear standing waves
Institute of Scientific and Technical Information of China (English)
马大猷; 刘克
1996-01-01
The sound pressure of the nonlinear standing waves is distorted as expected, but also tends to saturate as being found in standing-wave tube experiments with increasing sinusoidal excitation. Saturation conditions were not actually reached, owing to limited excitation power, but the evidence of tendency to saturation is without question. It is the purpose of this investigation to find the law of saturation from the existing experimental data. The results of curve fitting indicate that negative feedback limits the growth of sound pressure with increasing excitation, the growth of the fundamental and the second harmonic by the negative feedback of their sound pressures, and the growth of the third and higher harmonics, however, by their energies (sound pressures squared). The growth functions of all the harmonics are derived, which are confirmed by the experiments. The saturation pressures and their properties are found.
Adaptive control method for nonlinear time-delay processes
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
Two complex properties,varying time-delay and block-oriented nonlinearity,are very common in chemical engineering processes and not easy to be controlled by routine control methods.Aimed at these two complex properties,a novel adaptive control algorithm the basis of nonlinear OFS(orthonormal functional series) model is proposed.First,the hybrid model which combines OFS and Volterra series is introduced.Then,a stable state feedback strategy is used to construct a nonlinear adaptive control algorithm that can guarantee the closed-loop stability and can track the set point curve without steady-state errors.Finally,control simulations and experiments on a nonlinear process with varying time-delay are presented.A number of experimental results validate the efficiency and superiority of this algorithm.
Nonlinear fiber applications for ultrafast all-optical signal processing
Kravtsov, Konstantin
In the present dissertation different aspects of all-optical signal processing, enabled by the use of nonlinear fibers, are studied. In particular, we focus on applications of a novel heavily GeO2-doped (HD) nonlinear fiber, that appears to be superior to many other types of nonlinear fibers because of its high nonlinearity and suitability for the use in nonlinear optical loop mirrors (NOLMs). Different functions, such as all-optical switching, thresholding, and wavelength conversion, are demonstrated with the HD fibers in the NOLM configuration. These basic functions are later used for realization of ultrafast time-domain demultiplexers, clock recovery, detectors of short pulses in stealth communications, and primitive elements for analog computations. Another important technology that benefits from the use of nonlinear fiber-based signal processing is optical code-division multiple access (CDMA). It is shown in both theory and experiment that all-optical thresholding is a unique way of improving existing detection methods for optical CDMA. Also, it is the way of implementation of true asynchronous optical spread-spectrum networks, which allows full realization of optical CDMA potential. Some aspects of quantum signal processing and manipulation of quantum states are also studied in this work. It is shown that propagation and collisions of Thirring solitons lead to a substantial squeezing of quantum states, which may find applications for generation of squeezed light.
Nonlinear Statistical Process Monitoring and Fault Detection Using Kernel ICA
Institute of Scientific and Technical Information of China (English)
ZHANG Xi; YAN Wei-wu; ZHAO Xu; SHAO Hui-he
2007-01-01
A novel nonlinear process monitoring and fault detection method based on kernel independent component analysis (ICA) is proposed. The kernel ICA method is a two-phase algorithm: whitened kernel principal component (KPCA) plus ICA. KPCA spheres data and makes the data structure become as linearly separable as possible by virtue of an implicit nonlinear mapping determined by kernel. ICA seeks the projection directions in the KPCA whitened space, making the distribution of the projected data as non-gaussian as possible. The application to the fluid catalytic cracking unit (FCCU) simulated process indicates that the proposed process monitoring method based on kernel ICA can effectively capture the nonlinear relationship in process variables. Its performance significantly outperforms monitoring method based on ICA or KPCA.
Modeling and stability analysis of the nonlinear reactive sputtering process
Directory of Open Access Journals (Sweden)
György Katalin
2011-12-01
Full Text Available The model of the reactive sputtering process has been determined from the dynamic equilibrium of the reactive gas inside the chamber and the dynamic equilibrium of the sputtered metal atoms which form the compound with the reactive gas atoms on the surface of the substrate. The analytically obtained dynamical model is a system of nonlinear differential equations which can result in a histeresis-type input/output nonlinearity. The reactive sputtering process has been simulated by integrating these differential equations. Linearization has been applied for classical analysis of the sputtering process and control system design.
An Agent Interaction Based Method for Nonlinear Process Plan Scheduling
Institute of Scientific and Technical Information of China (English)
GAO Qinglu; WU Bo; GUO Guang
2006-01-01
This article puts forward a scheduling method for nonlinear process plan shop floor. Task allocation and load balance are realized by bidding mechanism. Though the agent interaction process, the execution of tasks is determined and the coherence of manufacturing decision is verified. The employment of heuristic index can help to optimize the system performance.
Innovation as a Nonlinear Process and the Scientometric Perspective
Leydesdorff, L.; Rotolo, D.; de Nooy, W.; Archambault, E.; Gingras, Y.; Larivière, V.
2012-01-01
The process of innovation follows non-linear patterns across the domains of science, technology, and the economy. Novel bibliometric mapping techniques can be used to investigate and represent distinctive, but complementary perspectives on the innovation process (e.g., "demand" and "supply") as well
Jun, James J.; Longtin, André
2017-01-01
Abstract The neural basis of spontaneous movement generation is a fascinating open question. Long-term monitoring of fish, swimming freely in a constant sensory environment, has revealed a sequence of behavioral states that alternate randomly and spontaneously between periods of activity and inactivity. We show that key dynamical features of this sequence are captured by a 1-D diffusion process evolving in a nonlinear double well energy landscape, in which a slow variable modulates the relative depth of the wells. This combination of stochasticity, nonlinearity, and nonstationary forcing correctly captures the vastly different timescales of fluctuations observed in the data (∼1 to ∼1000 s), and yields long-tailed residence time distributions (RTDs) also consistent with the data. In fact, our model provides a simple mechanism for the emergence of long-tailed distributions in spontaneous animal behavior. We interpret the stochastic variable of this dynamical model as a decision-like variable that, upon reaching a threshold, triggers the transition between states. Our main finding is thus the identification of a threshold crossing process as the mechanism governing spontaneous movement initiation and termination, and to infer the presence of underlying nonstationary agents. Another important outcome of our work is a dimensionality reduction scheme that allows similar segments of data to be grouped together. This is done by first extracting geometrical features in the dataset and then applying principal component analysis over the feature space. Our study is novel in its ability to model nonstationary behavioral data over a wide range of timescales. PMID:28374017
Nonlinear partial least squares with Hellinger distance for nonlinear process monitoring
Harrou, Fouzi
2017-02-16
This paper proposes an efficient data-based anomaly detection method that can be used for monitoring nonlinear processes. The proposed method merges advantages of nonlinear projection to latent structures (NLPLS) modeling and those of Hellinger distance (HD) metric to identify abnormal changes in highly correlated multivariate data. Specifically, the HD is used to quantify the dissimilarity between current NLPLS-based residual and reference probability distributions. The performances of the developed anomaly detection using NLPLS-based HD technique is illustrated using simulated plug flow reactor data.
Nonlinear Dynamic Characteristics of Combustion Wave in SHS Process
Institute of Scientific and Technical Information of China (English)
无
2002-01-01
The characteristic of combustion wave and its change were analyzed by numerical value calculation and computer simulation,based on the combustion dynamical model of SHS process. It is shown that with the change of condition parameters in SHS process various time-space order combustion waves appear.It is concluded from non-liner dynamical mechanism analysis that the strong coupling of two non-linear dynamical processes is the dynamical mechanism causing the time-space order dissipation structures.
Relaxation Processes in Nonlinear Optical Polymer Films
Directory of Open Access Journals (Sweden)
S.N. Fedosov
2010-01-01
Full Text Available Dielectric properties of the guest-host polystyrene/DR1 system have been studied by the AC dielectric spectroscopy method at frequencies from 1 Hz to 0,5 MHz and by the thermally stimulated depolarization current (TSDC method from – 160 to 0 °C. The relaxation peaks at infra-low frequencies from 10 – 5to 10–2 Hz were also calculated using the Hamon’s approximation. Three relaxation processes, namely, α, β and δ ones were identified from the TSDC peaks, while the ε''(fdependence showed a non-Debye ρ-peak narrowing with temperature. The activation energy of the α-relaxation appeared to be 2,57 eV, while that of the γ-process was 0,52 eV. Temperature dependence of the relaxation time is agreed with the Williams-Landel-Ferry model. The ε''(fpeaks were fitted to Havriliak-Negami’s expression and the corresponding distribution parameters were obtained.
Ultra-Fast Optical Signal Processing in Nonlinear Silicon Waveguides
DEFF Research Database (Denmark)
Oxenløwe, Leif Katsuo; Galili, Michael; Pu, Minhao;
2011-01-01
We describe recent demonstrations of exploiting highly nonlinear silicon nanowires for processing Tbit/s optical data signals. We perform demultiplexing and optical waveform sampling of 1.28 Tbit/s and wavelength conversion of 640 Gbit/s data signals....
Institute of Scientific and Technical Information of China (English)
胡业民; 胡希伟
2001-01-01
Numerical analyses for the nonlinear evolutions of stimulated Raman scattering (SRS) and stimulated Brillouin scattering (SBS) processes are given. Various effects of the second- and third-order nonlinear susceptibilities on the SRS and SBS processes are studied. The nonlinear evolutions of SRS and SBS processes are atfected more efficiently than their linear growth rates by the nonlinear susceptibility.
Modeling Autoregressive Processes with Moving-Quantiles-Implied Nonlinearity
Directory of Open Access Journals (Sweden)
Isao Ishida
2015-01-01
Full Text Available We introduce and investigate some properties of a class of nonlinear time series models based on the moving sample quantiles in the autoregressive data generating process. We derive a test fit to detect this type of nonlinearity. Using the daily realized volatility data of Standard & Poor’s 500 (S&P 500 and several other indices, we obtained good performance using these models in an out-of-sample forecasting exercise compared with the forecasts obtained based on the usual linear heterogeneous autoregressive and other models of realized volatility.
New CMOS Compatible Platforms for Integrated Nonlinear Optical Signal Processing
Moss, D J
2014-01-01
Nonlinear photonic chips have succeeded in generating and processing signals all-optically with performance far superior to that possible electronically - particularly with respect to speed. Although silicon-on-insulator has been the leading platform for nonlinear optics, its high two-photon absorption at telecommunications wavelengths poses a fundamental limitation. This paper reviews some of the recent achievements in CMOS-compatible platforms for nonlinear optics, focusing on amorphous silicon and Hydex glass, highlighting their potential future impact as well as the challenges to achieving practical solutions for many key applications. These material systems have opened up many new capabilities such as on-chip optical frequency comb generation and ultrafast optical pulse generation and measurement.
Linear and Nonlinear MHD Wave Processes in Plasmas. Final Report
Energy Technology Data Exchange (ETDEWEB)
Tataronis, J. A.
2004-06-01
This program treats theoretically low frequency linear and nonlinear wave processes in magnetized plasmas. A primary objective has been to evaluate the effectiveness of MHD waves to heat plasma and drive current in toroidal configurations. The research covers the following topics: (1) the existence and properties of the MHD continua in plasma equilibria without spatial symmetry; (2) low frequency nonresonant current drive and nonlinear Alfven wave effects; and (3) nonlinear electron acceleration by rf and random plasma waves. Results have contributed to the fundamental knowledge base of MHD activity in symmetric and asymmetric toroidal plasmas. Among the accomplishments of this research effort, the following are highlighted: Identification of the MHD continuum mode singularities in toroidal geometry. Derivation of a third order ordinary differential equation that governs nonlinear current drive in the singular layers of the Alfvkn continuum modes in axisymmetric toroidal geometry. Bounded solutions of this ODE implies a net average current parallel to the toroidal equilibrium magnetic field. Discovery of a new unstable continuum of the linearized MHD equation in axially periodic circular plasma cylinders with shear and incompressibility. This continuum, which we named “accumulation continuum” and which is related to ballooning modes, arises as discrete unstable eigenfrequency accumulate on the imaginary frequency axis in the limit of large mode numbers. Development of techniques to control nonlinear electron acceleration through the action of multiple coherent and random plasmas waves. Two important elements of this program aye student participation and student training in plasma theory.
Process and meaning: nonlinear dynamics and psychology in visual art.
Zausner, Tobi
2007-01-01
Creating and viewing visual art are both nonlinear experiences. Creating a work of art is an irreversible process involving increasing levels of complexity and unpredictable events. Viewing art is also creative with collective responses forming autopoietic structures that shape cultural history. Artists work largely from the chaos of the unconscious and visual art contains elements of chaos. Works of art by the author are discussed in reference to nonlinear dynamics. "Travelogues" demonstrates continued emerging interpretations and a deterministic chaos. "Advice to the Imperfect" signifies the resolution of paradox in the nonlinear tension of opposites. "Quanah" shows the nonlinear tension of opposites as an ongoing personal evolution. "The Mother of All Things" depicts seemingly separate phenomena arising from undifferentiated chaos. "Memories" refers to emotional fixations as limit cycles. "Compassionate Heart," "Wind on the Lake," and "Le Mal du Pays" are a series of works in fractal format focusing on the archetype of the mother and child. "Sameness, Depth of Mystery" addresses the illusion of hierarchy and the dynamics of symbols. In "Chasadim" the origin of worlds and the regeneration of individuals emerge through chaos. References to chaos in visual art mirror the nonlinear complexity of life.
Nonlinear Processes in Magnetic Nanodots under Perpendicular Pumping: Micromagnetic Simulations
Directory of Open Access Journals (Sweden)
D.V. Slobodiainuk
2013-03-01
Full Text Available Processes that take place in permalloy nanodots under external electromagnetic pumping are considered. It is shown that in such system similar to bulk samples Suhl and kinetic instability processes are possible. Using micromagnetic simulations approach key features of mode excitation with an external pumping power increase were revealed. Results of the simulations were compared with published experimental data dedicated to investigation of magnetic nanodotes in nonlinear regime.
Information retrieval for nonstationary data records
Su, M. Y.
1971-01-01
A review and a critical discussion are made on the existing methods for analysis of nonstationary time series, and a new algorithm for splitting nonstationary time series, is applied to the analysis of sunspot data.
A non-linear model of economic production processes
Ponzi, A.; Yasutomi, A.; Kaneko, K.
2003-06-01
We present a new two phase model of economic production processes which is a non-linear dynamical version of von Neumann's neoclassical model of production, including a market price-setting phase as well as a production phase. The rate of an economic production process is observed, for the first time, to depend on the minimum of its input supplies. This creates highly non-linear supply and demand dynamics. By numerical simulation, production networks are shown to become unstable when the ratio of different products to total processes increases. This provides some insight into observed stability of competitive capitalist economies in comparison to monopolistic economies. Capitalist economies are also shown to have low unemployment.
Optoelectronic and nonlinear optical processes in low dimensional semiconductors
Indian Academy of Sciences (India)
B P Singh
2006-11-01
Spatial confinement of quantum excitations on their characteristic wavelength scale in low dimensional materials offers unique possibilities to engineer the electronic structure and thereby control their physical properties by way of simple manipulation of geometrical parameters. This has led to an overwhelming interest in quasi-zero dimensional semiconductors or quantum dots as tunable materials for multitude of exciting applications in optoelectronic and nonlinear optical devices and quantum information processing. Large nonlinear optical response and high luminescence quantum yield expected in these systems is a consequence of huge enhancement of transition probabilities ensuing from quantum confinement. High quantum efficiency of photoluminescence, however, is not usually realized in the case of bare semiconductor nanoparticles owing to the presence of surface states. In this talk, I will focus on the role of quantum confinement and surface states in ascertaining nonlinear optical and optoelectronic properties of II–VI semiconductor quantum dots and their nanocomposites. I will also discuss the influence of nonlinear optical processes on their optoelectronic characteristics.
NON-LINEAR FINITE ELEMENT MODELING OF DEEP DRAWING PROCESS
Directory of Open Access Journals (Sweden)
Hasan YILDIZ
2004-03-01
Full Text Available Deep drawing process is one of the main procedures used in different branches of industry. Finding numerical solutions for determination of the mechanical behaviour of this process will save time and money. In die surfaces, which have complex geometries, it is hard to determine the effects of parameters of sheet metal forming. Some of these parameters are wrinkling, tearing, and determination of the flow of the thin sheet metal in the die and thickness change. However, the most difficult one is determination of material properties during plastic deformation. In this study, the effects of all these parameters are analyzed before producing the dies. The explicit non-linear finite element method is chosen to be used in the analysis. The numerical results obtained for non-linear material and contact models are also compared with the experiments. A good agreement between the numerical and the experimental results is obtained. The results obtained for the models are given in detail.
Nonlinear Silicon Photonic Signal Processing Devices for Future Optical Networks
Directory of Open Access Journals (Sweden)
Cosimo Lacava
2017-01-01
Full Text Available In this paper, we present a review on silicon-based nonlinear devices for all optical nonlinear processing of complex telecommunication signals. We discuss some recent developments achieved by our research group, through extensive collaborations with academic partners across Europe, on optical signal processing using silicon-germanium and amorphous silicon based waveguides as well as novel materials such as silicon rich silicon nitride and tantalum pentoxide. We review the performance of four wave mixing wavelength conversion applied on complex signals such as Differential Phase Shift Keying (DPSK, Quadrature Phase Shift Keying (QPSK, 16-Quadrature Amplitude Modulation (QAM and 64-QAM that dramatically enhance the telecom signal spectral efficiency, paving the way to next generation terabit all-optical networks.
Preface "Nonlinear processes in oceanic and atmospheric flows"
Directory of Open Access Journals (Sweden)
E. García-Ladona
2010-05-01
Full Text Available Nonlinear phenomena are essential ingredients in many oceanic and atmospheric processes, and successful understanding of them benefits from multidisciplinary collaboration between oceanographers, meteorologists, physicists and mathematicians. The present Special Issue on "Nonlinear Processes in Oceanic and Atmospheric Flows" contains selected contributions from attendants to the workshop which, in the above spirit, was held in Castro Urdiales, Spain, in July 2008. Here we summarize the Special Issue contributions, which include papers on the characterization of ocean transport in the Lagrangian and in the Eulerian frameworks, generation and variability of jets and waves, interactions of fluid flow with plankton dynamics or heavy drops, scaling in meteorological fields, and statistical properties of El Niño Southern Oscillation.
Preface "Nonlinear processes in oceanic and atmospheric flows"
Mancho, A M; Turiel, A; Hernandez-Garcia, E; Lopez, C; Garcia-Ladona, E; 10.5194/npg-17-283-2010
2010-01-01
Nonlinear phenomena are essential ingredients in many oceanic and atmospheric processes, and successful understanding of them benefits from multidisciplinary collaboration between oceanographers, meteorologists, physicists and mathematicians. The present Special Issue on ``Nonlinear Processes in Oceanic and Atmospheric Flows'' contains selected contributions from attendants to the workshop which, in the above spirit, was held in Castro Urdiales, Spain, in July 2008. Here we summarize the Special Issue contributions, which include papers on the characterization of ocean transport in the Lagrangian and in the Eulerian frameworks, generation and variability of jets and waves, interactions of fluid flow with plankton dynamics or heavy drops, scaling in meteorological fields, and statistical properties of El Ni\\~no Southern Oscillation.
High-speed signal processing using highly nonlinear optical fibres
DEFF Research Database (Denmark)
Peucheret, Christophe; Oxenløwe, Leif Katsuo; Mulvad, Hans Christian Hansen
2009-01-01
relying on the phase of the optical field. Topics covered include all-optical switching of 640 Gbit/s and 1.28 Tbit/s serial data, wavelength conversion at 640 Gbit/s, optical amplitude regeneration of differential phase shift keying (DPSK) signals, as well as midspan spectral inversion for differential 8......We review recent progress in all-optical signal processing techniques making use of conventional silica-based highly nonlinear fibres. In particular, we focus on recent demonstrations of ultra-fast processing at 640 Gbit/s and above, as well as on signal processing of novel modulation formats...
Double resonant processes in $\\chi^{(2)}$ nonlinear periodic media
Konotop, V. V.; Kuzmiak, V.
2000-01-01
In a one-dimensional periodic nonlinear $\\chi^{(2)}$ medium, by choosing a proper material and geometrical parameters of the structure, it is possible to obtain two matching conditions for simultaneous generation of second and third harmonics. This leads to new diversity of the processes of the resonant three-wave interactions, which are discussed within the framework of slowly varying envelope approach. In particular, we concentrate on the fractional conversion of the frequency $\\omega \\to (...
SAR processing with non-linear FM chirp waveforms.
Energy Technology Data Exchange (ETDEWEB)
Doerry, Armin Walter
2006-12-01
Nonlinear FM (NLFM) waveforms offer a radar matched filter output with inherently low range sidelobes. This yields a 1-2 dB advantage in Signal-to-Noise Ratio over the output of a Linear FM (LFM) waveform with equivalent sidelobe filtering. This report presents details of processing NLFM waveforms in both range and Doppler dimensions, with special emphasis on compensating intra-pulse Doppler, often cited as a weakness of NLFM waveforms.
Park, Jeryang; Rao, P. Suresh C.
2014-11-01
We present here a conceptual model and analysis of complex systems using hypothetical cases of regime shifts resulting from temporal non-stationarity in attractor strengths, and then present selected published cases to illustrate such regime shifts in hydrologic systems (shallow aquatic ecosystems; water table shifts; soil salinization). Complex systems are dynamic and can exist in two or more stable states (or regimes). Temporal variations in state variables occur in response to fluctuations in external forcing, which are modulated by interactions among internal processes. Combined effects of external forcing and non-stationary strengths of alternative attractors can lead to shifts from original to alternate regimes. In systems with bi-stable states, when the strengths of two competing attractors are constant in time, or are non-stationary but change in a linear fashion, regime shifts are found to be temporally stationary and only controlled by the characteristics of the external forcing. However, when attractor strengths change in time non-linearly or vary stochastically, regime shifts in complex systems are characterized by non-stationary probability density functions (pdfs). We briefly discuss implications and challenges to prediction and management of hydrologic complex systems.
Park, Jeryang; Rao, P Suresh C
2014-11-15
We present here a conceptual model and analysis of complex systems using hypothetical cases of regime shifts resulting from temporal non-stationarity in attractor strengths, and then present selected published cases to illustrate such regime shifts in hydrologic systems (shallow aquatic ecosystems; water table shifts; soil salinization). Complex systems are dynamic and can exist in two or more stable states (or regimes). Temporal variations in state variables occur in response to fluctuations in external forcing, which are modulated by interactions among internal processes. Combined effects of external forcing and non-stationary strengths of alternative attractors can lead to shifts from original to alternate regimes. In systems with bi-stable states, when the strengths of two competing attractors are constant in time, or are non-stationary but change in a linear fashion, regime shifts are found to be temporally stationary and only controlled by the characteristics of the external forcing. However, when attractor strengths change in time non-linearly or vary stochastically, regime shifts in complex systems are characterized by non-stationary probability density functions (pdfs). We briefly discuss implications and challenges to prediction and management of hydrologic complex systems.
Correlation, regression, and cointegration of nonstationary economic time series
DEFF Research Database (Denmark)
Johansen, Søren
Yule (1926) introduced the concept of spurious or nonsense correlation, and showed by simulation that for some nonstationary processes, that the empirical correlations seem not to converge in probability even if the processes were independent. This was later discussed by Granger and Newbold (1974...
Correlation, Regression, and Cointegration of Nonstationary Economic Time Series
DEFF Research Database (Denmark)
Johansen, Søren
Yule (1926) introduced the concept of spurious or nonsense correlation, and showed by simulation that for some nonstationary processes, that the empirical correlations seem not to converge in probability even if the processes were independent. This was later discussed by Granger and Newbold (1974...
Measurements of bubbles in sea water by nonstationary sound scattering.
Akulichev, V A; Bulanov, V A
2011-11-01
Methods for the characterization of bubbles in sea water by acoustic scattering are analyzed. Nonstationary linear and nonlinear sound scattering methods are proposed. The transient linear and nonlinear sound scattering allows the scattering by resonant gas bubbles to be distinguished from the scattering by other microinhomogeneities. The application of parametric arrays in oceanic experiments, together with the broadband frequency analysis of the backscattering coefficient, allows information about bubbles in sea water to be obtained. Experimental results on sound scattering and gas bubble distribution functions are presented for different conditions in the ocean.
A comparison of nonlinear media for parametric all-optical signal processing
DEFF Research Database (Denmark)
Martinez Diaz, Jordi; Bohigas Nadal, Jaume; Vukovic, Dragana;
2013-01-01
We systematically compare nonlinear media for parametric signal processing by determining the minimum pump power that is required for a given conversion efficiency in a degenerate four-wave mixing process, including the effect of nonlinear loss....
Nonlinear Statistical Signal Processing: A Particle Filtering Approach
Energy Technology Data Exchange (ETDEWEB)
Candy, J
2007-09-19
A introduction to particle filtering is discussed starting with an overview of Bayesian inference from batch to sequential processors. Once the evolving Bayesian paradigm is established, simulation-based methods using sampling theory and Monte Carlo realizations are discussed. Here the usual limitations of nonlinear approximations and non-gaussian processes prevalent in classical nonlinear processing algorithms (e.g. Kalman filters) are no longer a restriction to perform Bayesian inference. It is shown how the underlying hidden or state variables are easily assimilated into this Bayesian construct. Importance sampling methods are then discussed and shown how they can be extended to sequential solutions implemented using Markovian state-space models as a natural evolution. With this in mind, the idea of a particle filter, which is a discrete representation of a probability distribution, is developed and shown how it can be implemented using sequential importance sampling/resampling methods. Finally, an application is briefly discussed comparing the performance of the particle filter designs with classical nonlinear filter implementations.
Predicting speech intelligibility in conditions with nonlinearly processed noisy speech
DEFF Research Database (Denmark)
Jørgensen, Søren; Dau, Torsten
2013-01-01
The speech-based envelope power spectrum model (sEPSM; [1]) was proposed in order to overcome the limitations of the classical speech transmission index (STI) and speech intelligibility index (SII). The sEPSM applies the signal-tonoise ratio in the envelope domain (SNRenv), which was demonstrated...... to successfully predict speech intelligibility in conditions with nonlinearly processed noisy speech, such as processing with spectral subtraction. Moreover, a multiresolution version (mr-sEPSM) was demonstrated to account for speech intelligibility in various conditions with stationary and fluctuating...... from computational auditory scene analysis and further support the hypothesis that the SNRenv is a powerful metric for speech intelligibility prediction....
Hazard function theory for nonstationary natural hazards
Read, Laura K.; Vogel, Richard M.
2016-04-01
Impact from natural hazards is a shared global problem that causes tremendous loss of life and property, economic cost, and damage to the environment. Increasingly, many natural processes show evidence of nonstationary behavior including wind speeds, landslides, wildfires, precipitation, streamflow, sea levels, and earthquakes. Traditional probabilistic analysis of natural hazards based on peaks over threshold (POT) generally assumes stationarity in the magnitudes and arrivals of events, i.e., that the probability of exceedance of some critical event is constant through time. Given increasing evidence of trends in natural hazards, new methods are needed to characterize their probabilistic behavior. The well-developed field of hazard function analysis (HFA) is ideally suited to this problem because its primary goal is to describe changes in the exceedance probability of an event over time. HFA is widely used in medicine, manufacturing, actuarial statistics, reliability engineering, economics, and elsewhere. HFA provides a rich theory to relate the natural hazard event series (X) with its failure time series (T), enabling computation of corresponding average return periods, risk, and reliabilities associated with nonstationary event series. This work investigates the suitability of HFA to characterize nonstationary natural hazards whose POT magnitudes are assumed to follow the widely applied generalized Pareto model. We derive the hazard function for this case and demonstrate how metrics such as reliability and average return period are impacted by nonstationarity and discuss the implications for planning and design. Our theoretical analysis linking hazard random variable X with corresponding failure time series T should have application to a wide class of natural hazards with opportunities for future extensions.
Non-stationary model residuals: information, disinformation and measures of information
Beven, K.
2012-12-01
We expect error in applying hydrological models. They are approximate representations of hydrological processes, driven by approximate estimates of boundary fluxes and compared against uncertain observations of discharge (and perhaps other observables). We should expect, from the nonlinear dynamics of hydrological responses and the epistemic nature of many of the sources of uncertainty, that the residuals should be non-stationary in character. This suggests that it might be difficult to find a simple representation of the error characteristics that could be used, for example, to define a likelihood function for parameter estimation. This is often ignored: the likelihood functions used in hydrology have generally been simple, aleatory and stationary (albeit that this is not a conceptual limitation - as one referee put it, in principle an error model can be infinitely complex!). However, the epistemic nature of the uncertainty does raise the issue of how far nonstationary model residuals might be informative about change in the system and how far they reflect epistemic disinformation in inferring the true nature of the system. Some periods of potential calibration data are clearly disinformative in inference (even if informative about observational techniques), but other unusual events might be particularly revealing about the process responses. Is it therefore possible to define measures of information that can reflect some of these difficulties prior to running a model, or must we resort to data assimilation conditional on a model in detecting nonstationarity?
Wu, Hao; Noé, Frank
2011-03-01
Diffusion processes are relevant for a variety of phenomena in the natural sciences, including diffusion of cells or biomolecules within cells, diffusion of molecules on a membrane or surface, and diffusion of a molecular conformation within a complex energy landscape. Many experimental tools exist now to track such diffusive motions in single cells or molecules, including high-resolution light microscopy, optical tweezers, fluorescence quenching, and Förster resonance energy transfer (FRET). Experimental observations are most often indirect and incomplete: (1) They do not directly reveal the potential or diffusion constants that govern the diffusion process, (2) they have limited time and space resolution, and (3) the highest-resolution experiments do not track the motion directly but rather probe it stochastically by recording single events, such as photons, whose properties depend on the state of the system under investigation. Here, we propose a general Bayesian framework to model diffusion processes with nonlinear drift based on incomplete observations as generated by various types of experiments. A maximum penalized likelihood estimator is given as well as a Gibbs sampling method that allows to estimate the trajectories that have caused the measurement, the nonlinear drift or potential function and the noise or diffusion matrices, as well as uncertainty estimates of these properties. The approach is illustrated on numerical simulations of FRET experiments where it is shown that trajectories, potentials, and diffusion constants can be efficiently and reliably estimated even in cases with little statistics or nonequilibrium measurement conditions.
Nonlinear processes in the strong wave-plasma interaction
Pegoraro, Francesco; Califano, Francesco; Attico, Nicola; Bulanov, Sergei
2000-10-01
Nonlinear interactions in hot laboratory and/or astrophysical plasmas are a very efficient mechanism able to transfer the energy from the large to the small spatial scales of the system. As a result, kinetic processes are excited and play a key role in the plasma dynamics since the typical fluid dissipative length scales (where the nonlinear cascade is stopped) are (much) smaller then the kinetic length scales. Then, the key point is the role of the kinetic effects in the global plasma dynamics, i.e. whether the kinetic effects remains confined to the small scales of the system or whether there is a significant feedback on the large scales. Here we will address this problem by discussing the nonlinear kinetic evolution of the electromagnetic beam plasma instability where phase space vortices, as well as large scale vortex like magnetic structures in the physical space, are generated by wave - particle interactions. The role and influence of kinetic effects on the large scale plasma dynamics will be also discussed by addressing the problem of collisionless magnetic reconection.
Experimental characterization of nonlinear processes of whistler branch waves
Tejero, E. M.; Crabtree, C.; Blackwell, D. D.; Amatucci, W. E.; Ganguli, G.; Rudakov, L.
2016-05-01
Experiments in the Space Physics Simulation Chamber at the Naval Research Laboratory isolated and characterized important nonlinear wave-wave and wave-particle interactions that can occur in the Earth's Van Allen radiation belts by launching predominantly electrostatic waves in the intermediate frequency range with wave normal angle greater than 85 ° and measuring the nonlinearly generated electromagnetic scattered waves. The scattered waves have a perpendicular wavelength that is nearly an order of magnitude larger than that of the pump wave. Calculations of scattering efficiency from experimental measurements demonstrate that the scattering efficiency is inversely proportional to the damping rate and trends towards unity as the damping rate approaches zero. Signatures of both wave-wave and wave-particle scatterings are also observed in the triggered emission process in which a launched wave resonant with a counter-propagating electron beam generates a large amplitude chirped whistler wave. The possibility of nonlinear scattering or three wave decay as a saturation mechanism for the triggered emission is suggested. The laboratory experiment has inspired the search for scattering signatures in the in situ data of chorus emission in the radiation belts.
Recent Advances in Graphene-Assisted Nonlinear Optical Signal Processing
Directory of Open Access Journals (Sweden)
Jian Wang
2016-01-01
Full Text Available Possessing a variety of remarkable optical, electronic, and mechanical properties, graphene has emerged as an attractive material for a myriad of optoelectronic applications. The wonderful optical properties of graphene afford multiple functions of graphene based polarizers, modulators, transistors, and photodetectors. So far, the main focus has been on graphene based photonics and optoelectronics devices. Due to the linear band structure allowing interband optical transitions at all photon energies, graphene has remarkably large third-order optical susceptibility χ(3, which is only weakly dependent on the wavelength in the near-infrared frequency range. The graphene-assisted four-wave mixing (FWM based wavelength conversions have been experimentally demonstrated. So, we believe that the potential applications of graphene also lie in nonlinear optical signal processing, where the combination of its unique large χ(3 nonlinearities and dispersionless over the wavelength can be fully exploited. In this review article, we give a brief overview of our recent progress in graphene-assisted nonlinear optical device and their applications, including degenerate FWM based wavelength conversion of quadrature phase-shift keying (QPSK signal, phase conjugated wavelength conversion by degenerate FWM and transparent wavelength conversion by nondegenerate FWM, two-input and three-input high-base optical computing, and high-speed gate-tunable terahertz coherent perfect absorption (CPA using a split-ring graphene.
Nonstationary distributions of wave intensities in wave turbulence
Choi, Yeontaek; Jo, Sanggyu; Kwon, Young-Sam; Nazarenko, Sergey
2017-09-01
We obtain a general solution for the probability density function (PDF) of wave intensities in non-stationary wave turbulence. The solution is expressed in terms of the initial PDF and the wave action spectrum satisfying the wave-kinetic equation. We establish that, in the absence of wave breaking, the wave statistics converge to a Gaussian distribution in forced-dissipated wave systems while approaching a steady state. Also, we find that in non-stationary systems, if the statistic is Gaussian initially, it will remain Gaussian for all time. Generally, if the statistic is not initially Gaussian, it will remain non-Gaussian over the characteristic nonlinear evolution time of the wave spectrum. In freely decaying wave turbulence, substantial deviations from Gaussianity may persist infinitely long.
Institute of Scientific and Technical Information of China (English)
XU Guang; QIAN Liejia; WANG Tao; FAN Dianyuan; LI Fuming
2004-01-01
It is shown that the cascaded fifth-order nonlinear phase shifts will increase with energy loss in the cascaded processes. Essentially different from the multi-photon absorption accompanied with inherent material nonlinearities, the loss of fundamental wave in a cascaded process is controllable and suppressible. By introducing difference frequencies generated from the reaction between the fundamental and its second harmonic after the cascaded processes, the fundamental wave can be free of energy loss, while the large cascaded fifth-order nonlinear phase shift is maintained.
Nonstationary Narrow-Band Response and First-Passage Probability
DEFF Research Database (Denmark)
Krenk, Steen
1979-01-01
The notion of a nonstationary narrow-band stochastic process is introduced without reference to a frequency spectrum, and the joint distribution function of two consecutive maxima is approximated by use of an envelope. Based on these definitions the first passage problem is treated as a Markov po...
Identification of Nonstationary Cellular Automata
Institute of Scientific and Technical Information of China (English)
AndrewI.Adamatzky
1992-01-01
The principal feature of nonstationary cellular automata(NCA) is that a local transitiol rule of each cell is changed at each time step depending on neighborhood configuration at previous time step.The identification problem for NCA is extraction of local transition rules and the establishment of mechanism for changing these rules using sequence of NCA configurations.We present serial and parallel algorithms for identification of NCA.
Nonlinear Optical Microscopy Signal Processing Strategies in Cancer
Adur, Javier; Carvalho, Hernandes F; Cesar, Carlos L; Casco, Víctor H
2014-01-01
This work reviews the most relevant present-day processing methods used to improve the accuracy of multimodal nonlinear images in the detection of epithelial cancer and the supporting stroma. Special emphasis has been placed on methods of non linear optical (NLO) microscopy image processing such as: second harmonic to autofluorescence ageing index of dermis (SAAID), tumor-associated collagen signatures (TACS), fast Fourier transform (FFT) analysis, and gray level co-occurrence matrix (GLCM)-based methods. These strategies are presented as a set of potential valuable diagnostic tools for early cancer detection. It may be proposed that the combination of NLO microscopy and informatics based image analysis approaches described in this review (all carried out on free software) may represent a powerful tool to investigate collagen organization and remodeling of extracellular matrix in carcinogenesis processes. PMID:24737930
An intelligent approach for variable size segmentation of non-stationary signals.
Azami, Hamed; Hassanpour, Hamid; Escudero, Javier; Sanei, Saeid
2015-09-01
In numerous signal processing applications, non-stationary signals should be segmented to piece-wise stationary epochs before being further analyzed. In this article, an enhanced segmentation method based on fractal dimension (FD) and evolutionary algorithms (EAs) for non-stationary signals, such as electroencephalogram (EEG), magnetoencephalogram (MEG) and electromyogram (EMG), is proposed. In the proposed approach, discrete wavelet transform (DWT) decomposes the signal into orthonormal time series with different frequency bands. Then, the FD of the decomposed signal is calculated within two sliding windows. The accuracy of the segmentation method depends on these parameters of FD. In this study, four EAs are used to increase the accuracy of segmentation method and choose acceptable parameters of the FD. These include particle swarm optimization (PSO), new PSO (NPSO), PSO with mutation, and bee colony optimization (BCO). The suggested methods are compared with other most popular approaches (improved nonlinear energy operator (INLEO), wavelet generalized likelihood ratio (WGLR), and Varri's method) using synthetic signals, real EEG data, and the difference in the received photons of galactic objects. The results demonstrate the absolute superiority of the suggested approach.
An intelligent approach for variable size segmentation of non-stationary signals
Directory of Open Access Journals (Sweden)
Hamed Azami
2015-09-01
Full Text Available In numerous signal processing applications, non-stationary signals should be segmented to piece-wise stationary epochs before being further analyzed. In this article, an enhanced segmentation method based on fractal dimension (FD and evolutionary algorithms (EAs for non-stationary signals, such as electroencephalogram (EEG, magnetoencephalogram (MEG and electromyogram (EMG, is proposed. In the proposed approach, discrete wavelet transform (DWT decomposes the signal into orthonormal time series with different frequency bands. Then, the FD of the decomposed signal is calculated within two sliding windows. The accuracy of the segmentation method depends on these parameters of FD. In this study, four EAs are used to increase the accuracy of segmentation method and choose acceptable parameters of the FD. These include particle swarm optimization (PSO, new PSO (NPSO, PSO with mutation, and bee colony optimization (BCO. The suggested methods are compared with other most popular approaches (improved nonlinear energy operator (INLEO, wavelet generalized likelihood ratio (WGLR, and Varri’s method using synthetic signals, real EEG data, and the difference in the received photons of galactic objects. The results demonstrate the absolute superiority of the suggested approach.
A simple nonlinear PD controller for integrating processes.
Dey, Chanchal; Mudi, Rajani K; Simhachalam, Dharmana
2014-01-01
Many industrial processes are found to be integrating in nature, for which widely used Ziegler-Nichols tuned PID controllers usually fail to provide satisfactory performance due to excessive overshoot with large settling time. Although, IMC (Internal Model Control) based PID controllers are capable to reduce the overshoot, but little improvement is found in the load disturbance response. Here, we propose an auto-tuning proportional-derivative controller (APD) where a nonlinear gain updating factor α continuously adjusts the proportional and derivative gains to achieve an overall improved performance during set point change as well as load disturbance. The value of α is obtained by a simple relation based on the instantaneous values of normalized error (eN) and change of error (ΔeN) of the controlled variable. Performance of the proposed nonlinear PD controller (APD) is tested and compared with other PD and PID tuning rules for pure integrating plus delay (IPD) and first-order integrating plus delay (FOIPD) processes. Effectiveness of the proposed scheme is verified on a laboratory scale servo position control system.
Non-Stationary Dynamics Data Analysis with Wavelet-Svd Filtering
Brenner, M. J.
2003-07-01
Non-stationary time-frequency analysis is used for identification and classification of aeroelastic and aeroservoelastic dynamics. Time-frequency multiscale wavelet processing generates discrete energy density distributions. The distributions are processed using the singular-value decomposition (SVD). Discrete density functions derived from the SVD generate moments that detect the principal features in the data. The SVD standard basis vectors are applied and then compared with a transformed-SVD, or TSVD, which reduces the number of features into more compact energy density concentrations. Finally, from the feature extraction, wavelet-based modal parameter estimation is applied. The primary objective is the automation of time-frequency analysis with modal system identification. The contribution is a more general approach in which distinct analysis tools are merged into a unified procedure for linear and non-linear data analysis. This method is first applied to aeroelastic pitch-plunge wing section models. Instability is detected in the linear system, and non-linear dynamics are observed from the time-frequency map and parameter estimates of the non-linear system. Aeroelastic and aeroservoelastic flight data from the drone for aerodynamic and structural testing and F18 aircraft are also investigated and comparisons made between the SVD and TSVD results. Input-output data are used to show that this process is an efficient and reliable tool for automated on-line analysis. Published by Elsevier Science Ltd.
Is the Labour Force Participation Rate Non-Stationary in Romania?
Directory of Open Access Journals (Sweden)
Tiwari Aviral Kumar
2015-01-01
Full Text Available The purpose of this paper is to test hysteresis of the Romanian labour force participation rate, by using time series data, with quarterly frequency, covering the period 1999Q1-2013Q4. The main results reveal that the Romanian labour force participation rate is a nonlinear process and has a partial unit root (i.e. it is stationary in the first regime and non-stationary in the second one, the main breaking point being registered around year 2005. In this context, the value of using unemployment rate as an indicator for capturing joblessness in this country is debatable. Starting from 2005, the participation rate has not followed long-term changes in unemployment rate, the disturbances having permanent effects on labour force participation rate.
Non-Stationary Random Response of MDOF Duffing Systems
Directory of Open Access Journals (Sweden)
J.H. Lin
2004-01-01
Full Text Available This paper presents a method to solve non-stationary random responses of nonlinear multi-degrees-of-freedom (MDOF Duffing systems subjected to evolutionary random excitations. Specific phase-lags between the excitations can also be taken into account. The power spectral density (PSD of the input excitations is not confined to simple white noise or filtered white noise, in fact it can also take more complicated forms. The MDOF nonlinear random differential equations are iteratively solved by means of the Equivalent Linearization Method (ELM combined with the Pseudo Excitation Method (PEM. This combined method is easy and efficient. Two examples are given in which this method is well justified by the Monte-Carlo numerical simulations. Although only a Duffing model is dealt with in this paper for computational simplicity, the proposed method is in fact quite general, e.g. it can also deal with nonlinear hysteretic structures that will be dealt with in a separate paper.
Simulation of inhomogeneous, non-stationary and non-Gaussian turbulent winds
DEFF Research Database (Denmark)
Hansen, Kurt Schaldemose
2007-01-01
Turbulence time series are needed for wind turbine load simulation. The multivariate Fourier simulation method often used for this purpose is extended for inhomogeneous and non-stationary processes of general probability distribution. This includes optional conditional simulation matching simulated...... series to field measurements at selected points. A probability model for the application of turbine wind loads is discussed, and finally the technique for non-stationary processes is illustrated by turbulence simulation during a front passage....
Structural Reliability Sensitivities under Nonstationary Random Vibrations
Directory of Open Access Journals (Sweden)
Rita Greco
2013-01-01
Full Text Available Response sensitivity evaluation is an important element in reliability evaluation and design optimization of structural systems. It has been widely studied under static and dynamic forcing conditions with deterministic input data. In this paper, structural response and reliability sensitivities are determined by means of the time domain covariance analysis in both classically and nonclassically damped linear structural systems. A time integration scheme is proposed for covariance sensitivity. A modulated, filtered, white noise input process is adopted to model the stochastic nonstationary loads. The method allows for the evaluation of sensitivity statistics of different quantities of dynamic response with respect to structural parameters. Finally, numerical examples are presented regarding a multistorey shear frame building.
Nonlinear calibration and data processing of the solar radio burst
Institute of Scientific and Technical Information of China (English)
颜毅华; 谭程明; 徐龙; 姬慧荣; 傅其骏; 宋国乡
2002-01-01
The processes of the sudden energy release and energy transfer, and particle accelerations are the most challenge fundamental problems in solar physics as well as in astrophysics. Nowadays, there has been no direct measurement of the plasma parameters and magnetic fields at the coronal energy release site. Under the certain hypothesis of radiation mechanism and transmission process, radio measurement is almost the only method to diagnose coronal magnetic field. The broadband dynamic solar radio spectrometer that has been finished recently in China has higher time and frequency resolutions. Thus it plays an important role during the research of the 23rd solar cycle in China. Sometimes when there were very large bursts, the spectrometer will be overflowed. It needs to take some special process to discriminate the instrument and interference effects from solar burst signals. According to the characteristic of the solar radio broadband dynamic spectrometer, we developed a nonlinear calibration method to deal with the overflow of instrument, and introduced channel-modification method to deal with images. Finally the interference is eliminated with the help of the wavelet method. Here we take the analysis of the well-known solar-terrestrial event on July 14th, 2000 as the example. It shows the feasibility and validity of the method mentioned above. These methods can also be applied to other issues.
Nonlinear closure relations theory for transport processes in nonequilibrium systems.
Sonnino, Giorgio
2009-05-01
A decade ago, a macroscopic theory for closure relations has been proposed for systems out of Onsager's region. This theory is referred to as the thermodynamic field theory (TFT). The aim of this work was to determine the nonlinear flux-force relations that respect the thermodynamic theorems for systems far from equilibrium. We propose a formulation of the TFT where one of the basic restrictions, namely, the closed-form solution for the skew-symmetric piece of the transport coefficients, has been removed. In addition, the general covariance principle is replaced by the De Donder-Prigogine thermodynamic covariance principle (TCP). The introduction of TCP requires the application of an appropriate mathematical formalism, which is referred to as the entropy-covariant formalism. By geometrical arguments, we prove the validity of the Glansdorff-Prigogine universal criterion of evolution. A new set of closure equations determining the nonlinear corrections to the linear ("Onsager") transport coefficients is also derived. The geometry of the thermodynamic space is non-Riemannian. However, it tends to be Riemannian for high values of the entropy production. In this limit, we recover the transport equations found by the old theory. Applications of our approach to transport in magnetically confined plasmas, materials submitted to temperature, and electric potential gradients or to unimolecular triangular chemical reactions can be found at references cited herein. Transport processes in tokamak plasmas are of particular interest. In this case, even in the absence of turbulence, the state of the plasma remains close to (but, it is not in) a state of local equilibrium. This prevents the transport relations from being linear.
Nonlinear properties of and nonlinear processing in hydrogenated amorphous silicon waveguides
DEFF Research Database (Denmark)
Kuyken, B.; Ji, Hua; Clemmen, S.
2011-01-01
We propose hydrogenated amorphous silicon nanowires as a platform for nonlinear optics in the telecommunication wavelength range. Extraction of the nonlinear parameter of these photonic nanowires reveals a figure of merit larger than 2. It is observed that the nonlinear optical properties...... of these waveguides degrade with time, but that this degradation can be reversed by annealing the samples. A four wave mixing conversion efficiency of + 12 dB is demonstrated in a 320 Gbit/s serial optical waveform data sampling experiment in a 4 mm long photonic nanowire....
Nonlinear quantum electrodynamic and electroweak processes in strong laser fields
Energy Technology Data Exchange (ETDEWEB)
Meuren, Sebastian
2015-06-24
Various nonlinear electrodynamic and electroweak processes in strong plane-wave laser fields are considered with an emphasis on short-pulse effects. In particular, the momentum distribution of photoproduced electron-positron pairs is calculated numerically and a semiclassical interpretation of its characteristic features is established. By proving the optical theorem, compact double-integral expressions for the total pair-creation probability are obtained and numerically evaluated. The exponential decay of the photon wave function in a plane wave is included by solving the Schwinger-Dyson equations to leading-order in the quasistatic approximation. In this respect, the polarization operator in a plane wave is investigated and its Ward-Takahashi identity verified. A classical analysis indicates that a photoproduced electron-positron pair recollides for certain initial conditions. The contributions of such recollision processes to the polarization operator are identified and calculated both analytically and numerically. Furthermore, the existence of nontrivial electron-spin dynamics induced by quantum fluctuations is verified for ultra-short laser pulses. Finally, the exchange of weak gauge bosons is considered, which is essential for neutrino-photon interactions. In particular, the axial-vector-vector coupling tensor is calculated and the so-called Adler-Bell-Jackiw (ABJ) anomaly investigated.
All-optical signal processing in quadratic nonlinear materials
DEFF Research Database (Denmark)
Johansen, Steffen Kjær
2002-01-01
of materials with a second order nonlinearity, the so-called X(2) materials, is faster and stronger than that of more conventional materials with a cubic nonlinearity. The X(2) materials support spatial solitons consisting of two coupled components, the fundamental wave (FW) and its second harmonic (SH......). During this project the interaction between such spatial solitons has been investigated theoretically through perturbation theory and experimentally via numerical simulations. The outcome of this research isnew theoretical tools for quantitatively predicting the escape angle, i.e. the angle of incidence...... and exploitation of these cubic nonlinearities in two-period QPM wave-guides has been another area of investigation. Introducing the second period might make practical engineering of the nonlinearities possible. A major result is the discovery that cubic nonlinearities leads to an enhancement of the bandwidth...
Nonstationary modeling of extreme precipitation in China
Gao, Meng; Mo, Dingyuan; Wu, Xiaoqing
2016-12-01
The statistical methods based on extreme value theory have been traditionally used in meteorology and hydrology for a long time. Due to climate change and variability, the hypothesis of stationarity in meteorological or hydrological time series was usually not satisfied. In this paper, a nonstationary extreme value analysis was conducted for annual maximum daily precipitation (AMP) at 631 meteorological stations over China for the period 1951-2013. Stationarity of all 631 AMP time series was firstly tested using KPSS test method, and only 48 AMP time series showed non-stationarity at 5% significance level. The trends of these 48 nonstationary AMP time series were further tested using M-K test method. There were 25 nonstationary AMP time series mainly distributed in southern and western China showing significant positive trend at 5% level. Another 5 nonstationary AMP time series with significant negative trends were near northern urban agglomeration, Sichuan Basin, and central China. For these nonstationary AMP time series with significant positive or negative trends, the location parameter in generalized extreme value (GEV) distribution was assumed to be time-varying, and the trends were successfully characterized by the nonstationary GEV models. For the remaining 18 nonstationary AMP time series mainly in the eastern portion of China, no significant trend was detected. The correlation analysis showed that only 5 nonstationary AMP time series were significantly correlated with one or two of the four climate indices EASMI, WPI, SOI, and PDO. Then, the location and scale parameters in the GEV distribution were modeled as functions of the significantly correlated climate indices. The modeling results in this study showed that the nonstationary GEV distributions performed better than their stationary equivalents. Finally, 20-year and 50-year return levels of precipitation extremes at all 631 stations were estimated using the best fitting distribution for the year 1961
Institute of Scientific and Technical Information of China (English)
LIN Xiangguo; LIANG Yong
2005-01-01
The processing of nonlinear data was one of hot topics in surveying and mapping field in recent years.As a result, many linear methods and nonlinear methods have been developed.But the methods for processing generalized nonlinear surveying and mapping data, especially for different data types and including unknown parameters with random or nonrandom, are seldom noticed.A new algorithm model is presented in this paper for processing nonlinear dynamic multiple-period and multiple-accuracy data derived from deformation monitoring network.
Learning in Non-Stationary Environments Methods and Applications
Lughofer, Edwin
2012-01-01
Recent decades have seen rapid advances in automatization processes, supported by modern machines and computers. The result is significant increases in system complexity and state changes, information sources, the need for faster data handling and the integration of environmental influences. Intelligent systems, equipped with a taxonomy of data-driven system identification and machine learning algorithms, can handle these problems partially. Conventional learning algorithms in a batch off-line setting fail whenever dynamic changes of the process appear due to non-stationary environments and external influences. Learning in Non-Stationary Environments: Methods and Applications offers a wide-ranging, comprehensive review of recent developments and important methodologies in the field. The coverage focuses on dynamic learning in unsupervised problems, dynamic learning in supervised classification and dynamic learning in supervised regression problems. A later section is dedicated to applications in which dyna...
1989-10-30
In this Phase I SBIR study, new methods are developed for the system identification and stochastic filtering of nonlinear controlled Markov processes...state space Markov process models and canonical variate analysis (CVA) for obtaining optimal nonlinear procedures for system identification and stochastic
Application of Novel Nonlinear Optical Materials to Optical Processing
Banerjee, Partha P.
1999-01-01
We describe wave mixing and interactions in nonlinear photorefractive polymers and disodium flourescein. Higher diffracted orders yielding forward phase conjugation can be generated in a two-wave mixing geometry in photorefractive polymers, and this higher order can be used for image edge enhancement and correlation. Four-wave mixing and phase conjugation is studied using nonlinear disodium floureschein, and the nature and properties of gratings written in this material are investigated.
Equilibrium theory-based analysis of nonlinear waves in separation processes.
Mazzotti, Marco; Rajendran, Arvind
2013-01-01
Different areas of engineering, particularly separation process technology, deal with one-dimensional, nonstationary processes that under reasonable assumptions, namely negligible dispersion effects and transport resistances, are described by mathematical models consisting of systems of first-order partial differential equations. Their behavior is characterized by continuous or discontinuous composition (or thermal) fronts that propagate along the separation unit. The equilibrium theory (i.e., the approach discussed here to determine the solution to these model equations) predicts this with remarkable accuracy, despite the simplifications and assumptions. Interesting applications are in adsorption, chromatography and ion-exchange, distillation, gas injection, heat storage, sedimentation, precipitation, and dissolution waves. We show how mathematics can enlighten the engineering aspects, and we guide the researcher not only to reach a synthetic understanding of properties of fundamental and applicative interest but also to discover new, unexpected, and fascinating phenomena. The tools presented here are useful to teachers, researchers, and practitioners alike.
Thin viscoelastic disc subjected to radial non-stationary loading
Directory of Open Access Journals (Sweden)
Adámek V.
2010-07-01
Full Text Available The investigation of non-stationary wave phenomena in isotropic viscoelastic solids using analytical approaches is the aim of this paper. Concretely, the problem of a thin homogeneous disc subjected to radial pressure load nonzero on the part of its rim is solved. The external excitation is described by the Heaviside function in time, so the nonstationary state of stress is induced in the disc. Dissipative material behaviour of solid studied is represented by the discrete material model of standard linear viscoelastic solid in the Zener configuration. After the derivation of motion equations final form, the method of integral transforms in combination with the Fourier method is used for finding the problem solution. The solving process results in the derivation of integral transforms of radial and circumferential displacement components. Finally, the type of derived functions singularities and possible methods for their inverse Laplace transform are mentioned.
Non-Stationary Dependence Structures for Spatial Extremes
Huser, Raphaël
2016-03-03
Max-stable processes are natural models for spatial extremes because they provide suitable asymptotic approximations to the distribution of maxima of random fields. In the recent past, several parametric families of stationary max-stable models have been developed, and fitted to various types of data. However, a recurrent problem is the modeling of non-stationarity. In this paper, we develop non-stationary max-stable dependence structures in which covariates can be easily incorporated. Inference is performed using pairwise likelihoods, and its performance is assessed by an extensive simulation study based on a non-stationary locally isotropic extremal t model. Evidence that unknown parameters are well estimated is provided, and estimation of spatial return level curves is discussed. The methodology is demonstrated with temperature maxima recorded over a complex topography. Models are shown to satisfactorily capture extremal dependence.
Mapping the nonstationary internal tide with satellite altimetry
Zaron, Edward D.
2017-01-01
Temporal variability of the internal tide has been inferred from the 23 year long combined records of the TOPEX/Poseidon, Jason-1, and Jason-2 satellite altimeters by combining harmonic analysis with an analysis of along-track wavenumber spectra of sea-surface height (SSH). Conventional harmonic analysis is first applied to estimate and remove the stationary components of the tide at each point along the reference ground tracks. The wavenumber spectrum of the residual SSH is then computed, and the variance in a neighborhood around the wavenumber of the mode-1 baroclinic M2 tide is interpreted as the sum of noise, broadband nontidal processes, and the nonstationary tide. At many sites a bump in the spectrum associated with the internal tide is noted, and an empirical model for the noise and nontidal processes is used to estimate the nonstationary semidiurnal tidal variance. The results indicate a spatially inhomogeneous pattern of tidal variability. Nonstationary tides are larger than stationary tides throughout much of the equatorial Pacific and Indian Oceans.
Nonlinear Model Algorithmic Control of a pH Neutralization Process
Institute of Scientific and Technical Information of China (English)
ZOU Zhiyun; YU Meng; WANG Zhizhen; LIU Xinghong; GUO Yuqing; ZHANG Fengbo; GUO Ning
2013-01-01
Control of pH neutralization processes is challenging in the chemical process industry because of their inherent strong nonlinearity.In this paper,the model algorithmic control (MAC) strategy is extended to nonlinear processes using Hammerstein model that consists of a static nonlinear polynomial function followed in series by a linear impulse response dynamic element.A new nonlinear Hammerstein MAC algorithm (named NLH-MAC) is presented in detail.The simulation control results of a pH neutralization process show that NLH-MAC gives better control performance than linear MAC and the commonly used industrial nonlinear propotional plus integral plus derivative (PID) controller.Further simulation experiment demonstrates that NLH-MAC not only gives good control response,but also possesses good stability and robustness even with large modeling errors.
Femtosecond Fiber Lasers Based on Dissipative Processes for Nonlinear Microscopy
Wise, Frank W.
2012-01-01
Recent progress in the development of femtosecond-pulse fiber lasers with parameters appropriate for nonlinear microscopy is reviewed. Pulse-shaping in lasers with only normal-dispersion components is briefly described, and the performance of the resulting lasers is summarized. Fiber lasers based on the formation of dissipative solitons now offer performance competitive with that of solid-state lasers, but with the benefits of the fiber medium. Lasers based on self-similar pulse evolution in the gain section of a laser also offer a combination of short pulse duration and high pulse energy that will be attractive for applications in nonlinear bioimaging. PMID:23869163
Nonlinear projective filtering in a data stream
Schreiber, T; Schreiber, Thomas; Richter, Marcus
1998-01-01
We introduce a modified algorithm to perform nonlinear filtering of a time series by locally linear phase space projections. Unlike previous implementations, the algorithm can be used not only for a posteriori processing but includes the possibility to perform real time filtering in a data stream. The data base that represents the phase space structure generated by the data is updated dynamically. This also allows filtering of non-stationary signals and dynamic parameter adjustment. We discuss exemplary applications, including the real time extraction of the fetal electrocardiogram from abdominal recordings.
Mikhailov, V; E. Strock
2013-01-01
In the paper mathematical model of steering system is shown. The model was described through hydraulic and mechanical connections of differential equations. Some test results are represented.This model allows to analyze transient processes in different combination of kinematics disturbances and power factors, and also to determine functional suitability of System.This Model can be recommended for Control System testing.
2013-01-01
This book consists of twenty seven chapters, which can be divided into three large categories: articles with the focus on the mathematical treatment of non-linear problems, including the methodologies, algorithms and properties of analytical and numerical solutions to particular non-linear problems; theoretical and computational studies dedicated to the physics and chemistry of non-linear micro-and nano-scale systems, including molecular clusters, nano-particles and nano-composites; and, papers focused on non-linear processes in medico-biological systems, including mathematical models of ferments, amino acids, blood fluids and polynucleic chains.
Gómez-Polo, C.; Duque, J. G. S.; Knobel, M.
2004-07-01
The magnetoimpedance effect and its nonlinear terms are analysed for a (Co0.94Fe0.06)72.5Si12.5B15 amorphous wire. In order to enhance the nonlinear contribution the sample was previously subjected to current annealing (Joule heating) to induce a circumferential anisotropy. The effect of the application of a torsional strain on the nonlinear magnetoimpedance is analysed in terms of the torsional dependence of the magnetic permeability, evaluated through experimental circumferential hysteresis loops. The results obtained clearly confirm the direct correlation between the asymmetric circumferential magnetization process and the occurrence of nonlinear second-harmonic terms in the magnetoimpedance voltage.
Neural Generalized Predictive Control of a non-linear Process
DEFF Research Database (Denmark)
Sørensen, Paul Haase; Nørgård, Peter Magnus; Ravn, Ole
1998-01-01
qualities. The controller is a non-linear version of the well-known generalized predictive controller developed in linear control theory. It involves minimization of a cost function which in the present case has to be done numerically. Therefore, we develop the numerical algorithms necessary in substantial...
Directory of Open Access Journals (Sweden)
V. Mikhailov
2013-01-01
Full Text Available In the paper mathematical model of steering system is shown. The model was described through hydraulic and mechanical connections of differential equations. Some test results are represented.This model allows to analyze transient processes in different combination of kinematics disturbances and power factors, and also to determine functional suitability of System.This Model can be recommended for Control System testing.
2011-10-01
applications, Spinger -Verlag, 1989. Fig. 7.11. Two dimensional marginal chains for parameters m5,m6,m7,m8. The Gaussian process predictor is obtained after ten...43 (2005), pp. 1306–1315. [48] Radford M. Neal, Bayesian learning for neural networks, Spinger -Verlag, 1996. [49] Ngoc Cuong Nguyen, An uncertainty...J. Santner, Brian J. Williams, and William I. Notz, The Design and Analysis of Computer Experiments, Spinger -Verlag, 2003. [60] Alexandra M. Schmidt
A Nonlinear Approach to Tunisian Inflation Rate
Directory of Open Access Journals (Sweden)
Thouraya Boujelbène Dammak
2016-09-01
Full Text Available In this study, we investigated the properties and the macroeconomic performance of the nonlinearity of the Inflation Rate Set in Tunisia. We developed an inference asymptotic theory for an unrestricted two-regime threshold autoregressive (TAR model with an autoregressive unit root. We proposed two types of tests namely asymptotic and bootstrap-based. These tests as well as the distribution theory allow a joint consideration of nonlinear thresholds and non-stationary unit roots. Our empirical results reveal a strong evidence of a threshold effect. This makes clear the possibility of non stationary and nonlinear of the Monthly Inflation Rate in Tunisia for the 1994.01-2011.06 period. While the Perron test found a unit root, our TAR unit root tests are arguably significant. Then, the evidence is quite strong that the inflation rate is not a unit root process.
Schillinger, Dominik
2013-07-01
The method of separation can be used as a non-parametric estimation technique, especially suitable for evolutionary spectral density functions of uniformly modulated and strongly narrow-band stochastic processes. The paper at hand provides a consistent derivation of method of separation based spectrum estimation for the general multi-variate and multi-dimensional case. The validity of the method is demonstrated by benchmark tests with uniformly modulated spectra, for which convergence to the analytical solution is demonstrated. The key advantage of the method of separation is the minimization of spectral dispersion due to optimum time- or space-frequency localization. This is illustrated by the calibration of multi-dimensional and multi-variate geometric imperfection models from strongly narrow-band measurements in I-beams and cylindrical shells. Finally, the application of the method of separation based estimates for the stochastic buckling analysis of the example structures is briefly discussed. © 2013 Elsevier Ltd.
Nonlinear analysis and control of a continuous fermentation process
DEFF Research Database (Denmark)
Szederkényi, G.; Kristensen, Niels Rode; Hangos, K.M
2002-01-01
open-loop system properties, to explore the possible control difficulties and to select the system output to be used in the control structure. A wide range of controllers are tested including pole placement and LQ controllers, feedback and input–output linearization controllers and a nonlinear...... controller based on direct passivation. The comparison is based on time-domain performance and on investigating the stability region, robustness and tuning possibilities of the controllers. Controllers using partial state feedback of the substrate concentration and not directly depending on the reaction rate...... are recommended for the simple fermenter. Passivity based controllers have been found to be globally stable, not very sensitive to the uncertainties in the reaction rate and controller parameter but they require full nonlinear state feedback....
Photonic Crystal Nanocavity Devices for Nonlinear Signal Processing
DEFF Research Database (Denmark)
Yu, Yi
, membranization of InP/InGaAs structure and wet etching. Experimental investigation of the switching dynamics of InP photonic crystal nanocavity structures are carried out using short-pulse homodyne pump-probe techniques, both in the linear and nonlinear region where the cavity is perturbed by a relatively small......This thesis deals with the investigation of InP material based photonic crystal cavity membrane structures, both experimentally and theoretically. The work emphasizes on the understanding of the physics underlying the structures’ nonlinear properties and their applications for all-optical signal...... and large pump power. The experimental results are compared with coupled mode equations developed based on the first order perturbation theory, and carrier rate equations we established for the dynamics of the carrier density governing the cavity properties. The experimental observations show a good...
Neural Generalized Predictive Control of a non-linear Process
DEFF Research Database (Denmark)
Sørensen, Paul Haase; Nørgård, Peter Magnus; Ravn, Ole
1998-01-01
The use of neural network in non-linear control is made difficult by the fact the stability and robustness is not guaranteed and that the implementation in real time is non-trivial. In this paper we introduce a predictive controller based on a neural network model which has promising stability...... detail and discuss the implementation difficulties. The neural generalized predictive controller is tested on a pneumatic servo sys-tem....
Analysis of nonstationary modulated time series with applications to oceanographic flow measurements
Guillaumin, Arthur P; Olhede, Sofia C; Early, Jeffrey J; Lilly, Jonathan M
2016-01-01
We extend the concept of a modulated nonstationary process to account for rapidly time-evolving correlation structure. This correlation varies sufficiently fast to make existing theory for nonstationary processes not applicable. The rapid variation in the correlations challenges state-of-the-art methods to make inferences. Even for stationary processes, exact inference in the time domain is often not computa- tionally viable. A well-established and fast approximation, known as the Whittle likelihood, is used as a pseudo-likelihood approach. We discuss how the Whittle likelihood can be extended to our given class of nonstationary modulated processes. Simulation studies reveal the power of our proposed methodology. We demonstrate the performance of our method on the analysis of ocean surface currents measured by freely-drifting instruments, a dataset which is pivotal to understanding global climate patterns.
Nonstationary Dynamics Data Analysis with Wavelet-SVD Filtering
Brenner, Marty; Groutage, Dale; Bessette, Denis (Technical Monitor)
2001-01-01
Nonstationary time-frequency analysis is used for identification and classification of aeroelastic and aeroservoelastic dynamics. Time-frequency multiscale wavelet processing generates discrete energy density distributions. The distributions are processed using the singular value decomposition (SVD). Discrete density functions derived from the SVD generate moments that detect the principal features in the data. The SVD standard basis vectors are applied and then compared with a transformed-SVD, or TSVD, which reduces the number of features into more compact energy density concentrations. Finally, from the feature extraction, wavelet-based modal parameter estimation is applied.
Dynamics of breathers in discrete nonlinear Schrodinger models
DEFF Research Database (Denmark)
Christiansen, Peter Leth; Johansson, Magnus; Aubry, Serge
1998-01-01
We review some recent results concerning the existence and stability of spatially localized and temporally quasiperiodic (non-stationary) excitations in discrete nonlinear Schrodinger (DNLS) models. In two dimensions, we show the existence of linearly stable, stationary and non-stationary localized...
Real-Time Implementation of Nonlinear Optical Processing Functions.
1986-09-30
demonstrating that the memory is nonlinear and selective. The recording medium could be replaced with real-time media such as photorefractive crystals. Thicker...recording media Fi4 4. Schematic of experiment that d,.non* trated ,,pera have the added advantage of higher angular selectiv- "" . e e r aity. thus... geometrica snapes in contact ’A,.n a c-:’:ser ’Figure 51a’ ., and a spher:cal 4:verg.ng reference -eam Upion :"um’latlon of t -" c-’gram by the object beam
Cultural evolution as a nonstationary stochastic process
DEFF Research Database (Denmark)
Nicholson, Arwen; Sibani, Paolo
2016-01-01
We present an individual based model of cultural evolution, where interacting agents are coded by binary strings standing for strategies for action, blueprints for products or attitudes and beliefs. The model is patterned on an established model of biological evolution, the Tangled Nature Model (...... qualitatively reproduce the flurry of cultural activity which follows a disruptive innovation....
Nonstationary processes in the rail gun channel
Vompe, A. G.; Kovalev, V. L.
1993-06-01
An analysis is made of the response of the plasma-projectile system to an abrupt change in current density and to mass injection. Calculations are carried out using the numerical method developed by Zvezdin and Kovalev (1992) for investigating the motion of plasma and the accelerated body. It is found that every case considered involves attenuating oscillations about the stationary solution. A comparison with data in the literature demonstrates good convergence of the results.
Approaches to handle nonlinearities and nonnormalities in process chemometrics
Thissen, Uwe Maria Johannes
2004-01-01
For every industrial process, it is of paramount interest to online monitor the performance of the process and to assess the quality of the products made. In order to meet these goals, the field of process control works on understanding and improving industrial processes. Process chemometrics can be
A nonlinear optoelectronic filter for electronic signal processing
Loh, William; Yegnanarayanan, Siva; Ram, Rajeev J.; Juodawlkis, Paul W.
2014-01-01
The conversion of electrical signals into modulated optical waves and back into electrical signals provides the capacity for low-loss radio-frequency (RF) signal transfer over optical fiber. Here, we show that the unique properties of this microwave-photonic link also enable the manipulation of RF signals beyond what is possible in conventional systems. We achieve these capabilities by realizing a novel nonlinear filter, which acts to suppress a stronger RF signal in the presence of a weaker signal independent of their separation in frequency. Using this filter, we demonstrate a relative suppression of 56 dB for a stronger signal having a 1-GHz center frequency, uncovering the presence of otherwise undetectable weaker signals located as close as 3.5 Hz away. The capabilities of the optoelectronic filter break the conventional limits of signal detection, opening up new possibilities for radar and communication systems, and for the field of precision frequency metrology. PMID:24402418
Nonlinear model predictive control for chemical looping process
Energy Technology Data Exchange (ETDEWEB)
Joshi, Abhinaya; Lei, Hao; Lou, Xinsheng
2017-08-22
A control system for optimizing a chemical looping ("CL") plant includes a reduced order mathematical model ("ROM") that is designed by eliminating mathematical terms that have minimal effect on the outcome. A non-linear optimizer provides various inputs to the ROM and monitors the outputs to determine the optimum inputs that are then provided to the CL plant. An estimator estimates the values of various internal state variables of the CL plant. The system has one structure adapted to control a CL plant that only provides pressure measurements in the CL loops A and B, a second structure adapted to a CL plant that provides pressure measurements and solid levels in both loops A, and B, and a third structure adapted to control a CL plant that provides full information on internal state variables. A final structure provides a neural network NMPC controller to control operation of loops A and B.
Institute of Scientific and Technical Information of China (English)
Yun Li; Hiroshi Kashiwagi
2005-01-01
Model Predictive Control (MPC) has recently found wide acceptance in the process industry, but existing design and implementation methods are restricted to linear process models. A chemical process, however, involves severe nonlinearity which cannot be ignored in practice. This paper aims to solve this nonlinear control problem by extending MPC to accommodate nonlinear models. It develops an analytical framework for nonlinear model predictive control (NMPC). It also offers a third-order Volterra series based nonparametric nonlinear modelling technique for NMPC design, which relieves practising engineers from the need for deriving a physical-principles based model first. An on-line realisation technique for implementing NMPC is then developed and applied to a Mitsubishi Chemicals polymerisation reaction process. Results show that this nonlinear MPC technique is feasible and very effective. It considerably outperforms linear and low-order Volterra model based methods. The advantages of the developed approach lie not only in control performance superior to existing NMPC methods, but also in eliminating the need for converting an analytical model and then convert it to a Volterra model obtainable only up to the second order.
Lavdas, Spyros; You, Jie; Osgood, Richard M.; Panoiu, Nicolae C.
2015-08-01
We present recent results pertaining to pulse reshaping and optical signal processing using optical nonlinearities of silicon-based tapered photonic wires and photonic crystal waveguides. In particular, we show how nonlinearity and dispersion engineering of tapered photonic wires can be employed to generate optical similaritons and achieve more than 10× pulse compression. We also discuss the properties of four-wave mixing pulse amplification and frequency conversion efficiency in long-period Bragg waveguides and photonic crystal waveguides. Finally, the influence of linear and nonlinear optical effects on the transmission bit-error rate in uniform photonic wires and photonic crystal waveguides made of silicon is discussed.
Blind Image Deblurring Driven by Nonlinear Processing in the Edge Domain
Directory of Open Access Journals (Sweden)
Stefania Colonnese
2004-12-01
Full Text Available This work addresses the problem of blind image deblurring, that is, of recovering an original image observed through one or more unknown linear channels and corrupted by additive noise. We resort to an iterative algorithm, belonging to the class of Bussgang algorithms, based on alternating a linear and a nonlinear image estimation stage. In detail, we investigate the design of a novel nonlinear processing acting on the Radon transform of the image edges. This choice is motivated by the fact that the Radon transform of the image edges well describes the structural image features and the effect of blur, thus simplifying the nonlinearity design. The effect of the nonlinear processing is to thin the blurred image edges and to drive the overall blind restoration algorithm to a sharp, focused image. The performance of the algorithm is assessed by experimental results pertaining to restoration of blurred natural images.
Data Analysis Techniques for Resolving Nonlinear Processes in Plasmas : a Review
de Wit, T. Dudok
1996-01-01
The growing need for a better understanding of nonlinear processes in plasma physics has in the last decades stimulated the development of new and more advanced data analysis techniques. This review lists some of the basic properties one may wish to infer from a data set and then presents appropriate analysis techniques with some recent applications. The emphasis is put on the investigation of nonlinear wave phenomena and turbulence in space plasmas.
Simulations of the Ocean Response to a Hurricane: Nonlinear Processes
Zedler, Sarah E.
2009-10-01
Superinertial internal waves generated by a tropical cyclone can propagate vertically and laterally away from their local generation site and break, contributing to turbulent vertical mixing in the deep ocean and maintenance of the stratification of the main thermocline. In this paper, the results of a modeling study are reported to investigate the mechanism by which superinertial fluctuations are generated in the deep ocean. The general properties of the superinertial wave wake were also characterized as a function of storm speed and central latitude. The Massachusetts Institute of Technology (MIT) Ocean General Circulation Model (OGCM) was used to simulate the open ocean response to realistic westward-tracking hurricane-type surface wind stress and heat and net freshwater buoyancy forcing for regions representative of midlatitudes in the Atlantic, the Caribbean, and low latitudes in the eastern Pacific. The model had high horizontal [Δ(x, y) = 1/6°] and vertical (Δz = 5 m in top 100 m) resolution and employed a parameterization for vertical mixing induced by shear instability. In the horizontal momentum equation, the relative size of the nonlinear advection terms, which had a dominant frequency near twice the inertial, was large only in the upper 200 m of water. Below 200 m, the linear momentum equations obeyed a linear balance to 2%. Fluctuations at nearly twice the inertial frequency (2f) were prevalent throughout the depth of the water column, indicating that these nonlinear advection terms in the upper 200 m forced a linear mode below at nearly twice the inertial frequency via vorticity conservation. Maximum variance at 2f in horizontal velocity occurred on the south side of the track. This was in response to vertical advection of northward momentum, which in the north momentum equation is an oscillatory positive definite term that constituted a net force to the south at a frequency near 2f. The ratio of this term to the Coriolis force was larger on the
Nonlinearities in the quantum measurement process of superconducting qubits
Energy Technology Data Exchange (ETDEWEB)
Serban, Ioana
2008-05-15
The work described in this thesis focuses on the investigation of decoherence and measurement backaction, on the theoretical description of measurement schemes and their improvement. The study presented here is centered around quantum computing implementations using superconducting devices and most important, the Josephson effect. The measured system is invariantly a qubit, i. e. a two-level system. The objective is to study detectors with increasing nonlinearity, e. g. coupling of the qubit to the frequency a driven oscillator, or to the bifurcation amplifier, to determine the performance and backaction of the detector on the measured system and to investigate the importance of a strong qubit-detector coupling for the achievement of a quantum non-demolition type of detection. The first part gives a very basic introduction to quantum information, briefly reviews some of the most promising physical implementations of a quantum computer before focusing on the superconducting devices. The second part presents a series of studies of different qubit measurements, describing the backaction of the measurement onto the measured system and the internal dynamics of the detector. Methodology adapted from quantum optics and chemical physics (master equations, phase-space analysis etc.) combined with the representation of a complex environment yielded a tool capable of describing a nonlinear, non-Markovian environment, which couples arbitrarily strongly to the measured system. This is described in chapter 3. Chapter 4 focuses on the backaction on the qubit and presents novel insights into the qubit dephasing in the strong coupling regime. Chapter 5 uses basically the same system and technical tools to explore the potential of a fast, strong, indirect measurement, and determine how close such a detection would ideally come to the quantum non-demolition regime. Chapter 6 focuses on the internal dynamics of a strongly driven Josephson junction. The analytical results are based on
Kannan, Rohit; Tangirala, Arun K.
2014-06-01
Identification of directional influences in multivariate systems is of prime importance in several applications of engineering and sciences such as plant topology reconstruction, fault detection and diagnosis, and neurosciences. A spectrum of related directionality measures, ranging from linear measures such as partial directed coherence (PDC) to nonlinear measures such as transfer entropy, have emerged over the past two decades. The PDC-based technique is simple and effective, but being a linear directionality measure has limited applicability. On the other hand, transfer entropy, despite being a robust nonlinear measure, is computationally intensive and practically implementable only for bivariate processes. The objective of this work is to develop a nonlinear directionality measure, termed as KPDC, that possesses the simplicity of PDC but is still applicable to nonlinear processes. The technique is founded on a nonlinear measure called correntropy, a recently proposed generalized correlation measure. The proposed method is equivalent to constructing PDC in a kernel space where the PDC is estimated using a vector autoregressive model built on correntropy. A consistent estimator of the KPDC is developed and important theoretical results are established. A permutation scheme combined with the sequential Bonferroni procedure is proposed for testing hypothesis on absence of causality. It is demonstrated through several case studies that the proposed methodology effectively detects Granger causality in nonlinear processes.
Institute of Scientific and Technical Information of China (English)
TAO Hua-xue (陶华学); GUO Jin-yun (郭金运)
2003-01-01
Data are very important to build the digital mine. Data come from many sources, have different types and temporal states. Relations between one class of data and the other one, or between data and unknown parameters are more nonlinear. The unknown parameters are non-random or random, among which the random parameters often dynamically vary with time. Therefore it is not accurate and reliable to process the data in building the digital mine with the classical least squares method or the method of the common nonlinear least squares. So a generalized nonlinear dynamic least squares method to process data in building the digital mine is put forward. In the meantime, the corresponding mathematical model is also given. The generalized nonlinear least squares problem is more complex than the common nonlinear least squares problem and its solution is more difficultly obtained because the dimensions of data and parameters in the former are bigger. So a new solution model and the method are put forward to solve the generalized nonlinear dynamic least squares problem. In fact, the problem can be converted to two sub-problems, each of which has a single variable. That is to say, a complex problem can be separated and then solved. So the dimension of unknown parameters can be reduced to its half, which simplifies the original high dimensional equations. The method lessens the calculating load and opens up a new way to process the data in building the digital mine, which have more sources, different types and more temporal states.
Non-stationary probabilistic characterization of drought events
Bonaccorso, Brunella; Cancelliere, Antonino
2016-04-01
Probabilistic characterization of droughts is an essential step for designing and implementing appropriate mitigation strategies. Traditionally, probabilistic characterization of droughts has been carried out assuming stationarity for the underlying hydrological series. In particular, under the stationary framework, probability distributions and moments of hydrological processes are assumed to be invariant with time. However many studies in the past decades have highlighted the presence of non-stationary patterns (such as trends or shifts) in hydrological records, leading to question the stationarity paradigm. Regardless of the causes (either anthropogenic or natural), the need arises to develop new statistical concepts and tools able to deal with such non-stationarity. In the present work, an analytical framework for deriving probabilities and return periods of droughts, assuming non-stationarity in the underlying hydrological series, is developed. In particular, exact and approximate analytical expressions for the moments and probability distributions of drought characteristics (i.e. length and accumulated deficit), are derived as a function of the non-stationary probability distribution of the hydrological process under investigation, as well as of the threshold level. Furthermore, capitalizing on previous developments suggested in the statistical and climate change literature, the concept of return period is revisited to take into account non-stationarity, as well as the multivariate nature of droughts which requires to consider different characteristics simultaneously. The derived expressions are applied to several precipitation series in Sicily Italy, exhibiting trends. Results indicate the feasibility of the proposed methodology to compute probabilities and return periods of drought characteristics in a non-stationary context.
NON-STATIONARY STOKES FLOWS UNDER LEAK BOUNDARY CONDITIONS OF FRICTION TYPE
Institute of Scientific and Technical Information of China (English)
Hiroshi Fujita
2001-01-01
This paper is concerned with the initial value problem for non-stationary Stokes flows,under a certain non-linear boundary condition which can be called the leak boundarycondition of friction type. Theoretically, our main purpose is to show the strong solvability(i.e.,the unique existence of the L2-strong solution) of this initial value problem by meansof the non-linear semi-group theory originated with Y. Komura. The method of analysiscan be applied to other boundary or interface conditions of friction type. It should benoted that the result yields a sound basis of simulation methods for evolution problemsinvolving these conditions.
The Study of a New Method for Forecasting Non-stationary Series
Institute of Scientific and Technical Information of China (English)
无
2002-01-01
A new method for forecasting non-stationary series is developed. Its steps are as follows: Step 1. Data delaminating. Non-stationary series is delaminated into several multi-scale steady data layers and one trend layer. Step 2. Modeling and forecasting each stationary data layer. Step 3. Imitating trend layer using polynomial. Step 4. Combining the forecasting layers and imitating layer into one series. The EMD (Empirical Mode Decomposition) method suitable to process non-stationary series is selected to delaminate data, while ARMA (Auto Regressive Moving Average) model is employed to model and forecast stationary data layer and least square error method for trend layer regression. Aiming at forecasting length, forecasting orientation and selective method, experiments are performed for SAR (Synthetic Aperture Radar) images. Finally, an example is provided, in which the whole SAR image is restored via the method proposed by this paper.
Shinkawa, Mizuki; Ishikura, Norihiro; Hama, Yosuke; Suzuki, Keijiro; Baba, Toshihiko
2011-10-24
We have studied low-dispersion slow light and its nonlinear enhancement in photonic crystal waveguides. In this work, we fabricated the waveguides using Si CMOS-compatible process. It enables us to integrate spotsize converters, which greatly simplifies the optical coupling from fibers as well as demonstration of the nonlinear enhancement. Two-photon absorption, self-phase modulation and four-wave mixing were observed clearly for picosecond pulses in a 200-μm-long device. In comparison with Si wire waveguides, a 60-120 fold higher nonlinearity was evaluated for a group index of 51. Unique intensity response also occurred due to the specific transmission spectrum and enhanced nonlinearities. Such slow light may add various functionalities in Si photonics, while loss reduction is desired for ensuring the advantage of slow light.
Nonlinear Transport Processes in Tokamak Plasmas. Part I: The Collisional Regimes
Sonnino, Giorgio
2008-01-01
An application of the thermodynamic field theory (TFT) to transport processes in L-mode tokamak plasmas is presented. The nonlinear corrections to the linear (Onsager) transport coefficients in the collisional regimes are derived. A quite encouraging result is the appearance of an asymmetry between the Pfirsch-Schlueter (P-S) ion and electron transport coefficients: the latter presents a nonlinear correction, which is absent for the ions, and makes the radial electron coefficients much larger than the former. Explicit calculations and comparisons between the neoclassical results and the TFT predictions for JET plasmas are also reported. We found that the nonlinear electron P-S transport coefficients exceed the values provided by neoclassical theory by a factor, which may be of the order 100. The nonlinear classical coefficients exceed the neoclassical ones by a factor, which may be of order 2. The expressions of the ion transport coefficients, determined by the neoclassical theory in these two regimes, remain...
Institute of Scientific and Technical Information of China (English)
Xiao Li; Zhang Wei; Huang Yi-Dong; Peng Jiang-De
2008-01-01
High nonlinear microstructure fibre (HNMF) is preferred in nonlinear fibre optics, especially in the applications of optical parametric effects, due to its high optical nonlinear coefficient. However, polarization dependent dispersion will impact the nonlinear optical parametric process in HNMFs. In this paper, modulation instability (MI) method is used to measure the polarization dependent dispersion of a piece of commercial HNMF, including the group velocity dispersion, the dispersion slope, the fourth-order dispersion and group birefringence. It also experimentally demonstrates the impact of the polarization dependent dispersion on the continuous wave supercontinuum (SC) generation. On one axis MI sidebands with symmetric frequency dctunings are generated, while on the other axis with larger MI frequency detuning, SC is generated by soliton self-frequency shift.
Leydesdorff, L.; Rotolo, D.; de Nooy, W.
2013-01-01
The process of innovation follows nonlinear patterns across the domains of science, technology, and the economy. Novel bibliometric mapping techniques can be used to investigate and represent distinctive, but complementary perspectives on the innovation process (e.g. ‘demand’ and ‘supply’) as well
Quasilinear Extreme Learning Machine Model Based Internal Model Control for Nonlinear Process
Directory of Open Access Journals (Sweden)
Dazi Li
2015-01-01
Full Text Available A new strategy for internal model control (IMC is proposed using a regression algorithm of quasilinear model with extreme learning machine (QL-ELM. Aimed at the chemical process with nonlinearity, the learning process of the internal model and inverse model is derived. The proposed QL-ELM is constructed as a linear ARX model with a complicated nonlinear coefficient. It shows some good approximation ability and fast convergence. The complicated coefficients are separated into two parts. The linear part is determined by recursive least square (RLS, while the nonlinear part is identified through extreme learning machine. The parameters of linear part and the output weights of ELM are estimated iteratively. The proposed internal model control is applied to CSTR process. The effectiveness and accuracy of the proposed method are extensively verified through numerical results.
Liu, Gang; Mao, Zhu; Todd, Michael
2016-11-01
This paper proposes a damage detection method based on the geometrical variation of transient trajectories in phase-space, and the proposed methodology is compatible with non-stationary excitations (e.g., earthquake-induced ground motion). The work presented assumes zero-mean non-stationary excitation, and extends the random decrement technique to convert non-stationary response signals of the structure into free-vibration data. Transient trajectories of the structure are reconstructed via the embedding theorem from the converted free-vibration data, and trajectories are mapped successively into phase-space to enhance statistical analysis. Based upon the characterized system dynamics in terms of phase-space, the time prediction error is adopted as the damage index. To identify the presence and severity of damage in a statistically rigorous way, receiver operating characteristic curves and the Bhattacharyya distance are employed. The results from both numerical simulations and experiments validate the proposed framework, when the test structures are subject to non-stationary excitations. The extension achieved in this paper enables the phase-space damage detection approach to be compatible with non-stationary scenarios, such as traffic, wind, and earthquake loadings. Moreover, the results indicate that this phase-state-based method is able to identify damage-induced nonlinearity in response, which is an intrinsic characteristic associated with most structural damage types.
A fuzzy model based adaptive PID controller design for nonlinear and uncertain processes.
Savran, Aydogan; Kahraman, Gokalp
2014-03-01
We develop a novel adaptive tuning method for classical proportional-integral-derivative (PID) controller to control nonlinear processes to adjust PID gains, a problem which is very difficult to overcome in the classical PID controllers. By incorporating classical PID control, which is well-known in industry, to the control of nonlinear processes, we introduce a method which can readily be used by the industry. In this method, controller design does not require a first principal model of the process which is usually very difficult to obtain. Instead, it depends on a fuzzy process model which is constructed from the measured input-output data of the process. A soft limiter is used to impose industrial limits on the control input. The performance of the system is successfully tested on the bioreactor, a highly nonlinear process involving instabilities. Several tests showed the method's success in tracking, robustness to noise, and adaptation properties. We as well compared our system's performance to those of a plant with altered parameters with measurement noise, and obtained less ringing and better tracking. To conclude, we present a novel adaptive control method that is built upon the well-known PID architecture that successfully controls highly nonlinear industrial processes, even under conditions such as strong parameter variations, noise, and instabilities.
Non-linear thermodynamic laws application to soil processes
Directory of Open Access Journals (Sweden)
Ilgiz Khabirov
2013-01-01
Full Text Available An attempt has been made to analyze the possibility to use nonequilibrium thermodynamics for the soil dynamic open systemstreatment. Entropy change of such a system and the entropy coming from or going into the outer sphere. In the steady state, dynamic soil-formation processes occur within an organized structure and are characterized by stable parameters close to equilibrium. Accordingly, when examining soil, one can proceed from the conventional thermodynamic equilibrium. However, the matter of Onzager-Prigozhin general phenomenological theory applicability to soil processes is more complicated. To study soil stability it is necessary to go beyond the limits of linear thermodynamics.
Nonlinear processes upon two-photon interband picosecond excitation of PbWO4 crystal
Lukanin, V. I.; Karasik, A. Ya
2016-09-01
A new experimental method is proposed to study the dynamics of nonlinear processes occurring upon two-photon interband picosecond excitation of a lead tungstate crystal and upon its excitation by cw probe radiation in a temporal range from several nanoseconds to several seconds. The method is applied to the case of crystal excitation by a sequence of 25 high-power picosecond pulses with a wavelength of 523.5 nm and 633-nm cw probe radiation. Measuring the probe beam transmittance during crystal excitation, one can investigate the influence of two-photon interband absorption and the thermal nonlinearity of the refractive index on the dynamics of nonlinear processes in a wide range of times (from several nanoseconds to several seconds). The time resolution of the measuring system makes it possible to distinguish fast and slow nonlinear processes of electronic or thermal nature, including the generation of a thermal lens and thermal diffusion. An alternative method is proposed to study the dynamics of induced absorption transformation and, therefore, the dynamics of the development of nonlinear rocesses upon degenerate two-photon excitation of the crystal in the absence of external probe radiation.
Nonlinear Optical Signal Processing for Tbit/s Ethernet Applications
DEFF Research Database (Denmark)
Oxenløwe, Leif Katsuo; Galili, Michael; Mulvad, Hans Christian Hansen;
2012-01-01
We review recent experimental demonstrations of Tbaud optical signal processing. In particular, we describe a successful 1.28 Tbit/s serial data generation based on single polarization 1.28 Tbaud symbol rate pulses with binary data modulation (OOK) and subsequent all-optical demultiplexing. We also...
Linear and nonlinear optical processing of polymer matrix nanocomposites
DeJournett, Travis J.; Han, Karen; Olasov, Lauren R.; Zeng, Fan W.; Lee, Brennan; Spicer, James B.
2015-08-01
This work focuses on the scalable synthesis and processing of nanostructures in polymer matrix nanocomposites (PMNCs) for applications that require photochemical functionality of these nanostructures. An in situ vapor deposition process using various metal and metal oxide precursors has been used to create a range of nanocomposites that display photochromic and photocatalytic behaviors. Under specific processing conditions, these composites consist of discrete nanoparticles distributed uniformly throughout the bulk of an optically transparent polymer matrix. Incorporating other chemical species as supplementary deposition agents in the synthesis process can modify these particles and produce complicated nanostructures with enhanced properties. In particular, work has been carried out to structure nanoparticles using laser irradiation. Starting with metallic or metal oxide nanoparticles in the polymer matrix, localized chemical vapor deposition in the near-particle environment has been carried out using laser irradiation to decompose chemical precursors leading to the formation of secondary structures surrounding the seed nanoparticles. Control of the spatial and temporal characteristics of the excitation source allows for synthesis of nanocomposites with a high degree of control over the location, composition and size of nanoparticles in the matrix and presents the opportunity to produce patterned materials with spatially varying properties.
A Kernel Time Structure Independent Component Analysis Method for Nonlinear Process Monitoring☆
Institute of Scientific and Technical Information of China (English)
Lianfang Cai; Xuemin Tian; Ni Zhang
2014-01-01
Kernel independent component analysis (KICA) is a newly emerging nonlinear process monitoring method, which can extract mutually independent latent variables cal ed independent components (ICs) from process var-iables. However, when more than one IC have Gaussian distribution, it cannot extract the IC feature effectively and thus its monitoring performance will be degraded drastical y. To solve such a problem, a kernel time struc-ture independent component analysis (KTSICA) method is proposed for monitoring nonlinear process in this paper. The original process data are mapped into a feature space nonlinearly and then the whitened data are calculated in the feature space by the kernel trick. Subsequently, a time structure independent component analysis algorithm, which has no requirement for the distribution of ICs, is proposed to extract the IC feature. Finally, two monitoring statistics are built to detect process faults. When some fault is detected, a nonlinear fault identification method is developed to identify fault variables based on sensitivity analysis. The proposed monitoring method is applied in the Tennessee Eastman benchmark process. Applications demonstrate the superiority of KTSICA over KICA.
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
A novel nonlinear combination process monitoring method was proposed based on techniques with memory effect (multivariate exponentially weighted moving average (MEWMA)) and kernel independent component analysis (KICA). The method was developed for dealing with nonlinear issues and detecting small or moderate drifts in one or more process variables with autocorrelation. MEWMA charts use additional information from the past history of the process for keeping the memory effect of the process behavior trend. KICA is a recently developed statistical technique for revealing hidden, nonlinear statistically independent factors that underlie sets of measurements and it is a two-phase algorithm: whitened kernel principal component analysis (KPCA) plus independent component analysis (ICA). The application to the fluid catalytic cracking unit (FCCU) simulated process indicates that the proposed combined method based on MEWMA and KICA can effectively capture the nonlinear relationship and detect small drifts in process variables. Its performance significantly outperforms monitoring method based on ICA, MEWMA-ICA and KICA, especially for long-term performance deterioration.
Laurendeau, Aurore; Bonilla, Luis Fabian
2012-01-01
For earthquake-resistant design, engineering seismologists employ time-history analysis for nonlinear simulations. The nonstationary stochastic method previously developed by Pousse et al. (2006) has been updated. This method has the advantage of being both simple, fast and taking into account the basic concepts of seismology (Brune's source, realistic time envelope function, nonstationarity and ground-motion variability). Time-domain simulations are derived from the signal spectrogram and depend on few ground-motion parameters: Arias intensity, significant relative duration and central frequency. These indicators are obtained from empirical attenuation equations that relate them to the magnitude of the event, the source-receiver distance, and the site conditions. We improve the nonstationary stochastic method by using new functional forms (new surface rock dataset, analysis of both intra-event and inter-event residuals, consideration of the scaling relations and VS30), by assessing the central frequency with...
Cai, Wenshan
2016-09-01
Metamaterials have offered not only the unprecedented opportunity to generate unconventional electromagnetic properties that are not found in nature, but also the exciting potential to create customized nonlinear media with tailored high-order effects. Two particularly compelling directions of current interests are active metamaterials, where the optical properties can be purposely manipulated by external stimuli, and nonlinear metamaterials, which enable intensity-dependent frequency conversion of light. By exploring the interaction of these two directions, we leverage the electrical and optical functions simultaneously supported in nanostructured metals and demonstrate electrically-controlled nonlinear processes from photonic metamaterials. We show that a variety of nonlinear optical phenomena, including the wave mixing and the optical rectification, can be purposely modulated by applied voltage signals. In addition, electrically-induced and voltage-controlled nonlinear effects facilitate us to demonstrate the backward phase matching in a negative index material, a long standing prediction in nonlinear metamaterials. Other results to be covered in this talk include photon-drag effect in plasmonic metamaterials and ion-assisted nonlinear effects from metamaterials in electrolytes. Our results reveal a grand opportunity to exploit optical metamaterials as self-contained, dynamic electrooptic systems with intrinsically embedded electrical functions and optical nonlinearities. Reference: L. Kang, Y. Cui, S. Lan, S. P. Rodrigues, M. L. Brongersma, and W. Cai, Nature Communications, 5, 4680 (2014). S. P. Rodrigues and W.Cai, Nature Nanotechnology, 10, 387 (2015). S. Lan, L. Kang, D. T. Schoen, S. P. Rodrigues, Y. Cui, M. L. Brongersma, and W. Cai, Nature Materials, 14, 807 (2015).
The effect of process delay on dynamical behaviors in a self-feedback nonlinear oscillator
Yao, Chenggui; Ma, Jun; Li, Chuan; He, Zhiwei
2016-10-01
The delayed feedback loops play a crucial role in the stability of dynamical systems. The effect of process delay in feedback is studied numerically and theoretically in the delayed feedback nonlinear systems including the neural model, periodic system and chaotic oscillator. The process delay is of key importance in determining the evolution of systems, and the rich dynamical phenomena are observed. By introducing a process delay, we find that it can induce bursting electric activities in the neural model. We demonstrate that this novel regime of amplitude death also exists in the parameter space of feedback strength and process delay for the periodic system and chaotic oscillator. Our results extend the effect of process delay in the paper of Zou et al.(2013) where the process delay can eliminate the amplitude death of the coupled nonlinear systems.
Nonlinear signal processing of electroencephalograms for automated sleep monitoring
Wilson, D.; Rowlands, D. D.; James, Daniel A.; Cutmore, T.
2005-02-01
An automated classification technique is desirable to identify the different stages of sleep. In this paper a technique for differentiating the characteristics of each sleep phase has been developed. This is an ideal pre-processor stage for classifying systems such as neural networks. A wavelet based continuous Morlet transform was developed to analyse the EEG signal in both the time and frequency domain. Test results using two 100 epoch EEG test data sets from pre-recorded EEG data are presented. Key rhythms in the EEG signal were identified and classified using the continuous wavelet transform. The wavelet results indicated each sleep phase contained different rhythms and artefacts (noise from muscle movement in the EEG); providing proof that an EEG can be classified accordingly. The coefficients founded by the wavelet transform have been emphasised by statistical techniques. Hypothesis testing was used to highlight major differences between adjacent sleep stages. Various signal processing methods such as power spectrum density and the discrete wavelet transform have been used to emphasise particular characteristics in an EEG. By implementing signal processing methods on an EEG data set specific rules for each sleep stage have been developed suitable for a neural network classification solution.
A Model for Nonstationary Market Dynamics with Nontrivial Dynamical Scaling
Liu, Min; Bassler, Kevin E.
2008-03-01
In a recent empirical analysis of the Euro/Dollar exchange rate [Bassler, et al., PNAS 104, 17287 (2007)] it was found that during certain periods of the day the market returns scale with Hurst exponents H that are significantly different from 1/2. In some of these periods it is less than 1/2, while in others it is greater than 1/2. In this talk we will propose a possible origin for this behavior and other stylized market facts, including short time negative autocorrelations of returns, in terms of a nonstationary compound Poisson process with a time-dependent intensity rate function that results from a changing bid-ask spread in the microscopic market. The model correctly describes the dynamic scaling behavior of a simple reaction-diffusion model of a limit-order book. That model, like the Euro/Dollar exchange rate, has nonstationary return increments and a Hurst exponent H not equal to 1/2.
Non-linear, adaptive array processing for acoustic interference suppression.
Hoppe, Elizabeth; Roan, Michael
2009-06-01
A method is introduced where blind source separation of acoustical sources is combined with spatial processing to remove non-Gaussian, broadband interferers from space-time displays such as bearing track recorder displays. This differs from most standard techniques such as generalized sidelobe cancellers in that the separation of signals is not done spatially. The algorithm performance is compared to adaptive beamforming techniques such as minimum variance distortionless response beamforming. Simulations and experiments using two acoustic sources were used to verify the performance of the algorithm. Simulations were also used to determine the effectiveness of the algorithm under various signal to interference, signal to noise, and array geometry conditions. A voice activity detection algorithm was used to benchmark the performance of the source isolation.
An Analytical Approximation Method for Strongly Nonlinear Oscillators
Directory of Open Access Journals (Sweden)
Wang Shimin
2012-01-01
Full Text Available An analytical method is proposed to get the amplitude-frequency and the phase-frequency characteristics of free/forced oscillators with nonlinear restoring force. The nonlinear restoring force is expressed as a spring with varying stiffness that depends on the vibration amplitude. That is, for stationary vibration, the restoring force linearly depends on the displacement, but the stiffness of the spring varies with the vibration amplitude for nonstationary oscillations. The varied stiffness is constructed by means of the first and second averaged derivatives of the restoring force with respect to the displacement. Then, this stiffness gives the amplitude frequency and the phase frequency characteristics of the oscillator. Various examples show that this method can be applied extensively to oscillators with nonlinear restoring force, and that the solving process is extremely simple.
Age and Creative Productivity: Nonlinear Estimation of an Information-Processing Model.
Simonton, Dean Keith
1989-01-01
Applied two-step cognitive model to relationship between age and creative productivity. Selected ideation and elaboration rates as information-processing parameters that define mathematical function which describes age curves and specifies their variance across disciplines. Applied non-linear estimation program to further validate model. Despite…
Ultrafast nonlinear all-optical processes in silicon-on-insulator waveguides
Dekker, R.; Usechak, N.; Först, M.; Driessen, A.
2007-01-01
In this review we present an overview of the progress made in recent years in the field of integrated silicon-on-insulator (SOI) waveguide photonics with a strong emphasis on third-order nonlinear optical processes. Although the focus is on simple waveguide structures the utilization of complex stru
Scene matching based on non-linear pre-processing on reference image and sensed image
Institute of Scientific and Technical Information of China (English)
Zhong Sheng; Zhang Tianxu; Sang Nong
2005-01-01
To solve the heterogeneous image scene matching problem, a non-linear pre-processing method for the original images before intensity-based correlation is proposed. The result shows that the proper matching probability is raised greatly. Especially for the low S/N image pairs, the effect is more remarkable.
Institute of Scientific and Technical Information of China (English)
无
1999-01-01
Making use of disk targets composed of several peculiar materials (foam Au, foam C8H8)and hohlraum with a special structure, experiments have been done at"Xing Guang - II" laser facility,which study the characteristics of hot electrons and therelated nonlinear processes such as StimulatedRaman Scattering (SRS), Two Plasma Decay (TPD), StimulatedBrillouin Scattering (SBS), etc.
Garcia-Retamero, Rocio; Hoffrage, Ulrich; Dieckmann, Anja; Ramos, Manuel
2007-01-01
Three experiments investigated whether participants used Take The Best (TTB) Configural, a fast and frugal heuristic that processes configurations of cues when making inferences concerning which of two alternatives has a higher criterion value. Participants were presented with a compound cue that was nonlinearly separable from its elements. The…
EDITORIAL: CAMOP: Quantum Non-Stationary Systems CAMOP: Quantum Non-Stationary Systems
Dodonov, Victor V.; Man'ko, Margarita A.
2010-09-01
Although time-dependent quantum systems have been studied since the very beginning of quantum mechanics, they continue to attract the attention of many researchers, and almost every decade new important discoveries or new fields of application are made. Among the impressive results or by-products of these studies, one should note the discovery of the path integral method in the 1940s, coherent and squeezed states in the 1960-70s, quantum tunneling in Josephson contacts and SQUIDs in the 1960s, the theory of time-dependent quantum invariants in the 1960-70s, different forms of quantum master equations in the 1960-70s, the Zeno effect in the 1970s, the concept of geometric phase in the 1980s, decoherence of macroscopic superpositions in the 1980s, quantum non-demolition measurements in the 1980s, dynamics of particles in quantum traps and cavity QED in the 1980-90s, and time-dependent processes in mesoscopic quantum devices in the 1990s. All these topics continue to be the subject of many publications. Now we are witnessing a new wave of interest in quantum non-stationary systems in different areas, from cosmology (the very first moments of the Universe) and quantum field theory (particle pair creation in ultra-strong fields) to elementary particle physics (neutrino oscillations). A rapid increase in the number of theoretical and experimental works on time-dependent phenomena is also observed in quantum optics, quantum information theory and condensed matter physics. Time-dependent tunneling and time-dependent transport in nano-structures are examples of such phenomena. Another emerging direction of study, stimulated by impressive progress in experimental techniques, is related to attempts to observe the quantum behavior of macroscopic objects, such as mirrors interacting with quantum fields in nano-resonators. Quantum effects manifest themselves in the dynamics of nano-electromechanical systems; they are dominant in the quite new and very promising field of circuit
Wei, Song; Chen, Wen; Hon, Y. C.
2016-11-01
This paper investigates the temporal effects in the modeling of flows through porous media and particles transport. Studies will be made among the time fractional diffusion model and two classical nonlinear diffusion models. The effects of the parameters upon the mentioned models have been studied. By simulating the sub-diffusion processes and comparing the numerical results of these models under different boundary conditions, we can conclude that the time fractional diffusion model is more suitable for simulating the sub-diffusion with steady diffusion rate; whereas the nonlinear models are more appropriate for depicting the sub-diffusion under changing diffusion rate.
Analytical investigation of machining chatter by considering the nonlinearity of process damping
Ahmadi, Keivan
2017-04-01
In this paper, the well-established problem of self-excited vibrations in machining is revisited to include the nonlinearity of process damping at the tool and workpiece interface. Machining dynamics is modeled using a time-delayed system with nonlinear damping, and the method of averaging is used to obtain the amplitude of the resulting limit cycles. As a result, an analytical relationship is presented to establish the stability charts corresponding with arbitrary limit cycles in machining systems. The presented analytical solutions are verified using experiments and numerical solutions.
2-D nonlinear IIR-filters for image processing - An exploratory analysis
Bauer, P. H.; Sartori, M.
1991-01-01
A new nonlinear IIR filter structure is introduced and its deterministic properties are analyzed. It is shown to be better suited for image processing applications than its linear shift-invariant counterpart. The new structure is obtained from causality inversion of a 2D quarterplane causal linear filter with respect to the two directions of propagation. It is demonstrated, that by using this design, a nonlinear 2D lowpass filter can be constructed, which is capable of effectively suppressing Gaussian or impulse noise without destroying important image information.
Institute of Scientific and Technical Information of China (English)
Xiao Huang; Jian Wang; Ling-zhi Zhang; Zhi-gang Cai; Zhao-xi Lianga
2001-01-01
Four phenoxysilicon networks for nonlinear optical (NLO) applications were designed and prepared by an extended sol-gel process without additional H20 and catalyst. All poled polymer network films possess high second-order nonlinear optical coefficients (d33) of 10-?～10-8 esu. The investigation of NLO temporal stability at room temperature and elevated temperature (120°C) indicated that these films exhibit high d33 stability because the orientation of the chromophores are locked in the phenoxysilicon organic/inorganic networks.
2-D nonlinear IIR-filters for image processing - An exploratory analysis
Bauer, P. H.; Sartori, M.
1991-01-01
A new nonlinear IIR filter structure is introduced and its deterministic properties are analyzed. It is shown to be better suited for image processing applications than its linear shift-invariant counterpart. The new structure is obtained from causality inversion of a 2D quarterplane causal linear filter with respect to the two directions of propagation. It is demonstrated, that by using this design, a nonlinear 2D lowpass filter can be constructed, which is capable of effectively suppressing Gaussian or impulse noise without destroying important image information.
CONTROL OF NONLINEAR PROCESS USING NEURAL NETWORK BASED MODEL PREDICTIVE CONTROL
Directory of Open Access Journals (Sweden)
Dr.A.TRIVEDI
2011-04-01
Full Text Available This paper presents a Neural Network based Model Predictive Control (NNMPC strategy to control nonlinear process. Multilayer Perceptron Neural Network (MLP is chosen to represent a Nonlinear Auto Regressive with eXogenous signal (NARX model of a nonlinear system. NARX dynamic model is based on feed-forward architecture and offers good approximation capabilities along with robustness and accuracy. Based on the identified neural model, a generalized predictive control (GPC algorithm is implemented to control the composition in acontinuous stirred tank reactor (CSTR, whose parameters are optimally determined by solving quadratic performance index using well known Levenberg-Marquardt and Quasi-Newton algorithm. NNMPC is tuned by selecting few horizon parameters and weighting factor. The tracking performance of the NNMPC is tested using different amplitude function as a reference signal on CSTR application. Also the robustness and performance is tested in the presence of disturbance on random reference signal.
Hydex Glass and Amorphous Silicon for Integrated Nonlinear Optical Signal Processing
Morandotti, Roberto
2015-01-01
Photonic integrated circuits that exploit nonlinear optics in order to generate and process signals all-optically have achieved performance far superior to that possible electronically - particularly with respect to speed. Although silicon-on-insulator has been the leading platform for nonlinear optics for some time, its high two-photon absorption at telecommunications wavelengths poses a fundamental limitation. We review the recent achievements based in new CMOS-compatible platforms that are better suited than SOI for nonlinear optics, focusing on amorphous silicon and Hydex glass. We highlight their potential as well as the challenges to achieving practical solutions for many key applications. These material systems have opened up many new capabilities such as on-chip optical frequency comb generation and ultrafast optical pulse generation and measurement.
Nonlinear Pulse Shaping in Fibres for Pulse Generation and Optical Processing
Directory of Open Access Journals (Sweden)
Sonia Boscolo
2012-01-01
Full Text Available The development of new all-optical technologies for data processing and signal manipulation is a field of growing importance with a strong potential for numerous applications in diverse areas of modern science. Nonlinear phenomena occurring in optical fibres have many attractive features and great, but not yet fully explored, potential in signal processing. Here, we review recent progress on the use of fibre nonlinearities for the generation and shaping of optical pulses and on the applications of advanced pulse shapes in all-optical signal processing. Amongst other topics, we will discuss ultrahigh repetition rate pulse sources, the generation of parabolic shaped pulses in active and passive fibres, the generation of pulses with triangular temporal profiles, and coherent supercontinuum sources. The signal processing applications will span optical regeneration, linear distortion compensation, optical decision at the receiver in optical communication systems, spectral and temporal signal doubling, and frequency conversion.
Directory of Open Access Journals (Sweden)
Hyun-Seob Song
2013-09-01
Full Text Available The nonlinear behavior of metabolic systems can arise from at least two different sources. One comes from the nonlinear kinetics of chemical reactions in metabolism and the other from nonlinearity associated with regulatory processes. Consequently, organisms at a constant growth rate (as experienced in a chemostat could display multiple metabolic states or display complex oscillatory behavior both with potentially serious implications to process operation. This paper explores the nonlinear behavior of a metabolic model of Escherichia coli growth on mixed substrates with sufficient detail to include regulatory features through the cybernetic postulate that metabolic regulation is the consequence of a dynamic objective function ensuring the organism’s survival. The chief source of nonlinearity arises from the optimal formulation with the metabolic state determined by a convex combination of reactions contributing to the objective function. The model for anaerobic growth of E. coli was previously examined for multiple steady states in a chemostat fed by a mixture of glucose and pyruvate substrates under very specific conditions and experimentally verified. In this article, we explore the foregoing model for nonlinear behavior over the full range of parameters, γ (the fractional concentration of glucose in the feed mixture and D (the dilution rate. The observed multiplicity is in the cybernetic variables combining elementary modes. The results show steady-state multiplicity up to seven. No Hopf bifurcation was encountered, however. Bifurcation analysis of cybernetic models is complicated by the non-differentiability of the cybernetic variables for enzyme activities. A methodology is adopted here to overcome this problem, which is applicable to more complicated metabolic networks.
Circuits and systems based on delta modulation linear, nonlinear and mixed mode processing
Zrilic, Djuro G
2005-01-01
This book is intended for students and professionals who are interested in the field of digital signal processing of delta-sigma modulated sequences. The overall focus is on the development of algorithms and circuits for linear, non-linear, and mixed mode processing of delta-sigma modulated pulse streams. The material presented here is directly relevant to applications in digital communication, DSP, instrumentation, and control.
Rius, Manuel; Bolea, Mario; Mora, José; Ortega, Beatriz; Capmany, José
2015-05-18
We experimentally demonstrate, for the first time, a chirped microwave pulses generator based on the processing of an incoherent optical signal by means of a nonlinear dispersive element. Different capabilities have been demonstrated such as the control of the time-bandwidth product and the frequency tuning increasing the flexibility of the generated waveform compared to coherent techniques. Moreover, the use of differential detection improves considerably the limitation over the signal-to-noise ratio related to incoherent processing.
Non-linear effects in transition edge sensors for X-ray detection
Energy Technology Data Exchange (ETDEWEB)
Bandler, S.R. [NASA Goddard Space Flight Center, Greenbelt, MD 20771 (United States)]. E-mail: sbandler@milkyway.gsfc.nasa.gov; Figueroa-Feliciano, E. [NASA Goddard Space Flight Center, Greenbelt, MD 20771 (United States); Iyomoto, N. [NASA Goddard Space Flight Center, Greenbelt, MD 20771 (United States); Kelley, R.L. [NASA Goddard Space Flight Center, Greenbelt, MD 20771 (United States); Kilbourne, C.A. [NASA Goddard Space Flight Center, Greenbelt, MD 20771 (United States); Murphy, K.D. [NASA Goddard Space Flight Center, Greenbelt, MD 20771 (United States); Porter, F.S. [NASA Goddard Space Flight Center, Greenbelt, MD 20771 (United States); Saab, T. [NASA Goddard Space Flight Center, Greenbelt, MD 20771 (United States); Sadleir, J. [NASA Goddard Space Flight Center, Greenbelt, MD 20771 (United States)
2006-04-15
In a microcalorimeter that uses a transition-edge sensor to detect energy depositions, the small signal energy resolution improves with decreasing heat capacity. This improvement remains true up to the point where non-linear and saturation effects become significant. This happens when the energy deposition causes a significant change in the sensor resistance. Not only does the signal size become a non-linear function of the energy deposited, but also the noise becomes non-stationary over the duration of the pulse. Algorithms have been developed that can calculate the optimal performance given this non-linear behavior that typically requires significant processing and calibration work-both of which are impractical for space missions. We have investigated the relative importance of the various non-linear effects, with the hope that a computationally simple transformation can overcome the largest of the non-linear and non-stationary effects, producing a highly linear 'gain' for pulse-height versus energy, and close to the best energy resolution at all energies when using a Wiener filter.
Agilan, V.; Umamahesh, N. V.
2017-03-01
Present infrastructure design is primarily based on rainfall Intensity-Duration-Frequency (IDF) curves with so-called stationary assumption. However, in recent years, the extreme precipitation events are increasing due to global climate change and creating non-stationarity in the series. Based on recent theoretical developments in the Extreme Value Theory (EVT), recent studies proposed a methodology for developing non-stationary rainfall IDF curve by incorporating trend in the parameters of the Generalized Extreme Value (GEV) distribution using Time covariate. But, the covariate Time may not be the best covariate and it is important to analyze all possible covariates and find the best covariate to model non-stationarity. In this study, five physical processes, namely, urbanization, local temperature changes, global warming, El Niño-Southern Oscillation (ENSO) cycle and Indian Ocean Dipole (IOD) are used as covariates. Based on these five covariates and their possible combinations, sixty-two non-stationary GEV models are constructed. In addition, two non-stationary GEV models based on Time covariate and one stationary GEV model are also constructed. The best model for each duration rainfall series is chosen based on the corrected Akaike Information Criterion (AICc). From the findings of this study, it is observed that the local processes (i.e., Urbanization, local temperature changes) are the best covariate for short duration rainfall and global processes (i.e., Global warming, ENSO cycle and IOD) are the best covariate for the long duration rainfall of the Hyderabad city, India. Furthermore, the covariate Time is never qualified as the best covariate. In addition, the identified best covariates are further used to develop non-stationary rainfall IDF curves of the Hyderabad city. The proposed methodology can be applied to other situations to develop the non-stationary IDF curves based on the best covariate.
Institute of Scientific and Technical Information of China (English)
唐圣金; 郭晓松; 于传强; 周志杰; 周召发; 张邦成
2014-01-01
Real time remaining useful life (RUL) prediction based on condition monitoring is an essential part in condition based maintenance (CBM). In the current methods about the real time RUL prediction of the nonlinear degradation process, the measurement error is not considered and forecasting uncertainty is large. Therefore, an approximate analytical RUL distribution in a closed-form of a nonlinear Wiener based degradation process with measurement errors was proposed. The maximum likelihood estimation approach was used to estimate the unknown fixed parameters in the proposed model. When the newly observed data are available, the random parameter is updated by the Bayesian method to make the estimation adapt to the item’s individual characteristic and reduce the uncertainty of the estimation. The simulation results show that considering measurement errors in the degradation process can significantly improve the accuracy of real time RUL prediction.
Soft sensor modeling based on variable partition ensemble method for nonlinear batch processes
Wang, Li; Chen, Xiangguang; Yang, Kai; Jin, Huaiping
2017-01-01
Batch processes are always characterized by nonlinear and system uncertain properties, therefore, the conventional single model may be ill-suited. A local learning strategy soft sensor based on variable partition ensemble method is developed for the quality prediction of nonlinear and non-Gaussian batch processes. A set of input variable sets are obtained by bootstrapping and PMI criterion. Then, multiple local GPR models are developed based on each local input variable set. When a new test data is coming, the posterior probability of each best performance local model is estimated based on Bayesian inference and used to combine these local GPR models to get the final prediction result. The proposed soft sensor is demonstrated by applying to an industrial fed-batch chlortetracycline fermentation process.
Multistep Wind Speed Forecasting Based on Wavelet and Gaussian Processes
Niya Chen; Zheng Qian; Xiaofeng Meng
2013-01-01
Accurate wind speed forecasts are necessary for the safety and economy of the renewable energy utilization. The wind speed forecasts can be obtained by statistical model based on historical data. In this paper, a novel W-GP model (wavelet decomposition based Gaussian process learning paradigm) is proposed for short-term wind speed forecasting. The nonstationary and nonlinear original wind speed series is first decomposed into a set of better-behaved constitutive subseries by wavelet decomposi...
Design and implementation of non-linear image processing functions for CMOS image sensor
Musa, Purnawarman; Sudiro, Sunny A.; Wibowo, Eri P.; Harmanto, Suryadi; Paindavoine, Michel
2012-11-01
Today, solid state image sensors are used in many applications like in mobile phones, video surveillance systems, embedded medical imaging and industrial vision systems. These image sensors require the integration in the focal plane (or near the focal plane) of complex image processing algorithms. Such devices must meet the constraints related to the quality of acquired images, speed and performance of embedded processing, as well as low power consumption. To achieve these objectives, low-level analog processing allows extracting the useful information in the scene directly. For example, edge detection step followed by a local maxima extraction will facilitate the high-level processing like objects pattern recognition in a visual scene. Our goal was to design an intelligent image sensor prototype achieving high-speed image acquisition and non-linear image processing (like local minima and maxima calculations). For this purpose, we present in this article the design and test of a 64×64 pixels image sensor built in a standard CMOS Technology 0.35 μm including non-linear image processing. The architecture of our sensor, named nLiRIC (non-Linear Rapid Image Capture), is based on the implementation of an analog Minima/Maxima Unit. This MMU calculates the minimum and maximum values (non-linear functions), in real time, in a 2×2 pixels neighbourhood. Each MMU needs 52 transistors and the pitch of one pixel is 40×40 mu m. The total area of the 64×64 pixels is 12.5mm2. Our tests have shown the validity of the main functions of our new image sensor like fast image acquisition (10K frames per second), minima/maxima calculations in less then one ms.
Multiaxis Rainflow Fatigue Methods for Nonstationary Vibration
Irvine, T.
2016-09-01
Mechanical structures and components may be subjected to cyclical loading conditions, including sine and random vibration. Such systems must be designed and tested according. Rainflow cycle counting is the standard method for reducing a stress time history to a table of amplitude-cycle pairings prior to the Palmgren-Miner cumulative damage calculation. The damage calculation is straightforward for sinusoidal stress but very complicated for random stress, particularly for nonstationary vibration. This paper evaluates candidate methods and makes a recommendation for further study of a hybrid technique.
Modelling Nonlinear Dynamic Textures using Hybrid DWT-DCT and Kernel PCA with GPU
Ghadekar, Premanand Pralhad; Chopade, Nilkanth Bhikaji
2016-12-01
Most of the real-world dynamic textures are nonlinear, non-stationary, and irregular. Nonlinear motion also has some repetition of motion, but it exhibits high variation, stochasticity, and randomness. Hybrid DWT-DCT and Kernel Principal Component Analysis (KPCA) with YCbCr/YIQ colour coding using the Dynamic Texture Unit (DTU) approach is proposed to model a nonlinear dynamic texture, which provides better results than state-of-art methods in terms of PSNR, compression ratio, model coefficients, and model size. Dynamic texture is decomposed into DTUs as they help to extract temporal self-similarity. Hybrid DWT-DCT is used to extract spatial redundancy. YCbCr/YIQ colour encoding is performed to capture chromatic correlation. KPCA is applied to capture nonlinear motion. Further, the proposed algorithm is implemented on Graphics Processing Unit (GPU), which comprise of hundreds of small processors to decrease time complexity and to achieve parallelism.
Energy Technology Data Exchange (ETDEWEB)
Golovin, Sergey V., E-mail: sergey@hydro.nsc.r [Lavrentyev Institute of Hydrodynamics SB RAS, 630090 Novosibirsk (Russian Federation); Department of Mechanics and Mathematics, Novosibirsk State University, 630090 Novosibirsk (Russian Federation)
2011-01-17
Equations of magnetohydrodynamics (MHD) in the natural curvilinear system of coordinates where trajectories and magnetic lines play a role of coordinate curves are reduced to the non-linear vector wave equation coupled with the incompressibility condition in the form of the generalized Cauchy integral. The symmetry group of obtained equation, equivalence transformation, and group classification with respect to the constitutive equation are calculated. New exact solutions with functional arbitrariness describing non-stationary incompressible flows with constant total pressure are given by explicit formulae. The corresponding magnetic surfaces have the shape of deformed nested cylinders, tori, or knotted tubes.
Numerical Solution of Problem for Non-Stationary Heat Conduction in Multi-Layer Bodies
Directory of Open Access Journals (Sweden)
R. I. Еsman
2007-01-01
Full Text Available A mathematical model for non-stationary heat conduction of multi-layer bodies has been developed. Dirac’s δ-function is used to take into account phase and chemical transformations in one of the wall layers. While formulating a problem non-linear heat conduction equations have been used with due account of dependence of thermal and physical characteristics on temperature. Solution of the problem is realized with the help of methods of a numerical experiment and computer modeling.
Supervised and unsupervised condition monitoring of non-stationary acoustic emission signals
DEFF Research Database (Denmark)
Sigurdsson, Sigurdur; Pontoppidan, Niels Henrik; Larsen, Jan
2005-01-01
We are pursuing a system that monitors the engine condition under multiple load settings, i.e. under non-stationary operating conditions. The running speed when data acquired under simulated marine conditions (different load settings on the propeller curve) was in the range from approximately 70...... approaches perform well, which indicates that unsupervised models, modelled without faulty data, may be used for accurate condition monitoring....... condition changes across load changes. In this paper we approach this load interpolation problem with supervised and unsupervised learning, i.e. model with normal and fault examples and normal examples only, respectively. We apply non-linear methods for the learning of engine condition changes. Both...
Martingales, nonstationary increments, and the efficient market hypothesis
McCauley, Joseph L.; Bassler, Kevin E.; Gunaratne, Gemunu H.
2008-06-01
We discuss the deep connection between nonstationary increments, martingales, and the efficient market hypothesis for stochastic processes x(t) with arbitrary diffusion coefficients D(x,t). We explain why a test for a martingale is generally a test for uncorrelated increments. We explain why martingales look Markovian at the level of both simple averages and 2-point correlations. But while a Markovian market has no memory to exploit and cannot be beaten systematically, a martingale admits memory that might be exploitable in higher order correlations. We also use the analysis of this paper to correct a misstatement of the ‘fair game’ condition in terms of serial correlations in Fama’s paper on the EMH. We emphasize that the use of the log increment as a variable in data analysis generates spurious fat tails and spurious Hurst exponents.
Simulation of nonstationary phenomena in atmospheric-pressure glow discharge
Korolev, Yu. D.; Frants, O. B.; Nekhoroshev, V. O.; Suslov, A. I.; Kas'yanov, V. S.; Shemyakin, I. A.; Bolotov, A. V.
2016-06-01
Nonstationary processes in atmospheric-pressure glow discharge manifest themselves in spontaneous transitions from the normal glow discharge into a spark. In the experiments, both so-called completed transitions in which a highly conductive constricted channel arises and incomplete transitions accompanied by the formation of a diffuse channel are observed. A model of the positive column of a discharge in air is elaborated that allows one to interpret specific features of the discharge both in the stationary stage and during its transition into a spark and makes it possible to calculate the characteristic oscillatory current waveforms for completed transitions into a spark and aperiodic ones for incomplete transitions. The calculated parameters of the positive column in the glow discharge mode agree well with experiment. Data on the densities of the most abundant species generated in the discharge (such as atomic oxygen, metastable nitrogen molecules, ozone, nitrogen oxides, and negative oxygen ions) are presented.
Liu, Qian; OuYang, Liangfei; Liang, Heng; Li, Nan; Geng, Xindu
2012-06-01
A novel thermodynamic state recursion (TSR) method, which is based on nonequilibrium thermodynamic path described by the Lagrangian-Eulerian representation, is presented to simulate the whole chromatographic process of frontal analysis using the spatial distribution of solute bands in time series like as a series of images. TSR differs from the current numerical methods using the partial differential equations in Eulerian representation. The novel method is used to simulate the nonideal, nonlinear hydrophobic interaction chromatography (HIC) processes of lysozyme and myoglobin under the discrete complex boundary conditions. The results show that the simulated breakthrough curves agree well with the experimental ones. The apparent diffusion coefficient and the Langmuir isotherm parameters of the two proteins in HIC are obtained by the state recursion inverse method. Due to its the time domain and Markov characteristics, TSR is applicable to the design and online control of the nonlinear multicolumn chromatographic systems.
Photonic Damascene Process for Integrated High-Q Microresonator Based Nonlinear Photonics
Pfeiffer, Martin H P; Brasch, Victor; Zervas, Michael; Geiselmann, Michael; Jost, John D; Kippenberg, Tobias J
2015-01-01
High confinement, integrated silicon nitride (SiN) waveguides have recently emerged as attractive platform for on-chip nonlinear optical devices. The fabrication of high-Q SiN microresonators with anomalous group velocity dispersion (GVD) has enabled broadband nonlinear optical frequency comb generation. Such frequency combs have been successfully applied in coherent communication and ultrashort pulse generation. However, the reliable fabrication of high confinement waveguides from stoichiometric, high stress SiN remains challenging. Here we present a novel photonic Damascene fabrication process enabling the use of substrate topography for stress control and thin film crack prevention. With close to unity sample yield we fabricate microresonators with $1.35\\,\\mu\\mathrm{m}$ thick waveguides and optical Q factors of $3.7\\times10^{6}$ and demonstrate single temporal dissipative Kerr soliton (DKS) based coherent optical frequency comb generation. Our newly developed process is interesting also for other material ...
Nonlinear software sensor for monitoring genetic regulation processes with noise and modeling errors
Ibarra-Junquera, V; Rosu, H C; Arguello, G; Collado-Vides, J
2004-01-01
Nonlinear control techniques by means of a software sensor that are commonly used in chemical engineering could be also applied to genetic regulation processes. We provide here a realistic formulation of this procedure by introducing an additive white Gaussian noise, which is usually found in experimental data. Besides, we include model errors, meaning that we assume we do not know the nonlinear regulation function of the process. In order to illustrate this procedure, we employ the Goodwin dynamics of the concentrations (1963) in the simple form recently discussed by De Jong (2002), which involves the dynamics of the mRNA a, given protein A, and metabolite K concentrations. However instead of considering their full dynamics, we use only the data of metabolite K and a designed software sensor. We also show, more generally, that it is possible to rebuild the complete set of n concentrations despite the uncertainties in the regulation function and the perturbation due to the additive white Gaussian noise
The SPH approach to the process of container filling based on non-linear constitutive models
Institute of Scientific and Technical Information of China (English)
Tao Jiang; Jie Ouyang; Lin Zhang; Jin-Lian Ren
2012-01-01
In this work,the transient free surface of container filling with non-linear constitutive equation's fluids is numerically investigated by the smoothed particle hydrodynamics (SPH) method.Specifically,the filling process of a square container is considered for non-linear polymer fluids based on the Cross model.The validity of the presented SPH is first verified by solving the Newtonian fluid and OldroydB fluid jet.Various phenomena in the filling process are shown,including the jet buckling,jet thinning,splashing or spluttering,steady filling.Moreover,a new phenomenon of vortex whirling is more evidently observed for the Cross model fluid compared with the Newtonian fluid case.
Institute of Scientific and Technical Information of China (English)
WANG Yan-bo; BAO Gang
2008-01-01
By applying a nonlinear control and arranging a transient process, the initiative error of the pneumatic servo positioning system is reduced largely, and a larger gain of the controller is used to improve the responding speed of the system at the same damping ratio. Therefore, a compromise is made among the responding speed, overshoot, robustness, adaptability and stability. In addition, a dynamic output feedback controller, including position velocity and acceleration (PVA) feedback, is designed to improve the performance of the system. And a nonlinear controller is reconstructed based on the linear output feedback controller to decrease noises and disturbances. The dynamic responses of the system are simulated and tested. Results show that the error is kept within 0.02 mm under different mass loads and the positioning transient process is smooth, without overshoot and speedy.
Effects of non-linear rheology on the electrospinning process: a model study
Pontrelli, Giuseppe; Coluzza, Ivan; Pisignano, Dario; Succi, Sauro
2014-01-01
We develop an analytical bead-spring model to investigate the role of non-linear rheology on the dynamics of electrified jets in the early stage of the electrospinning process. Qualitative arguments, parameter studies as well as numerical simulations, show that the elongation of the charged jet filament is significantly reduced in the presence of a non-zero yield stress. This may have beneficial implications for the optimal design of future electrospinning experiments.
Salcedo-Sanz, S.
2016-10-01
Meta-heuristic algorithms are problem-solving methods which try to find good-enough solutions to very hard optimization problems, at a reasonable computation time, where classical approaches fail, or cannot even been applied. Many existing meta-heuristics approaches are nature-inspired techniques, which work by simulating or modeling different natural processes in a computer. Historically, many of the most successful meta-heuristic approaches have had a biological inspiration, such as evolutionary computation or swarm intelligence paradigms, but in the last few years new approaches based on nonlinear physics processes modeling have been proposed and applied with success. Non-linear physics processes, modeled as optimization algorithms, are able to produce completely new search procedures, with extremely effective exploration capabilities in many cases, which are able to outperform existing optimization approaches. In this paper we review the most important optimization algorithms based on nonlinear physics, how they have been constructed from specific modeling of a real phenomena, and also their novelty in terms of comparison with alternative existing algorithms for optimization. We first review important concepts on optimization problems, search spaces and problems' difficulty. Then, the usefulness of heuristics and meta-heuristics approaches to face hard optimization problems is introduced, and some of the main existing classical versions of these algorithms are reviewed. The mathematical framework of different nonlinear physics processes is then introduced as a preparatory step to review in detail the most important meta-heuristics based on them. A discussion on the novelty of these approaches, their main computational implementation and design issues, and the evaluation of a novel meta-heuristic based on Strange Attractors mutation will be carried out to complete the review of these techniques. We also describe some of the most important application areas, in
Molecular Optics Nonlinear Optical Processes in Organic and Polymeric Crystals and Films. Part 2
1991-11-01
susceptibility gamma ijkl(-omega 4; omega 1, omega 2, omega 3 ) demonstrate that the microscopic origin of the nonresonant third order nonlinear optical...interaction calculations of gamma jkl(-omega 4; omega 1, omega 2, omega 3 ) for the archetypal class of quasi-one dimensional conjugated structures...largest of the two dominant, competing virtual excitation processes that determine gamma ijkl(- omega 4; omega 1, omega 2, omega 3 ). It is also found in
Nonstationary sparsity-constrained seismic deconvolution
Sun, Xue-Kai; Sam, Zandong Sun; Xie, Hui-Wen
2014-12-01
The Robinson convolution model is mainly restricted by three inappropriate assumptions, i.e., statistically white reflectivity, minimum-phase wavelet, and stationarity. Modern reflectivity inversion methods (e.g., sparsity-constrained deconvolution) generally attempt to suppress the problems associated with the first two assumptions but often ignore that seismic traces are nonstationary signals, which undermines the basic assumption of unchanging wavelet in reflectivity inversion. Through tests on reflectivity series, we confirm the effects of nonstationarity on reflectivity estimation and the loss of significant information, especially in deep layers. To overcome the problems caused by nonstationarity, we propose a nonstationary convolutional model, and then use the attenuation curve in log spectra to detect and correct the influences of nonstationarity. We use Gabor deconvolution to handle nonstationarity and sparsity-constrained deconvolution to separating reflectivity and wavelet. The combination of the two deconvolution methods effectively handles nonstationarity and greatly reduces the problems associated with the unreasonable assumptions regarding reflectivity and wavelet. Using marine seismic data, we show that correcting nonstationarity helps recover subtle reflectivity information and enhances the characterization of details with respect to the geological record.
Scaling in non-stationary time series. (I)
Ignaccolo, M.; Allegrini, P.; Grigolini, P.; Hamilton, P.; West, B. J.
2004-05-01
Most data processing techniques, applied to biomedical and sociological time series, are only valid for random fluctuations that are stationary in time. Unfortunately, these data are often non-stationary and the use of techniques of analysis resting on the stationary assumption can produce a wrong information on the scaling, and so on the complexity of the process under study. Herein, we test and compare two techniques for removing the non-stationary influences from computer generated time series, consisting of the superposition of a slow signal and a random fluctuation. The former is based on the method of wavelet decomposition, and the latter is a proposal of this paper, denoted by us as step detrending technique. We focus our attention on two cases, when the slow signal is a periodic function mimicking the influence of seasons, and when it is an aperiodic signal mimicking the influence of a population change (increase or decrease). For the purpose of computational simplicity the random fluctuation is taken to be uncorrelated. However, the detrending techniques here illustrated work also in the case when the random component is correlated. This expectation is fully confirmed by the sociological applications made in the companion paper. We also illustrate a new procedure to assess the existence of a genuine scaling, based on the adoption of diffusion entropy, multiscaling analysis and the direct assessment of scaling. Using artificial sequences, we show that the joint use of all these techniques yield the detection of the real scaling, and that this is independent of the technique used to detrend the original signal.
Data-driven design of fault diagnosis systems nonlinear multimode processes
Haghani Abandan Sari, Adel
2014-01-01
In many industrial applications early detection and diagnosis of abnormal behavior of the plant is of great importance. During the last decades, the complexity of process plants has been drastically increased, which imposes great challenges in development of model-based monitoring approaches and it sometimes becomes unrealistic for modern large-scale processes. The main objective of Adel Haghani Abandan Sari is to study eﬃcient fault diagnosis techniques for complex industrial systems using process historical data and considering the nonlinear behavior of the process. To this end, diﬀerent methods are presented to solve the fault diagnosis problem based on the overall behavior of the process and its dynamics. Moreover, a novel technique is proposed for fault isolation and determination of the root-cause of the faults in the system, based on the fault impacts on the process measurements. Contents Process monitoring Fault diagnosis and fault-tolerant control Data-driven approaches and decision making Target...
Development of coherent tunable source in 2–16 m region using nonlinear frequency mixing processes
Indian Academy of Sciences (India)
Udit Chatterjee
2014-01-01
A very convenient way to obtain widely tunable source of coherent radiation in the infrared region is through nonlinear frequency mixing processes like second harmonic generation (SHG), difference-frequency mixing (DFM) or optical parametric oscillation (OPO). Using commonly available Nd:YAG laser and its harmonic pumped dye laser radiation as parent beams, we have been able to generate coherent tunable infrared radiation (IR) in 2–16 m region using different nonlinear crystals by DFM and OPO. We have also generated such IR source in the 4–5 m region through SHG of CO2 laser in different infrared crystals. In the process we have characterized a large number of nonlinear crystals like different borate group of crystals, KTP, KTA, LiIO3, MgO:LiNbO3, GaSe, AgGaSe2, ZnGeP2, AgGa1−InSe2, HgGa2S4 etc. To improve the conversion efficiencies of such frequency conversion processes, we have developed some novel schemes, like multipass configuration (MC) and positive optical feedback (POF). The significance of the obtained results lies in the fact that to get the same conversion in SHG or DFM, one now requires fundamental input radiation with much lower intensity.
Abdeldayem, Hossin; Frazier, Donald O.; Paley, Mark S.; Penn, Benjamin; Witherow, William K.; Bank, Curtis; Shields, Angela; Hicks, Rosline; Ashley, Paul R.
1996-01-01
In this paper, we will take a closer look at the state of the art of polydiacetylene, and metal-free phthalocyanine films, in view of the microgravity impact on their optical properties, their nonlinear optical properties and their potential advantages for integrated optics. These materials have many attractive features with regard to their use in integrated optical circuits and optical switching. Thin films of these materials processed in microgravity environment show enhanced optical quality and better molecular alignment than those processed in unit gravity. Our studies of these materials indicate that microgravity can play a major role in integrated optics technology. Polydiacetylene films are produced by UV irradiation of monomer solution through an optical window. This novel technique of forming polydiacetylene thin films has been modified for constructing sophisticated micro-structure integrated optical patterns using a pre-programmed UV-Laser beam. Wave guiding through these thin films by the prism coupler technique has been demonstrated. The third order nonlinear parameters of these films have been evaluated. Metal-free phthalocyanine films of good optical quality are processed in our laboratories by vapor deposition technique. Initial studies on these films indicate that they have excellent chemical, laser, and environmental stability. They have large nonlinear optical parameters and show intrinsic optical bistability. This bistability is essential for optical logic gates and optical switching applications. Waveguiding and device making investigations of these materials are underway.
Soft Sensor for Inputs and Parameters Using Nonlinear Singular State Observer in Chemical Processes
Institute of Scientific and Technical Information of China (English)
许锋; 汪晔晔; 罗雄麟
2013-01-01
Chemical processes are usually nonlinear singular systems. In this study, a soft sensor using nonlinear singular state observer is established for unknown inputs and uncertain model parameters in chemical processes, which are augmented as state variables. Based on the observability of the singular system, this paper presents a simplified observability criterion under certain conditions for unknown inputs and uncertain model parameters. When the observability is satisfied, the unknown inputs and the uncertain model parameters are estimated online by the soft sensor using augmented nonlinear singular state observer. The riser reactor of fluid catalytic cracking unit is used as an example for analysis and simulation. With the catalyst circulation rate as the only unknown input without model error, one temperature sensor at the riser reactor outlet will ensure the correct estimation for the catalyst cir-culation rate. However, when uncertain model parameters also exist, additional temperature sensors must be used to ensure correct estimation for unknown inputs and uncertain model parameters of chemical processes.
Frank, T. D.
2008-02-01
We discuss two central claims made in the study by Bassler et al. [K.E. Bassler, G.H. Gunaratne, J.L. McCauley, Physica A 369 (2006) 343]. Bassler et al. claimed that Green functions and Langevin equations cannot be defined for nonlinear diffusion equations. In addition, they claimed that nonlinear diffusion equations are linear partial differential equations disguised as nonlinear ones. We review bottom-up and top-down approaches that have been used in the literature to derive Green functions for nonlinear diffusion equations and, in doing so, show that the first claim needs to be revised. We show that the second claim as well needs to be revised. To this end, we point out similarities and differences between non-autonomous linear Fokker-Planck equations and autonomous nonlinear Fokker-Planck equations. In this context, we raise the question whether Bassler et al.’s approach to financial markets is physically plausible because it necessitates the introduction of external traders and causes. Such external entities can easily be eliminated when taking self-organization principles and concepts of nonextensive thermostatistics into account and modeling financial processes by means of nonlinear Fokker-Planck equations.
Ultrafast nonlinear optical processes in metal-dielectric nanocomposites and nanostructures
Energy Technology Data Exchange (ETDEWEB)
Kim, Kwang-Hyon
2012-04-13
This work reports results of a theoretical study of nonlinear optical processes in metal-dielectric nanocomposites used for the increase of the nonlinear coefficients and for plasmonic field enhancement. The main results include the study of the transient saturable nonlinearity in dielectric composites doped with metal nanoparticles, its physical mechanism as well its applications in nonlinear optics. For the study of the transient response, a time-depending equation for the dielectric function of the nanocomposite using the semi-classical two-temperature model is derived. By using this approach, we study the transient nonlinear characteristics of these materials in comparison with preceding experimental measurements. The results show that these materials behave as efficient saturable absorbers for passive mode-locking of lasers in the spectral range from the visible to near IR. We present results for the modelocked dynamics in short-wavelength solid-state and semiconductor disk lasers; in this spectral range other efficient saturable absorbers do not exist. We suggest a new mechanism for the realization of slow light phenomenon by using glasses doped with metal nanoparticles in a pump-probe regime near the plasmonic resonance. Furthermore, we study femtosecond plasmon generation by mode-locked surface plasmon polariton lasers with Bragg reflectors and metal-gain-absorber layered structures. In the final part of the thesis, we present results for high-order harmonic generation near a metallic fractal rough surface. The results show a possible reduction of the pump intensities by three orders of magnitudes and two orders of magnitudes higher efficiency compared with preceding experimental results by using bow-tie nanostructures.
Non-stationary (13)C-metabolic flux ratio analysis.
Hörl, Manuel; Schnidder, Julian; Sauer, Uwe; Zamboni, Nicola
2013-12-01
(13)C-metabolic flux analysis ((13)C-MFA) has become a key method for metabolic engineering and systems biology. In the most common methodology, fluxes are calculated by global isotopomer balancing and iterative fitting to stationary (13)C-labeling data. This approach requires a closed carbon balance, long-lasting metabolic steady state, and the detection of (13)C-patterns in a large number of metabolites. These restrictions mostly reduced the application of (13)C-MFA to the central carbon metabolism of well-studied model organisms grown in minimal media with a single carbon source. Here we introduce non-stationary (13)C-metabolic flux ratio analysis as a novel method for (13)C-MFA to allow estimating local, relative fluxes from ultra-short (13)C-labeling experiments and without the need for global isotopomer balancing. The approach relies on the acquisition of non-stationary (13)C-labeling data exclusively for metabolites in the proximity of a node of converging fluxes and a local parameter estimation with a system of ordinary differential equations. We developed a generalized workflow that takes into account reaction types and the availability of mass spectrometric data on molecular ions or fragments for data processing, modeling, parameter and error estimation. We demonstrated the approach by analyzing three key nodes of converging fluxes in central metabolism of Bacillus subtilis. We obtained flux estimates that are in agreement with published results obtained from steady state experiments, but reduced the duration of the necessary (13)C-labeling experiment to less than a minute. These results show that our strategy enables to formally estimate relative pathway fluxes on extremely short time scale, neglecting cellular carbon balancing. Hence this approach paves the road to targeted (13)C-MFA in dynamic systems with multiple carbon sources and towards rich media.
Luo, Biao; Wu, Huai-Ning; Li, Han-Xiong
2015-04-01
Highly dissipative nonlinear partial differential equations (PDEs) are widely employed to describe the system dynamics of industrial spatially distributed processes (SDPs). In this paper, we consider the optimal control problem of the general highly dissipative SDPs, and propose an adaptive optimal control approach based on neuro-dynamic programming (NDP). Initially, Karhunen-Loève decomposition is employed to compute empirical eigenfunctions (EEFs) of the SDP based on the method of snapshots. These EEFs together with singular perturbation technique are then used to obtain a finite-dimensional slow subsystem of ordinary differential equations that accurately describes the dominant dynamics of the PDE system. Subsequently, the optimal control problem is reformulated on the basis of the slow subsystem, which is further converted to solve a Hamilton-Jacobi-Bellman (HJB) equation. HJB equation is a nonlinear PDE that has proven to be impossible to solve analytically. Thus, an adaptive optimal control method is developed via NDP that solves the HJB equation online using neural network (NN) for approximating the value function; and an online NN weight tuning law is proposed without requiring an initial stabilizing control policy. Moreover, by involving the NN estimation error, we prove that the original closed-loop PDE system with the adaptive optimal control policy is semiglobally uniformly ultimately bounded. Finally, the developed method is tested on a nonlinear diffusion-convection-reaction process and applied to a temperature cooling fin of high-speed aerospace vehicle, and the achieved results show its effectiveness.
Multivariable adaptive control and estimation of a nonlinear wastewater treatment process
Energy Technology Data Exchange (ETDEWEB)
Ben Youssef, C.; Dahhou, B. [Centre National de la Recherche Scientifique (CNRS), 31 - Toulouse (France)]|[Institut National des Sciences Appliquees (INSA), 31 - Toulouse (France)
1995-12-31
In this paper, an approach for estimating biological state and parameter variables and for controlling a non linear wastewater treatment process is developed. Combination of a nonlinear estimation procedure and a multivariable reference model control law provides favourable performances for tracking a given model-based reference model despite disturbances and system parameter uncertainties. Convergence of both estimation and control scheme are demonstrated via Lyapunov`s method. Simulation study with additive measurements noises and parameter jumps shows the efficiency and significant robustness of the control methodology developed for this non linear process. (author) 13 refs.
De Siena, S; Illuminati, F; Siena, Silvio De; Lisi, Antonio Di; Illuminati, Fabrizio
2002-01-01
We introduce nonlinear canonical transformations that yield effective Hamiltonians of multiphoton down conversion processes, and we define the associated non-Gaussian multiphoton squeezed states as the coherent states of the multiphoton Hamiltonians. We study in detail the four-photon processes and the associated non-Gaussian four-photon squeezed states. The realization of squeezing, the behavior of the field statistics, and the structure of the phase space distributions show that these states realize a natural four-photon generalization of the two-photon squeezed states.
Nonlinear tracking in a diffusion process with a Bayesian filter and the finite element method
DEFF Research Database (Denmark)
Pedersen, Martin Wæver; Thygesen, Uffe Høgsbro; Madsen, Henrik
2011-01-01
A new approach to nonlinear state estimation and object tracking from indirect observations of a continuous time process is examined. Stochastic differential equations (SDEs) are employed to model the dynamics of the unobservable state. Tracking problems in the plane subject to boundaries...... become complicated using SMC because Monte Carlo randomness is introduced. The finite element (FE) method solves the Kolmogorov equations of the SDE numerically on a triangular unstructured mesh for which boundary conditions to the state-space are simple to incorporate. The FE approach to nonlinear state...... estimation is suited for off-line data analysis because the computed smoothed state densities, maximum a posteriori parameter estimates and state sequence are deterministic conditional on the finite element mesh and the observations. The proposed method is conceptually similar to existing point...
Nonlinear dynamics of three-magnon process driven by ferromagnetic resonance in yttrium iron garnet
Energy Technology Data Exchange (ETDEWEB)
Cunha, R. O. [Departamento de Física, Universidade Federal de Pernambuco, 50670-901 Recife, PE (Brazil); Centro Interdisciplinar de Ciências da Natureza, Universidade Federal da Integração Latino-Americana, 85867-970 Foz do Iguaçu, PR (Brazil); Holanda, J.; Azevedo, A.; Rezende, S. M., E-mail: rezende@df.ufpe.br [Departamento de Física, Universidade Federal de Pernambuco, 50670-901 Recife, PE (Brazil); Vilela-Leão, L. H. [Departamento de Física, Universidade Federal de Pernambuco, 50670-901 Recife, PE (Brazil); Centro Acadêmico do Agreste, Universidade Federal de Pernambuco, 55002-970 Caruaru, PE (Brazil); Rodríguez-Suárez, R. L. [Facultad de Física, Pontificia Universidad Católica de Chile, Casilla 306, Santiago (Chile)
2015-05-11
We report an investigation of the dynamics of the three-magnon splitting process associated with the ferromagnetic resonance (FMR) in films of the insulating ferrimagnet yttrium iron garnet (YIG). The experiments are performed with a 6 μm thick YIG film close to a microstrip line fed by a microwave generator operating in the 2–6 GHz range. The magnetization precession is driven by the microwave rf magnetic field perpendicular to the static magnetic field, and its dynamics is observed by monitoring the amplitude of the FMR absorption peak. The time evolution of the amplitude reveals that if the frequency is lowered below a critical value of 3.3 GHz, the FMR mode pumps two magnons with opposite wave vectors that react back on the FMR, resulting in a nonlinear dynamics of the magnetization. The results are explained by a model with coupled nonlinear equations describing the time evolution of the magnon modes.
Directory of Open Access Journals (Sweden)
Hong Qin
2000-08-01
Full Text Available Collective processes in intense charged particle beams described self-consistently by the Vlasov-Maxwell equations are studied using a 3D multispecies nonlinear perturbative particle simulation method. The newly developed beam equilibrium, stability, and transport (BEST code is used to simulate the nonlinear stability properties of intense beam propagation, surface eigenmodes in a high-intensity beam, and the electron-proton (e-p two-stream instability observed in the Proton Storage Ring (PSR experiment. Detailed simulations in a parameter regime characteristic of the PSR experiment show that the dipole-mode two-stream instability is stabilized by a modest spread (about 0.1% in axial momentum of the beam particles.
Numerical simulation of nonlinear processes in a beam-plasma system
Energy Technology Data Exchange (ETDEWEB)
Efimova, A. A., E-mail: anna.an.efimova@gmail.com; Berendeev, E. A.; Vshivkov, V. A. [Institute of Computational Mathematics and Mathematical Geophysics SB RAS 6 Acad. Lavrentyev Ave., Novosibirsk 630090 (Russian Federation); Dudnikova, G. I. [University of Maryland, College Park, MD 20742 (United States); Institute of Computational Technologies SB RAS, 6 Acad. Lavrentyev Ave., Novosibirsk 630090 (Russian Federation)
2015-10-28
In the present paper we consider the efficiency of the electromagnetic radiation generation due to various nonlinear processes in the beam-plasma system. The beam and plasma parameters were chosen close to the parameters in the experiment on the GOL-3 facility (BINP SB RAS). The model of the collisionless plasma is described by system of the Vlasov-Maxwell equations with periodic boundary conditions. The parallel numerical algorithm is based on the particles-in-cell method (PIC) with mixed Euler-Lagrangian domain decomposition. Various scenarios of nonlinear evolution in the beam-plasma system under the influence of an external magnetic field in case of a low density beam were studied. The energy transfer from one unstable mode to the others modes was observed.
DEFF Research Database (Denmark)
Porto da Silva, Edson
Digital signal processing (DSP) has become one of the main enabling technologies for the physical layer of coherent optical communication networks. The DSP subsystems are used to implement several functionalities in the digital domain, from synchronization to channel equalization. Flexibility...... nonlinearity compensation, (II) spectral shaping, and (III) adaptive equalization. For (I), original contributions are presented to the study of the nonlinearity compensation (NLC) with digital backpropagation (DBP). Numerical and experimental performance investigations are shown for different application...... scenarios. Concerning (II), it is demonstrated how optical and electrical (digital) pulse shaping can be allied to improve the spectral confinement of a particular class of optical time-division multiplexing (OTDM) signals that can be used as a building block for fast signaling single-carrier transceivers...
Anticipation and the Non-linear Dynamics of Meaning-Processing in Social Systems
Leydesdorff, Loet
2009-01-01
Social order does not exist as a stable phenomenon, but can be considered as "an order of reproduced expectations." When anticipations operate upon one another, they can generate a non-linear dynamics which processes meaning. Although specific meanings can be stabilized, for example in social institutions, all meaning arises from a global horizon of possible meanings. Using Luhmann's (1984) social systems theory and Rosen's (1985) theory of anticipatory systems, I submit algorithms for modeling the non-linear dynamics of meaning in social systems. First, a self-referential system can use a model of itself for the anticipation. Under the condition of functional differentiation, the social system can be expected to entertain a set of models; each model can also contain a model of the other models. Two anticipatory mechanisms are then possible: a transversal one between the models, and a longitudinal one providing the system with a variety of meanings. A system containing two anticipatory mechanisms can become h...
Jiang, Ning; Parker, Philip A; Englehart, Kevin B
2009-08-01
The spectrum of nonstationary electromyographic signal (EMG) is investigated, from which the error for neural drive information estimation from nonstationary EMG is studied in terms of signal-to-noise ratio (SNR), in analytical, numerical simulation, and experimental work. The signal refers to the neural drive information embedded within the nonstationary EMG, and noise refers to other portions of EMG that induce error in the estimation. The analytical expressions for the SNRs of force-modulated EMG with both single and multiple motor units (MU) are derived based on a sinusoidal integral pulse frequency modulation (IPFM) model. It is shown that the previously developed SNR expressions for stationary (unmodulated) EMG are special cases of the formulas presented here. The SNR results obtained from numerical simulated EMG agree very well with the analytical result. Results from nonstationary (modulated) surface EMG obtained from seven subjects also match the analytical and simulation results reasonably well. The results obtained from this work establish an analytical framework in studying and estimating the neural drive information contained in the EMG in the context of anisotonic and isometric contractions. Through the analytical study, the effects of different physiological parameters are identified, thus providing theoretical guidelines for developing advanced signal processing methods for nonstationary EMG in applications such as prosthesis control.
Nonstationary photonic jet from dielectric microsphere
Geints, Yu; Zemlyanov, A
2014-01-01
A photonic jet commonly denotes the specific spatially localized region in the near-field forward scattering of a light wave at a dielectric micron-sized particle. We present the detailed calculations of the transient response of an airborne silica microsphere illuminated by a femtosecond laser pulse. The spatial area constituting the photonic jet is theoretically investigated and the temporal dynamics of jet dimensions as well as of jet peak intensity is analyzed. The role of morphology-dependent resonances in jet formation is highlighted. The evolution scenario of a nonstationary photonic jet generally consists of the non-resonant and resonant temporal phases. In every phase, the photonic jet can change its spatial form and intensity.
Taylor, Z A; Cheng, M; Ourselin, S
2008-05-01
The use of biomechanical modelling, especially in conjunction with finite element analysis, has become common in many areas of medical image analysis and surgical simulation. Clinical employment of such techniques is hindered by conflicting requirements for high fidelity in the modelling approach, and fast solution speeds. We report the development of techniques for high-speed nonlinear finite element analysis for surgical simulation. We use a fully nonlinear total Lagrangian explicit finite element formulation which offers significant computational advantages for soft tissue simulation. However, the key contribution of the work is the presentation of a fast graphics processing unit (GPU) solution scheme for the finite element equations. To the best of our knowledge, this represents the first GPU implementation of a nonlinear finite element solver. We show that the present explicit finite element scheme is well suited to solution via highly parallel graphics hardware, and that even a midrange GPU allows significant solution speed gains (up to 16.8 x) compared with equivalent CPU implementations. For the models tested the scheme allows real-time solution of models with up to 16,000 tetrahedral elements. The use of GPUs for such purposes offers a cost-effective high-performance alternative to expensive multi-CPU machines, and may have important applications in medical image analysis and surgical simulation.
Selvendran, S.; Sivanantharaja, A.; Arivazhagan, S.; Kannan, M.
2016-09-01
We propose an index profiled, highly nonlinear ultraflattened dispersion fibre (HN-UFF) with appreciable values of fibre parameters such as dispersion, dispersion slope, effective area, nonlinearity, bending loss and splice loss. The designed fibre has normal zero flattened dispersion over S, C, L, U bands and extends up to 1.9857 μm. The maximum dispersion variation observed for this fibre is as low as 1.61 ps km-1 nm-1 over the 500-nm optical fibre transmission spectrum. This fibre also has two zero dispersion wavelengths at 1.487 and 1.9857 μm and the respective dispersion slopes are 0.02476 and 0.0068 ps nm-2 km-1. The fibre has a very low ITU-T cutoff wavelength of 1.2613 μm and a virtuous nonlinear coefficient of 9.43 W-1 km-1. The wide spectrum of zero flattened dispersion and a good nonlinear coefficient make the designed fibre very promising for different nonlinear optical signal processing applications.
Noise Cancellation with Static Mixtures of a Nonstationary Signal and Stationary Noise
Directory of Open Access Journals (Sweden)
Sharon Gannot
2003-01-01
Full Text Available We address the problem of cancelling a stationary noise component from its static mixtures with a nonstationary signal of interest. Two different approaches, both based on second-order statistics, are considered. The first is the blind source separation (BSS approach which aims at estimating the mixing parameters via approximate joint diagonalization of estimated correlation matrices. Proper exploitation of the nonstationary nature of the desired signal, in contrast to the stationarity of the noise, allows parameterization of the joint diagonalization problem in terms of a nonlinear weighted least squares (WLS problem. The second approach is a denoising approach, which translates into direct estimation of just one of the mixing coefficients via solution of a linear WLS problem, followed by the use of this coefficient to create a noise-only signal to be properly eliminated from the mixture. Under certain assumptions, the BSS approach is asymptotically optimal, yet computationally more intense, since it involves an iterative nonlinear WLS solution, whereas the second approach only requires a closed-form linear WLS solution. We analyze and compare the performance of the two approaches and provide some simulation results which confirm our analysis. Comparison to other methods is also provided.
Non-equilibrium condensation process in holographic superconductor with nonlinear electrodynamics
Liu, Yunqi; Wang, Bin
2015-01-01
We study the non-equilibrium condensation process in a holographic superconductor with nonlinear corrections to the U(1) gauge field. We start with an asymptotic Anti-de-Sitter(AdS) black hole against a complex scalar perturbation at the initial time, and solve the dynamics of the gravitational systems in the bulk. When the black hole temperature T is smaller than a critical value Tc, the scalar perturbation grows exponentially till saturation, the final state of spacetime approaches to a hairy black hole. In the bulk theory, we find the clue of the influence of nonlinear corrections in the gauge field on the process of the scalar field condensation. We show that the bulk dynamics in the non-equilibrium process is completely consistent with the observations on the boundary order parameter. Furthermore we examine the time evolution of horizons in the bulk non-equilibrium transformation process from the bald AdS black hole to the AdS hairy hole. Both the evolution of apparent and event horizons show that the or...
Vavulin, D. N.; Sukhorukov, A. A.
2016-08-01
We present an analytical description of the process of spontaneous four-wave mixing in a cubic nonlinear fiber with linear losses. We consider the generation of photon pairs in the fiber when in the input of fiber is fed the pumping wave and single signal photon. The focus of attention is on three cases: when the signal photon propagates in the fiber without generating of biphotons; when the photon pair is generated; and when the photon is lost in the fiber. We also consider the cascade processes, but do not give them an analytical description because of their smallness. Description of the biphotons generation process we provide using the Schrodinger-type equation, and take into account the losses in the fiber through the introduction of the virtual beam splitters. We demonstrate the effectiveness of the generation of photon pairs through parametric processes.
Definition of distance for nonlinear time series analysis of marked point process data
Energy Technology Data Exchange (ETDEWEB)
Iwayama, Koji, E-mail: koji@sat.t.u-tokyo.ac.jp [Research Institute for Food and Agriculture, Ryukoku Univeristy, 1-5 Yokotani, Seta Oe-cho, Otsu-Shi, Shiga 520-2194 (Japan); Hirata, Yoshito; Aihara, Kazuyuki [Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505 (Japan)
2017-01-30
Marked point process data are time series of discrete events accompanied with some values, such as economic trades, earthquakes, and lightnings. A distance for marked point process data allows us to apply nonlinear time series analysis to such data. We propose a distance for marked point process data which can be calculated much faster than the existing distance when the number of marks is small. Furthermore, under some assumptions, the Kullback–Leibler divergences between posterior distributions for neighbors defined by this distance are small. We performed some numerical simulations showing that analysis based on the proposed distance is effective. - Highlights: • A new distance for marked point process data is proposed. • The distance can be computed fast enough for a small number of marks. • The method to optimize parameter values of the distance is also proposed. • Numerical simulations indicate that the analysis based on the distance is effective.
Hawking effect of Dirac particles in non-stationary Kerr space-time
Institute of Scientific and Technical Information of China (English)
黎忠恒; 赵峥
1995-01-01
In the process of dealing with the Hawking effect of Dirac particles in the non-stationary Kerr space-time, a new universal method to define the generalized Tortoise coordinate transformation is given. By means of this coordinate transformation, one can discuss the properties of the dynamical equation of particles near event horizons, and get automatically the temperature of Hawking radiation using the method suggested by Damour and others, and thereby dodge the difficulties in calculating the renormalised energy-momentum tensor.
Analyses of non-linear systems and their application to biology: a review.
Sato, S
1994-01-01
In this review article, Wiener's analyses of non-linear systems and other topics on non-linear noise and non-stationary signals are introduced. Firstly, application and limitation of linear aspects on a biological system and a background of introduction of the Wiener's theory to non-linear analysis are briefly mentioned. The practical applications, however, were not so successful for several reasons. We shall see how these problems are solved under collaboration between biologists and engineers who have a knowledge of the subject and utilizing computational facility. Several aspects of the methodology involving non-linear systems, non-linear noise and non-stationary signals are also reviewed.
Stability of nonstationary solutions of the generalized KdV-Burgers equation
Chugainova, A. P.; Shargatov, V. A.
2015-02-01
The stability of nonstationary solutions to the Cauchy problem for a model equation with a complex nonlinearity, dispersion, and dissipation is analyzed. The equation describes the propagation of nonlinear longitudinal waves in rods. Previously, complex behavior of traveling waves was found, which can be treated as discontinuity structures in solutions of the same equation without dissipation and dispersion. As a result, the solutions of standard self-similar problems constructed as a sequence of Riemann waves and shocks with a stationary structure become multivalued. The multivaluedness of the solutions is attributed to special discontinuities caused by the large effect of dispersion in conjunction with viscosity. The stability of special discontinuities in the case of varying dispersion and dissipation parameters is analyzed numerically. The computations performed concern the stability analysis of a special discontinuity propagating through a layer with varying dispersion and dissipation parameters.
Thiombiano, Alida N.; El Adlouni, Salaheddine; St-Hilaire, André; Ouarda, Taha B. M. J.; El-Jabi, Nassir
2016-04-01
In this paper, a statistical inference of Southeastern Canada extreme daily precipitation amounts is proposed using a classical nonstationary peaks-over-threshold model. Indeed, the generalized Pareto distribution (GPD) is fitted to excess time series derived from annual averages of independent precipitation amount events above a fixed threshold, the 99th percentile. Only the scale parameter of the fitted distribution is allowed to vary as a function of a covariate. This variability is modeled using B-spline function. Nonlinear correlation and cross-wavelet analysis allowed identifying two dominant climate indices as covariates in the study area, Arctic Oscillation (AO) and Pacific North American (PNA). The nonstationary frequency analysis showed that there is an east-west behavior of the AO index effects on extreme daily precipitation amounts in the study area. Indeed, the higher quantiles of these events are conditional to the AO positive phase in Atlantic Canada, while those in the more southeastern part of Canada, especially in Southern Quebec and Ontario, are negatively related to AO. The negative phase of PNA also gives the best significant correlation in these regions. Moreover, a regression analysis between AO (PNA) index and conditional quantiles provided slope values for the positive phase of the index on the one hand and the negative phase and on the other hand. This statistic allows computing a slope ratio which permits to sustain the nonlinear relation assumption between climate indices and precipitation and the development of the nonstationary GPD model for Southeastern Canada extremes precipitation modeling.
Thiombiano, Alida N.; El Adlouni, Salaheddine; St-Hilaire, André; Ouarda, Taha B. M. J.; El-Jabi, Nassir
2017-07-01
In this paper, a statistical inference of Southeastern Canada extreme daily precipitation amounts is proposed using a classical nonstationary peaks-over-threshold model. Indeed, the generalized Pareto distribution (GPD) is fitted to excess time series derived from annual averages of independent precipitation amount events above a fixed threshold, the 99th percentile. Only the scale parameter of the fitted distribution is allowed to vary as a function of a covariate. This variability is modeled using B-spline function. Nonlinear correlation and cross-wavelet analysis allowed identifying two dominant climate indices as covariates in the study area, Arctic Oscillation (AO) and Pacific North American (PNA). The nonstationary frequency analysis showed that there is an east-west behavior of the AO index effects on extreme daily precipitation amounts in the study area. Indeed, the higher quantiles of these events are conditional to the AO positive phase in Atlantic Canada, while those in the more southeastern part of Canada, especially in Southern Quebec and Ontario, are negatively related to AO. The negative phase of PNA also gives the best significant correlation in these regions. Moreover, a regression analysis between AO (PNA) index and conditional quantiles provided slope values for the positive phase of the index on the one hand and the negative phase and on the other hand. This statistic allows computing a slope ratio which permits to sustain the nonlinear relation assumption between climate indices and precipitation and the development of the nonstationary GPD model for Southeastern Canada extremes precipitation modeling.
Intrinsic Nonlinearities and Layout Impacts of 100 V Integrated Power MOSFETs in Partial SOI Process
DEFF Research Database (Denmark)
Fan, Lin; Knott, Arnold; Jørgensen, Ivan Harald Holger
Parasitic capacitances of power semiconductors are a part of the key design parameters of state-of-the-art very high frequency (VHF) power supplies. In this poster, four 100 V integrated power MOSFETs with different layout structures are designed, implemented, and analyzed in a 0.18 ȝm partial...... Silicon-on-Insulator (SOI) process with a die area 2.31 mm2. A small-signal model of power MOSFETs is proposed to systematically analyze the nonlinear parasitic capacitances in different transistor states: off-state, sub-threshold region, and on-state in the linear region. 3D plots are used to summarize...
Time-ordering effects in the generation of entangled photons using nonlinear optical processes.
Quesada, Nicolás; Sipe, J E
2015-03-06
We study the effects of time ordering in photon generation processes such as spontaneous parametric down-conversion (SPDC) and four wave mixing (SFWM). The results presented here are used to construct an intuitive picture that allows us to predict when time-ordering effects significantly modify the joint spectral amplitude (JSA) of the photons generated in SPDC and SFWM. These effects become important only when the photons being generated lie with the pump beam that travels through the nonlinear material for a significant amount of time. Thus sources of spectrally separable photons are ideal candidates for the observation of modifications of the JSA due to time ordering.
Imitation learning of Non-Linear Point-to-Point Robot Motions using Dirichlet Processes
DEFF Research Database (Denmark)
Krüger, Volker; Tikhanoff, Vadim; Natale, Lorenzo
2012-01-01
In this paper we discuss the use of the infinite Gaussian mixture model and Dirichlet processes for learning robot movements from demonstrations. Starting point of this work is an earlier paper where the authors learn a non-linear dynamic robot movement model from a small number of observations....... The model in that work is learned using a classical finite Gaussian mixture model (FGMM) where the Gaussian mixtures are appropriately constrained. The problem with this approach is that one needs to make a good guess for how many mixtures the FGMM should use. In this work, we generalize this approach...
Calatroni, Luca
2013-08-01
We present directional operator splitting schemes for the numerical solution of a fourth-order, nonlinear partial differential evolution equation which arises in image processing. This equation constitutes the H -1-gradient flow of the total variation and represents a prototype of higher-order equations of similar type which are popular in imaging for denoising, deblurring and inpainting problems. The efficient numerical solution of this equation is very challenging due to the stiffness of most numerical schemes. We show that the combination of directional splitting schemes with implicit time-stepping provides a stable and computationally cheap numerical realisation of the equation.
A process fault estimation strategy for non-linear dynamic systems
Pazera, Marcin; Korbicz, Józef
2017-01-01
The paper deals with the problem of simultaneous state and process fault estimation for non-linear dynamic systems. Instead of estimating the fault directly, its product with state and the state itself are estimated. To derive the fault from the product, a simple algebraic approach is proposed. The estimation strategy is based on the quadratic boundedness approach. The final part of the paper presents an illustrative example concerning a laboratory multi-tank system. The real data experiments clearly exhibit the performance of the proposed approach.
Estimation and filtering of nonlinear systems application to a waste-water treatment process
Energy Technology Data Exchange (ETDEWEB)
Ben Youssef, C.; Dahhou, B. [Centre National de la Recherche Scientifique (CNRS), 31 - Toulouse (France). Lab. d`Automatique et d`Analyse des Systemes]|[Institut National des Sciences Appliquees (INSA), 31 - Toulouse (France); Zeng, F.Y.; Rols, J.L. [Institut National des Sciences Appliquees (INSA), 31 - Toulouse (France)
1994-04-01
A fundamental task in design and control of biotechnological processes is system modelling. This task is made difficult by the scarceness of on-line direct sensors for some key variables and by the fact that identifiability of models including Michaelis-Menten type of nonlinearities is not straightforward. The use of adaptive estimation approaches constitutes an interesting alternative to circumvent these kind of problems. This paper discusses an identification technique derived to solve the problem of estimating simultaneously inaccessible state variables and time-varying parameters of a nonlinear wastewater treatment process. An extended linearization technique using Kronecker`s calculation provides the error model of the joint observer-estimator procedure which convergence is proved via Lyapunov`s method. Sufficient conditions for stability of this joint identification scheme are given and discussed according to the persistence excitation conditions of the signals. A simulation study with measurement noises and abrupt jumps of the process parameters shows the feasibility and significant robustness of the proposed adaptive estimation methodologies. (author). (author). 10 refs., 3 figs.
Thermal Radiation of a General Non-stationary Black Hole
Institute of Scientific and Technical Information of China (English)
杨成全; 任秦安; 赵峥
1994-01-01
The thermal radiation of the most general non-stationary black holes is discussed in this paper.The universal representatives determining the location of an event horizon and the temperature function are given.
A new cellular nonlinear network emulation on FPGA for EEG signal processing in epilepsy
Müller, Jens; Müller, Jan; Tetzlaff, Ronald
2011-05-01
For processing of EEG signals, we propose a new architecture for the hardware emulation of discrete-time Cellular Nonlinear Networks (DT-CNN). Our results show the importance of a high computational accuracy in EEG signal prediction that cannot be achieved with existing analogue VLSI circuits. The refined architecture of the processing elements and its resource schedule, the cellular network structure with local couplings, the FPGA-based embedded system containing the DT-CNN, and the data flow in the entire system will be discussed in detail. The proposed DT-CNN design has been implemented and tested on an Xilinx FPGA development platform. The embedded co-processor with a multi-threading kernel is utilised for control and pre-processing tasks and data exchange to the host via Ethernet. The performance of the implemented DT-CNN has been determined for a popular example and compared to that of a conventional computer.
Zhu, Wenlong; Ma, Shoufeng; Tian, Junfang; Li, Geng
2016-11-01
Travelers' route adjustment behaviors in a congested road traffic network are acknowledged as a dynamic game process between them. Existing Proportional-Switch Adjustment Process (PSAP) models have been extensively investigated to characterize travelers' route choice behaviors; PSAP has concise structure and intuitive behavior rule. Unfortunately most of which have some limitations, i.e., the flow over adjustment problem for the discrete PSAP model, the absolute cost differences route adjustment problem, etc. This paper proposes a relative-Proportion-based Route Adjustment Process (rePRAP) maintains the advantages of PSAP and overcomes these limitations. The rePRAP describes the situation that travelers on higher cost route switch to those with lower cost at the rate that is unilaterally depended on the relative cost differences between higher cost route and its alternatives. It is verified to be consistent with the principle of the rational behavior adjustment process. The equivalence among user equilibrium, stationary path flow pattern and stationary link flow pattern is established, which can be applied to judge whether a given network traffic flow has reached UE or not by detecting the stationary or non-stationary state of link flow pattern. The stability theorem is proved by the Lyapunov function approach. A simple example is tested to demonstrate the effectiveness of the rePRAP model.
Tunnelling effect of the non-stationary Kerr black hole
Institute of Scientific and Technical Information of China (English)
Yang Shu-Zheng; Chen De-You
2008-01-01
Extending Parikh and Wilezek's work to the non-stationary black hole, we study the Hawking radiation of the non-stationary Kerr black hole by the Hamilton-Jacobi method. The result shows that the radiation spectrum is not purely thermal and the tunnelling probability is related to the change of Bekenstein-Hawking entropy, which gives a correction to the Hawking thermal radiation of the black hole.
A Comparison of PSD Enveloping Methods for Nonstationary Vibration
Irvine, Tom
2015-01-01
There is a need to derive a power spectral density (PSD) envelope for nonstationary acceleration time histories, including launch vehicle data, so that components can be designed and tested accordingly. This paper presents the results of the three methods for an actual flight accelerometer record. Guidelines are given for the application of each method to nonstationary data. The method can be extended to other scenarios, including transportation vibration.
Personnel planning in service systems with nonstationary demand.
Defraeye, Mieke
2014-01-01
1. Introduction 2. Staffing and scheduling with nonstationary demand for service: state of the art 3. Computing the probability of excessive waiting in M(t)/G/s(t) + G queues with an exhaustive service policy 4. Controlling excessive waiting times in small service systems with time-varying demand: an extension of the ISA algorithm 5. A branch-and-bound algorithm for shift scheduling with nonstationary demand 6. Epilogue
Exact Stationary and Non-stationary Solutions to Inelastic Maxwell Model with Infinite Energy
Ilyin, Oleg
2016-11-01
The one-dimensional inelastic Boltzmann equation with a constant collision rate (the Maxwell model) is considered. It is shown that for special values of restitution parameter there exists a stationary solution with the characteristic function in the form e^{-P(log (z))z}, where P is a periodic function. The corresponding distribution function belongs to a one special class of stochastic processes termed as a generalized stable in the probability theory. The Fourier transform of the non-stationary equation has the solution bigl (1+P(log (z))zbigr )e^{-Q(log (z))z}. It is proved that this solution is a characteristic function if periodic functions P, Q satisfy some not very restrictive conditions. The stationary and non-stationary solutions correspond to a gas with infinite temperature.
Nonlinear software sensor for monitoring genetic regulation processes with noise and modeling errors
Ibarra-Junquera, V.; Torres, L. A.; Rosu, H. C.; Argüello, G.; Collado-Vides, J.
2005-07-01
Nonlinear control techniques by means of a software sensor that are commonly used in chemical engineering could be also applied to genetic regulation processes. We provide here a realistic formulation of this procedure by introducing an additive white Gaussian noise, which is usually found in experimental data. Besides, we include model errors, meaning that we assume we do not know the nonlinear regulation function of the process. In order to illustrate this procedure, we employ the Goodwin dynamics of the concentrations [B. C. Goodwin, Temporal Oscillations in Cells (Academic, New York, 1963)] in the simple form recently applied to single gene systems and some operon cases [H. De Jong, J. Comput. Biol. 9, 67 (2002)], which involves the dynamics of the mRNA, given protein and metabolite concentrations. Further, we present results for a three gene case in coregulated sets of transcription units as they occur in prokaryotes. However, instead of considering their full dynamics, we use only the data of the metabolites and a designed software sensor. We also show, more generally, that it is possible to rebuild the complete set of nonmeasured concentrations despite the uncertainties in the regulation function or, even more, in the case of not knowing the mRNA dynamics. In addition, the rebuilding of concentrations is not affected by the perturbation due to the additive white Gaussian noise and also we managed to filter the noisy output of the biological system.
Munck, Sebastian; Miskiewicz, Katarzyna; Sannerud, Ragna; Menchon, Silvia A; Jose, Liya; Heintzmann, Rainer; Verstreken, Patrik; Annaert, Wim
2012-05-01
Visualization of organelles and molecules at nanometer resolution is revolutionizing the biological sciences. However, such technology is still limited for many cell biologists. We present here a novel approach using photobleaching microscopy with non-linear processing (PiMP) for sub-diffraction imaging. Bleaching of fluorophores both within the single-molecule regime and beyond allows visualization of stochastic representations of sub-populations of fluorophores by imaging the same region over time. Our method is based on enhancing the probable positions of the fluorophores underlying the images. The random nature of the bleached fluorophores is assessed by calculating the deviation of the local actual bleached fluorescence intensity to the average bleach expectation as given by the overall decay of intensity. Subtracting measured from estimated decay images yields differential images. Non-linear enhancement of maxima in these diffraction-limited differential images approximates the positions of the underlying structure. Summing many such processed differential images yields a super-resolution PiMP image. PiMP allows multi-color, three-dimensional sub-diffraction imaging of cells and tissues using common fluorophores and can be implemented on standard wide-field or confocal systems.
Li, Huanhuan; Chen, Diyi; Zhang, Hao; Wang, Feifei; Ba, Duoduo
2016-12-01
In order to study the nonlinear dynamic behaviors of a hydro-turbine governing system in the process of sudden load increase transient, we establish a novel nonlinear dynamic model of the hydro-turbine governing system which considers the elastic water-hammer model of the penstock and the second-order model of the generator. The six nonlinear dynamic transfer coefficients of the hydro-turbine are innovatively proposed by utilizing internal characteristics and analyzing the change laws of the characteristic parameters of the hydro-turbine governing system. Moreover, from the point of view of engineering, the nonlinear dynamic behaviors of the above system are exhaustively investigated based on bifurcation diagrams and time waveforms. More importantly, all of the above analyses supply theoretical basis for allowing a hydropower station to maintain a stable operation in the process of sudden load increase transient.
Institute of Scientific and Technical Information of China (English)
Zhiyun Zou; Dandan Zhao; Xinghong Liu; Yuqing Guo; Chen Guan; Wenqiang Feng; Ning Guo
2015-01-01
By taking advantage of the separation characteristics of nonlinear gain and dynamic sector inside a Hammerstein model, a novel pole placement self tuning control scheme for nonlinear Hammerstein system was put forward based on the linear system pole placement self tuning control algorithm. And the nonlinear Hammerstein system pole placement self tuning control (NL-PP-STC) algorithm was presented in detail. The identification ability of its parameter estimation algorithm of NL-PP-STC was analyzed, which was always identifiable in closed loop. Two particular problems including the selection of poles and the on-line estimation of model parameters, which may be met in applications of NL-PP-STC to real process control, were discussed. The control simulation of a strong nonlinear pH neutralization process was carried out and good control performance was achieved.
Institute of Scientific and Technical Information of China (English)
陶华学; 郭金运
2003-01-01
Data coming from different sources have different types and temporal states. Relations between one type of data and another ones, or between data and unknown parameters are almost nonlinear. It is not accurate and reliable to process the data in building the digital earth with the classical least squares method or the method of the common nonlinear least squares. So a generalized nonlinear dynamic least squares method was put forward to process data in building the digital earth. A separating solution model and the iterative calculation method were used to solve the generalized nonlinear dynamic least squares problem. In fact, a complex problem can be separated and then solved by converting to two sub-problems, each of which has a single variable. Therefore the dimension of unknown parameters can be reduced to its half, which simplifies the original high dimensional equations.
Institute of Scientific and Technical Information of China (English)
Kechang FU; Liankui DAI; Tiejun WU; Ming ZHU
2009-01-01
A new sensor fault diagnosis method based on structured kernel principal component analysis (KPCA) is proposed for nonlinear processes.By performing KPCA on subsets of variables,a set of structured residuals,i.e.,scaled powers of KPCA,can be obtained in the same way as partial PCA.The structured residuals are utilized in composing an isolation scheme for sensor fault diagnosis,according to a properly designed incidence matrix.Sensor fault sensitivity and critical sensitivity are defined,based on which an incidence matrix optimization algorithm is proposed to improve the performance of the structured KPCA.The effectiveness of the proposed method is demonstrated on the simulated continuous stirred tank reactor (CSTR) process.
Development of a robust calibration model for nonlinear in-line process data
Despagne; Massart; Chabot
2000-04-01
A comparative study involving a global linear method (partial least squares), a local linear method (locally weighted regression), and a nonlinear method (neural networks) has been performed in order to implement a calibration model on an industrial process. The models were designed to predict the water content in a reactor during a distillation process, using in-line measurements from a near-infrared analyzer. Curved effects due to changes in temperature and variations between the different batches make the problem particularly challenging. The influence of spectral range selection and data preprocessing has been studied. With each calibration method, specific procedures have been applied to promote model robustness. In particular, the use of a monitoring set with neural networks does not always prevent overfitting. Therefore, we developed a model selection criterion based on the determination of the median of monitoring error over replicate trials. The back-propagation neural network models selected were found to outperform the other methods on independent test data.
Nonlinear mechanisms to Rogue events in the process of interaction between optical filaments
Kovachev, L M
2015-01-01
We investigate two types of nonlinear interaction between collinear femtosecond laser pulses with power slightly above the critical for self-focusing $P_{cr}$. In the first case we study energy exchange between filaments. The model describes this process through degenerate four-photon parametric mixing (FPPM) scheme and requests initial phase difference between the waves. When there are no initial phase difference between the pulses, the FPPM process does not work. In this case it is obtained the second type of interaction as merging between two, three or four filaments in a single filament with higher power. It is found that in the second case the interflow between the filaments has potential of interaction due to cross-phase modulation (CPM).
Improved Kernel PLS-based Fault Detection Approach for Nonlinear Chemical Processes
Institute of Scientific and Technical Information of China (English)
王丽; 侍洪波
2014-01-01
In this paper, an improved nonlinear process fault detection method is proposed based on modified ker-nel partial least squares (KPLS). By integrating the statistical local approach (SLA) into the KPLS framework, two new statistics are established to monitor changes in the underlying model. The new modeling strategy can avoid the Gaussian distribution assumption of KPLS. Besides, advantage of the proposed method is that the kernel latent variables can be obtained directly through the eigen value decomposition instead of the iterative calculation, which can improve the computing speed. The new method is applied to fault detection in the simulation benchmark of the Tennessee Eastman process. The simulation results show superiority on detection sensitivity and accuracy in com-parison to KPLS monitoring.
Leydesdorff, Loet; de Nooy, Wouter
2012-01-01
The process of innovation follows non-linear patterns across the domains of science, technology, and the economy. Novel bibliometric mapping techniques can be used to investigate and represent distinctive, but complementary perspectives on the innovation process (e.g., "demand" and "supply") as well as the interactions among these perspectives. The perspectives can be represented as "continents" of data related to varying extents over time. For example, the different branches of Medical Subject Headings (MeSH) in the Medline database provide sources of such perspectives (e.g., "Diseases" versus "Drugs and Chemicals"). The multiple-perspective approach enables us to reconstruct facets of the dynamics of innovation, in terms of selection mechanisms shaping localizable trajectories and/or resulting in more globalized regimes. By expanding the data with patents and scholarly publications, we demonstrate the use of this multi-perspective approach in the case of RNA Interference (RNAi). The possibility to develop a...
Directory of Open Access Journals (Sweden)
G.S. Vorobyov
2014-04-01
Full Text Available The article describes the experimental equipment and the results of investigations of nonlinear processes occurring during the excitation of electromagnetic oscillations in the resonant electron beam devices such as an orotron-generator of diffraction radiation. These devices are finding wide application in physics and microwave technology, now. A technique for experimental research, which bases on the using of the universal electro vacuum equipment diffraction radiation analyzer and the microprocessor system for collecting and processing data. The experimental investigations results of the energy and frequency characteristics for the most common modes of the excitation oscillations in the open resonant systems such as an orotron. The implementations on the optimum modes for the oscillations excitation in such devices were recommended.
Hybrid modelling of a sugar boiling process
Lauret, Alfred Jean Philippe; Gatina, Jean Claude
2012-01-01
The first and maybe the most important step in designing a model-based predictive controller is to develop a model that is as accurate as possible and that is valid under a wide range of operating conditions. The sugar boiling process is a strongly nonlinear and nonstationary process. The main process nonlinearities are represented by the crystal growth rate. This paper addresses the development of the crystal growth rate model according to two approaches. The first approach is classical and consists of determining the parameters of the empirical expressions of the growth rate through the use of a nonlinear programming optimization technique. The second is a novel modeling strategy that combines an artificial neural network (ANN) as an approximator of the growth rate with prior knowledge represented by the mass balance of sucrose crystals. The first results show that the first type of model performs local fitting while the second offers a greater flexibility. The two models were developed with industrial data...
Slow and fast light using nonlinear processes in semiconductor optical amplifiers
Pesala, Bala Subrahmanyam
Ability to control the velocity of light is usually referred to as slow or fast light depending on whether the group velocity of light is reduced or increased. The slowing of light as it passes through the glass to 2/3rd its original value is a well known phenomenon. This slowing down happens due to the interaction of light with the electrons in the medium. As a general principle, stronger the interaction, larger is the reduction in velocity. Recently, a fascinating field has emerged with the objective of not only slowing down the velocity of light but also speeding it up as it goes through the medium by enhancing light-matter interaction. This unprecedented control opens up several exciting applications in various scientific disciplines ranging from nonlinear science, RF photonics to all-optical networks. Initial experiments succeeded in reducing the velocity of light more than a million times to a very impressive 17 m/s. This speed reduction is extremely useful to enhance various nonlinear processes. For RF photonic applications including phased array antennas and tunable filters, control of phase velocity of light is required while control of group velocity serves various functionalities including packet synchronization and contention resolution in an optical buffer. Within the last 10 years, several material systems have been proposed and investigated for this purpose. Schemes based on semiconductor systems for achieving slow and fast light has the advantage of extremely high speed and electrical control. In addition, they are compact, operate at room temperature and can be easily integrated with other optical subsystems. In this work, we propose to use nonlinear processes in semiconductor optical amplifiers (SOAs) for the purpose of controlling the velocity of light. The versatility of the physical processes present in SOAs enables the control of optical signals ranging from 1GHz to larger than 1000 GHz (1 THz). First, we experimentally demonstrate both
Model of non-stationary, inhomogeneous turbulence
Bragg, Andrew D.; Kurien, Susan; Clark, Timothy T.
2017-02-01
We compare results from a spectral model for non-stationary, inhomogeneous turbulence (Besnard et al. in Theor Comp Fluid Dyn 8:1-35, 1996) with direct numerical simulation (DNS) data of a shear-free mixing layer (SFML) (Tordella et al. in Phys Rev E 77:016309, 2008). The SFML is used as a test case in which the efficacy of the model closure for the physical-space transport of the fluid velocity field can be tested in a flow with inhomogeneity, without the additional complexity of mean-flow coupling. The model is able to capture certain features of the SFML quite well for intermediate to long times, including the evolution of the mixing-layer width and turbulent kinetic energy. At short-times, and for more sensitive statistics such as the generation of the velocity field anisotropy, the model is less accurate. We propose two possible causes for the discrepancies. The first is the local approximation to the pressure-transport and the second is the a priori spherical averaging used to reduce the dimensionality of the solution space of the model, from wavevector to wavenumber space. DNS data are then used to gauge the relative importance of both possible deficiencies in the model.
Zhang, Bo
The past decade has witnessed astounding boom in telecommunication network traffic. With the emergence of multimedia over Internet, the high-capacity optical transport systems have started to shift focus from the core network towards the end users. This trend leads to diverse optical networks with transparency and reconfigurability requirement. As single channel data rate continues to increase and channel spacing continues to shrink for high capacity, high spectral efficiency, the workload on conventional electronic signal processing elements in the router nodes continues to build up. Performing signal processing functions in the optical domain can potentially alleviate the speed bottleneck if the unique optical properties are efficiently leveraged to assist electronic processing methodologies. Ultra-high bandwidth capability along with the promise for multi-channel and format-transparent operation make optical signal processing an attractive technology which is expected to have great impact on future optical networks. For optical signal processing applications in fiber-optic network and systems, a laudable goal would be to explore the unique nonlinear optical processes in novel photonic devices. This dissertation investigates novel optical signal processing techniques through simulations and experimental demonstrations, analyzes limitations of these nonlinear processing elements and proposes techniques to enhance the system performance or designs for functional photonic modules. Two key signal-processing building blocks for future optical networks, namely slow-light-based tunable optical delay lines and SOA-based high-speed wavelength converters, are presented in the first part of the dissertation. Phase preserving and spectrally efficient slow light are experimentally demonstrated using advanced modulation formats. Functional and novel photonic modules, such as multi-channel synchronizer and variable-bit-rate optical time division multiplexer are designed and
Scaling in Non-stationary time series I
Ignaccolo, M; Grigolini, P; Hamilton, P; West, B J
2003-01-01
Most data processing techniques, applied to biomedical and sociological time series, are only valid for random fluctuations that are stationary in time. Unfortunately, these data are often non stationary and the use of techniques of analysis resting on the stationary assumption can produce a wrong information on the scaling, and so on the complexity of the process under study. Herein, we test and compare two techniques for removing the non-stationary influences from computer generated time series, consisting of the superposition of a slow signal and a random fluctuation. The former is based on the method of wavelet decomposition, and the latter is a proposal of this paper, denoted by us as step detrending technique. We focus our attention on two cases, when the slow signal is a periodic function mimicking the influence of seasons, and when it is an aperiodic signal mimicking the influence of a population change (increase or decrease). For the purpose of computational simplicity the random fluctuation is taken...
Blind estimation of statistical properties of non-stationary random variables
Mansour, Ali; Mesleh, Raed; Aggoune, el-Hadi M.
2014-12-01
To identify or equalize wireless transmission channels, or alternatively to evaluate the performance of many wireless communication algorithms, coefficients or statistical properties of the used transmission channels are often assumed to be known or can be estimated at the receiver end. For most of the proposed algorithms, the knowledge of transmission channel statistical properties is essential to detect signals and retrieve data. To the best of our knowledge, most proposed approaches assume that transmission channels are static and can be modeled by stationary random variables (uniform, Gaussian, exponential, Weilbul, Rayleigh, etc.). In the majority of sensor networks or cellular systems applications, transmitters and/or receivers are in motion. Therefore, the validity of static transmission channels and the underlying assumptions may not be valid. In this case, coefficients and statistical properties change and therefore the stationary model falls short of making an accurate representation. In order to estimate the statistical properties (represented by the high-order statistics and probability density function, PDF) of dynamic channels, we firstly assume that the dynamic channels can be modeled by short-term stationary but long-term non-stationary random variable (RV), i.e., the RVs are stationary within unknown successive periods but they may suddenly change their statistical properties between two successive periods. Therefore, this manuscript proposes an algorithm to detect the transition phases of non-stationary random variables and introduces an indicator based on high-order statistics for non-stationary transmission which can be used to alter channel properties and initiate the estimation process. Additionally, PDF estimators based on kernel functions are also developed. The first part of the manuscript provides a brief introduction for unbiased estimators of the second and fourth-order cumulants. Then, the non-stationary indicators are formulated
Directory of Open Access Journals (Sweden)
Li Sun
2016-01-01
Full Text Available It is assumed that the drift parameter is dependent on the acceleration variables and the diffusion coefficient remains the same across the whole accelerated degradation test (ADT in most of the literature based on Wiener process. However, the diffusion coefficient variation would also become obvious in some applications with the stress increasing. Aiming at the phenomenon, the paper concludes that both the drift parameter and the diffusion parameter depend on stress variables based on the invariance principle of failure mechanism and Nelson assumption. Accordingly, constant stress accelerated degradation process (CSADP and step stress accelerated degradation process (SSADP with random effects are modeled. The unknown parameters in the established model are estimated based on the property of degradation and degradation increment, separately for CASDT and SSADT, by the maximum likelihood estimation approach with measurement error. In addition, the simulation steps of accelerated degradation data are provided and simulated step stress accelerated degradation data is designed to validate the proposed model compared to other models. Finally, a case study of CSADT is conducted to demonstrate the benefits of our model in the practical engineering.
Studying the Dynamics of Non-stationary Jet Streams Formation in the Northern Hemisphere Troposphere
Emtsev, Sergey; Krasouski, Aliaksandr; Svetashev, Alexander; Turishev, Leonid; Barodka, Siarhei
2015-04-01
In the present study, we investigate dynamics of non-stationary jets formation in troposphere by means of mesoscale simulations in the Weather Research & Forecasting (WRF) modeling system, analyzing jet streams that affected the territory of Belarus over the time period of 2010-2012. For that purpose, we perform modeling on domains with 5 km, 3 km and 1 km grid steps and 35 vertical coordinate levels with an upper boundary of 10 hPa. We focus our attention to identification of basic regularities in formation, movements and transformations of jet streams, as well as to analysis of their characteristic features, geographical position and underlying atmospheric processes and their classification. On the basis of these regularities, we define basic meteorological parameters that can be used to directly or indirectly (as well as qualitatively and quantitatively) identify the presence of jet streams in the specific region of troposphere, and also to determine their localization, stage of development and other characteristics. Furthermore, we estimate energetic parameters of the identified jet streams and their impact on synoptic situation in the surrounding region. Analyzing meteorological fields obtained from satellite observations, we elaborate a methodology of operational detection and localization of non-stationary jet streams from satellite data. Validation of WRF modeling results with these data proves that mesoscale simulations with WRF are able to provide quite successful forecasts of non-stationary tropospheric jet streams occurrence and also determination of their localization and main characteristics up to 3 days in advance.
Time-varying nonstationary multivariate risk analysis using a dynamic Bayesian copula
Sarhadi, Ali; Burn, Donald H.; Concepción Ausín, María.; Wiper, Michael P.
2016-03-01
A time-varying risk analysis is proposed for an adaptive design framework in nonstationary conditions arising from climate change. A Bayesian, dynamic conditional copula is developed for modeling the time-varying dependence structure between mixed continuous and discrete multiattributes of multidimensional hydrometeorological phenomena. Joint Bayesian inference is carried out to fit the marginals and copula in an illustrative example using an adaptive, Gibbs Markov Chain Monte Carlo (MCMC) sampler. Posterior mean estimates and credible intervals are provided for the model parameters and the Deviance Information Criterion (DIC) is used to select the model that best captures different forms of nonstationarity over time. This study also introduces a fully Bayesian, time-varying joint return period for multivariate time-dependent risk analysis in nonstationary environments. The results demonstrate that the nature and the risk of extreme-climate multidimensional processes are changed over time under the impact of climate change, and accordingly the long-term decision making strategies should be updated based on the anomalies of the nonstationary environment.
Resolution enhancement of non-stationary seismic data using amplitude-frequency partition
Xie, Yujiang; Liu, Gao
2015-02-01
As the Earth's inhomogeneous and viscoelastic properties, seismic signal attenuation we are trying to mitigate is a long-standing problem facing with high-resolution techniques. For addressing such a problem in the fields of time-frequency transform, Gabor transform methods such as atom-window method (AWM) and molecular window method (MWM) have been reported recently. However, we observed that these methods might be much better if we partition the non-stationary seismic data into adaptive stationary segments based on the amplitude and frequency information of the seismic signal. In this study, we present a new method called amplitude-frequency partition (AFP) to implement this process in the time-frequency domain. Cases of a synthetic and field seismic data indicated that the AFP method could partition the non-stationary seismic data into stationary segments approximately, and significantly, a high-resolution result would be achieved by combining the AFP method with conventional spectral-whitening method, which could be considered superior to previous resolution-enhancement methods like time-variant spectral whitening method, the AWM and the MWM as well. This AFP method presented in this study would be an effective resolution-enhancement tool for the non-stationary seismic data in the fields of an adaptive time-frequency transform.
Phonon-assisted nonlinear optical processes in ultrashort-pulse pumped optical parametric amplifiers
Isaienko, Oleksandr; Robel, István
2016-03-01
Optically active phonon modes in ferroelectrics such as potassium titanyl phosphate (KTP) and potassium titanyl arsenate (KTA) in the ~7-20 THz range play an important role in applications of these materials in Raman lasing and terahertz wave generation. Previous studies with picosecond pulse excitation demonstrated that the interaction of pump pulses with phonons can lead to efficient stimulated Raman scattering (SRS) accompanying optical parametric oscillation or amplification processes (OPO/OPA), and to efficient polariton-phonon scattering. In this work, we investigate the behavior of infrared OPAs employing KTP or KTA crystals when pumped with ~800-nm ultrashort pulses of duration comparable to the oscillation period of the optical phonons. We demonstrate that under conditions of coherent impulsive Raman excitation of the phonons, when the effective χ(2) nonlinearity cannot be considered instantaneous, the parametrically amplified waves (most notably, signal) undergo significant spectral modulations leading to an overall redshift of the OPA output. The pump intensity dependence of the redshifted OPA output, the temporal evolution of the parametric gain, as well as the pump spectral modulations suggest the presence of coupling between the nonlinear optical polarizations PNL of the impulsively excited phonons and those of parametrically amplified waves.
Valenza, Gaetano; Citi, Luca; Scilingo, Enzo Pasquale; Barbieri, Riccardo
2014-01-01
Measures of entropy have been proved as powerful quantifiers of complex nonlinear systems, particularly when applied to stochastic series of heartbeat dynamics. Despite the remarkable achievements obtained through standard definitions of approximate and sample entropy, a time-varying definition of entropy characterizing the physiological dynamics at each moment in time is still missing. To this extent, we propose two novel measures of entropy based on the inho-mogeneous point-process theory. The RR interval series is modeled through probability density functions (pdfs) which characterize and predict the time until the next event occurs as a function of the past history. Laguerre expansions of the Wiener-Volterra autoregressive terms account for the long-term nonlinear information. As the proposed measures of entropy are instantaneously defined through such probability functions, the proposed indices are able to provide instantaneous tracking of autonomic nervous system complexity. Of note, the distance between the time-varying phase-space vectors is calculated through the Kolmogorov-Smirnov distance of two pdfs. Experimental results, obtained from the analysis of RR interval series extracted from ten healthy subjects during stand-up tasks, suggest that the proposed entropy indices provide instantaneous tracking of the heartbeat complexity, also allowing for the definition of complexity variability indices.
Energy Technology Data Exchange (ETDEWEB)
Geniet, F; Leon, J [Physique Mathematique et Theorique, CNRS-UMR 5825, 34095 Montpellier (France)
2003-05-07
A nonlinear system possessing a natural forbidden band gap can transmit energy of a signal with a frequency in the gap, as recently shown for a nonlinear chain of coupled pendulums (Geniet and Leon 2002 Phys. Rev. Lett. 89 134102). This process of nonlinear supratransmission, occurring at a threshold that is exactly predictable in many cases, is shown to have a simple experimental realization with a mechanical chain of pendulums coupled by a coil spring. It is then analysed in more detail. First we go to different (nonintegrable) systems which do sustain nonlinear supratransmission. Then a Josephson transmission line (a one-dimensional array of short Josephson junctions coupled through superconducting wires) is shown to also sustain nonlinear supratransmission, though being related to a different class of boundary conditions, and despite the presence of damping, finiteness, and discreteness. Finally, the mechanism at the origin of nonlinear supratransmission is found to be a nonlinear instability, and this is briefly discussed here.
Signal Processing Methods Monitor Cranial Pressure
2010-01-01
Dr. Norden Huang, of Goddard Space Flight Center, invented a set of algorithms (called the Hilbert-Huang Transform, or HHT) for analyzing nonlinear and nonstationary signals that developed into a user-friendly signal processing technology for analyzing time-varying processes. At an auction managed by Ocean Tomo Federal Services LLC, licenses of 10 U.S. patents and 1 domestic patent application related to HHT were sold to DynaDx Corporation, of Mountain View, California. DynaDx is now using the licensed NASA technology for medical diagnosis and prediction of brain blood flow-related problems, such as stroke, dementia, and traumatic brain injury.
Bell, Iris R; Sarter, Barbara; Standish, Leanna J; Banerji, Prasanta; Banerji, Pratip
2015-06-01
The purpose of the present paper is to (a) summarize evidence for the nanoparticle nature and biological effects of traditional homeopathically-prepared medicines at low and ultralow doses; (b) provide details of historically-based homeopathic green manufacturing materials and methods, relating them to top-down mechanical attrition and plant-based biosynthetic processes in modern nanotechnology; (c) outline the potential roles of nonlinear dose-responses and dynamical interactions with complex adaptive systems in generating endogenous amplification processes during low dose treatment. Possible mechanisms of low dose effects, for which there is evidence involving nanoparticles and/or homeopathically-manufactured medicines, include hormesis, time-dependent sensitization, and stochastic resonance. All of the proposed mechanisms depend upon endogenous nonlinear amplification processes in the recipient organism in interaction with the salient, albeit weak signal properties of the medicine. Conventional ligand-receptor mechanisms relevant to higher doses are less likely involved. Effects, especially for homeopathically-prepared nanophytomedicines, include bidirectional host state-dependent changes in function. Homeopathic clinicians report successful treatment of serious infections and cancers. Preclinical biological evidence is consistent with such claims. Controlled biological data on homeopathically-prepared medicines indicate modulation of gene expression and biological signaling pathways regulating cell cycles, immune reactions, and central nervous system function from studies on cells, animals, and human subjects. As a 200-year old system of traditional medicine used by millions of people worldwide, homeopathy offers a pulsed low dose treatment strategy and strong safety record to facilitate progress in translational nanomedicine with plants and other natural products. In turn, modern nanotechnology methods can improve homeopathic manufacturing procedures
Nonlinear modeling of activated sludge process using the Hammerstein-Wiener structure
Directory of Open Access Journals (Sweden)
Frącz Paweł
2016-01-01
Full Text Available The paper regards to physical model of the Activated Sludge Process, which is a part of the wastewater treatment. The aim of the study was to describe nitrogen transformation process and the demand of chemical fractions, involved in the ASP process. Moreover, the non-linear relationship between the flow of wastewater and the consumed electrical energy, used by the blowers, was determined. Such analyses are important from the economical and environmental point of view. Assuming that the total power does not change the blower is charging during a year an energy amount of approx. 613 MW. This illustrates in particular the scale of the demand for energy consumption in the biological aeration unit. The aim is to minimize the energy consumption through first building a model of ASP and then through optimization of the overall process by modifying chosen parameter in numerical simulations. In this paper example measurement and analysis results of nitrite and ammonium nitrogen concentrations in the aeration reactor and the active power consumed by blowers for the aeration process were presented. Further the ASP modeling procedure, which uses the Hammerstein-Wiener structure and example verification results were presented. Based on the achieved results it was stated that the developed set of methodologies may be used to improve and expand the overriding control system for system for wastewater treatment plant.
Non-Stationary Effects and Cross Correlations in Solar Activity
Nefedyev, Yuri; Panischev, Oleg; Demin, Sergey
2016-07-01
In this paper within the framework of the Flicker-Noise Spectroscopy (FNS) we consider the dynamic properties of the solar activity by analyzing the Zurich sunspot numbers. As is well-known astrophysics objects are the non-stationary open systems, whose evolution are the quite individual and have the alternation effects. The main difference of FNS compared to other related methods is the separation of the original signal reflecting the dynamics of solar activity into three frequency bands: system-specific "resonances" and their interferential contributions at lower frequencies, chaotic "random walk" ("irregularity-jump") components at larger frequencies, and chaotic "irregularity-spike" (inertial) components in the highest frequency range. Specific parameters corresponding to each of the bands are introduced and calculated. These irregularities as well as specific resonance frequencies are considered as the information carriers on every hierarchical level of the evolution of a complex natural system with intermittent behavior, consecutive alternation of rapid chaotic changes in the values of dynamic variables on small time intervals with small variations of the values on longer time intervals ("laminar" phases). The jump and spike irregularities are described by power spectra and difference moments (transient structural functions) of the second order. FNS allows revealing the most crucial points of the solar activity dynamics by means of "spikiness" factor. It is shown that this variable behaves as the predictor of crucial changes of the sunspot number dynamics, particularly when the number comes up to maximum value. The change of averaging interval allows revealing the non-stationary effects depending by 11-year cycle and by inside processes in a cycle. To consider the cross correlations between the different variables of solar activity we use the Zurich sunspot numbers and the sequence of corona's radiation energy. The FNS-approach allows extracting the
Indian Academy of Sciences (India)
Long Zhang; Guoliang Xiong; Hesheng Liu; Huijun Zou; Weizhong Guo
2010-04-01
A parametric time-frequency representation is presented based on timevarying autoregressive model (TVAR), followed by applications to non-stationary vibration signal processing. The identiﬁcation of time-varying model coefﬁcients and the determination of model order, are addressed by means of neural networks and genetic algorithms, respectively. Firstly, a simulated signal which mimic the rotor vibration during run-up stages was processed for a comparative study on TVAR and other non-parametric time-frequency representations such as Short Time Fourier Transform, Continuous Wavelet Transform, Empirical Mode Decomposition, Wigner–Ville Distribution and Choi–Williams Distribution, in terms of their resolutions, accuracy, cross term suppression as well as noise resistance. Secondly, TVAR was applied to analyse non-stationary vibration signals collected from a rotor test rig during run-up stages, with an aim to extract fault symptoms under non-stationary operating conditions. Simulation and experimental results demonstrate that TVAR is an effective solution to non-stationary signal analysis and has strong capability in signal time-frequency feature extraction.
Liu, Tao; Yan, Shaoze; Zhang, Wei
2016-06-01
Deployable structures have been widely used in on-orbit servicing spacecrafts, and the vibration properties of such structures have become increasingly important in the aerospace industry. The constant-Q nonstationary Gabor transform (CQ-NSGT) is introduced in this paper to accurately evaluate the variation in the frequency and amplitude of vibration signals along with time. First, an example signal is constructed on the basis of the vibration properties of deployable structures and is processed by the short-time Fourier transform, Wigner-Ville distribution, Hilbert-Huang transform, and CQ-NSGT. Results show that time and frequency resolutions are simultaneously fine only by employing CQ-NSGT. Subsequently, a zero padding operation is conducted to correct the calculation error at the end of the transform results. Finally, a set of experimental devices is constructed. The vibration signal of the experimental mode is processed by CQ-NSGT. On this basis, the experimental signal properties are discussed. This time-frequency method may be useful for formulating the dynamics for complex deployable structures.
DEFF Research Database (Denmark)
Peucheret, Christophe; Da Ros, Francesco; Vukovic, Dragana;
- compatible fabrication process, degrees of freedom in dispersion engineering, and high nonlinear coecient. However, the detrimental eect of free-carrier absorption induced by two-photon absorp- tion has so far prevented them from being used for the demonstration of phase-sensitive processing. Thanks...
McArthur, Duncan; Hourahine, Ben; Papoff, Francesco
2015-11-24
We model a scheme for the coherent control of light waves and currents in metallic nanospheres which applies independently of the nonlinear multiphoton processes at the origin of waves and currents. Using exact mathematical formulae, we calculate numerically with a custom fortran code the effect of an external control field which enable us to change the radiation pattern and suppress radiative losses or to reduce absorption, enabling the particle to behave as a perfect scatterer or as a perfect absorber. Data are provided in tabular, comma delimited value format and illustrate narrow features in the response of the particles that result in high sensitivity to small variations in the local environment, including subwavelength spatial shifts.
Nonlinear Sagnac interferometer based on the four-wave mixing process.
Xin, Jun; Liu, Jinming; Jing, Jietai
2017-01-23
A new nonlinear Sagnac interferometer (NSI) is proposed by replacing the beam-splitter in the traditional Sagnac interferometer (TSI) with a four-wave mixing process. Such a NSI has better angular velocity sensitivity than the one of the TSI. The standard quantum limit can be beaten and the Heisenberg Limit can even be reached for the ideal case by the NSI. We study the effect of the losses on the angular velocity sensitivity of the NSI and find that the optimal angular velocity, where the best angular velocity sensitivity can be obtained, of the NSI may be dependent on the losses inside the interferometer. Such a NSI has its advantages compared with the TSI and may find its potential applications in quantum metrology.
Baranov, Denis G; Milichko, Valentin A; Kudryashov, Sergey I; Krasnok, Alexander E; Belov, Pavel A
2016-01-01
Optically generated electron-hole plasma in high-index dielectric nanostructures was demonstrated as a means of tuning of their optical properties. However, until now an ultrafast operation regime of such plasma driven nanostructures has not been attained. Here, we perform pump-probe experiments with resonant silicon nanoparticles and report on dense optical plasma generation near the magnetic dipole resonance with ultrafast (about 2.5 ps) relaxation rate. Basing on experimental results, we develop an analytical model describing transient response of a nanocrystalline silicon nanoparticle to an intense laser pulse and show theoretically that plasma induced optical nonlinearity leads to ultrafast reconfiguration of the scattering power pattern. We demonstrate 100 fs switching to unidirectional scattering regime upon irradiation of the nanoparticle by an intense femtosecond pulse. Our work lays the foundation for developing ultracompact and ultrafast all-optical signal processing devices.
Nonlinear color-image decomposition for image processing of a digital color camera
Saito, Takahiro; Aizawa, Haruya; Yamada, Daisuke; Komatsu, Takashi
2009-01-01
This paper extends the BV (Bounded Variation) - G and/or the BV-L1 variational nonlinear image-decomposition approaches, which are considered to be useful for image processing of a digital color camera, to genuine color-image decomposition approaches. For utilizing inter-channel color cross-correlations, this paper first introduces TV (Total Variation) norms of color differences and TV norms of color sums into the BV-G and/or BV-L1 energy functionals, and then derives denoising-type decomposition-algorithms with an over-complete wavelet transform, through applying the Besov-norm approximation to the variational problems. Our methods decompose a noisy color image without producing undesirable low-frequency colored artifacts in its separated BV-component, and they achieve desirable high-quality color-image decomposition, which is very robust against colored random noise.
Directory of Open Access Journals (Sweden)
Naveed Ishtiaq Chaudhary
2013-01-01
Full Text Available A novel algorithm is developed based on fractional signal processing approach for parameter estimation of input nonlinear control autoregressive (INCAR models. The design scheme consists of parameterization of INCAR systems to obtain linear-in-parameter models and to use fractional least mean square algorithm (FLMS for adaptation of unknown parameter vectors. The performance analyses of the proposed scheme are carried out with third-order Volterra least mean square (VLMS and kernel least mean square (KLMS algorithms based on convergence to the true values of INCAR systems. It is found that the proposed FLMS algorithm provides most accurate and convergent results than those of VLMS and KLMS under different scenarios and by taking the low-to-high signal-to-noise ratio.
Chaudhary, Naveed Ishtiaq; Raja, Muhammad Asif Zahoor; Khan, Junaid Ali; Aslam, Muhammad Saeed
2013-01-01
A novel algorithm is developed based on fractional signal processing approach for parameter estimation of input nonlinear control autoregressive (INCAR) models. The design scheme consists of parameterization of INCAR systems to obtain linear-in-parameter models and to use fractional least mean square algorithm (FLMS) for adaptation of unknown parameter vectors. The performance analyses of the proposed scheme are carried out with third-order Volterra least mean square (VLMS) and kernel least mean square (KLMS) algorithms based on convergence to the true values of INCAR systems. It is found that the proposed FLMS algorithm provides most accurate and convergent results than those of VLMS and KLMS under different scenarios and by taking the low-to-high signal-to-noise ratio. PMID:23853538
Rodrigo, M A; Seco, A; Ferrer, J; Penya-roja, J M; Valverde, J L
1999-01-01
In this paper, several tuning algorithms, specifically ITAE, IMC and Cohen and Coon, were applied in order to tune an activated sludge aeration PID controller. Performance results of these controllers were compared by simulation with those obtained by using a nonlinear fuzzy PID controller. In order to design this controller, a trial and error procedure was used to determine, as a function of error at current time and at a previous time, sets of parameters (including controller gain, integral time and derivative time) which achieve satisfactory response of a PID controller actuating over the aeration process. Once these sets of data were obtained, neural networks were used to obtain fuzzy membership functions and fuzzy rules of the fuzzy PID controller.
Directory of Open Access Journals (Sweden)
Luiz Augusto da Cruz Meleiro
2005-06-01
Full Text Available In this work a MIMO non-linear predictive controller was developed for an extractive alcoholic fermentation process. The internal model of the controller was represented by two MISO Functional Link Networks (FLNs, identified using simulated data generated from a deterministic mathematical model whose kinetic parameters were determined experimentally. The FLN structure presents as advantages fast training and guaranteed convergence, since the estimation of the weights is a linear optimization problem. Besides, the elimination of non-significant weights generates parsimonious models, which allows for fast execution in an MPC-based algorithm. The proposed algorithm showed good potential in identification and control of non-linear processes.Neste trabalho um controlador preditivo não linear multivariável foi desenvolvido para um processo de fermentação alcoólica extrativa. O modelo interno do controlador foi representado por duas redes do tipo Functional Link (FLN, identificadas usando dados de simulação gerados a partir de um modelo validado experimentalmente. A estrutura FLN apresenta como vantagem o treinamento rápido e convergência garantida, já que a estimação dos seus pesos é um problema de otimização linear. Além disso, a eliminação de pesos não significativos gera modelos parsimoniosos, o que permite a rápida execução em algoritmos de controle preditivo baseado em modelo. Os resultados mostram que o algoritmo proposto tem grande potencial para identificação e controle de processos não lineares.
Non-Stationary Hydrologic Frequency Analysis using B-Splines Quantile Regression
Nasri, B.; St-Hilaire, A.; Bouezmarni, T.; Ouarda, T.
2015-12-01
Hydrologic frequency analysis is commonly used by engineers and hydrologists to provide the basic information on planning, design and management of hydraulic structures and water resources system under the assumption of stationarity. However, with increasing evidence of changing climate, it is possible that the assumption of stationarity would no longer be valid and the results of conventional analysis would become questionable. In this study, we consider a framework for frequency analysis of extreme flows based on B-Splines quantile regression, which allows to model non-stationary data that have a dependence on covariates. Such covariates may have linear or nonlinear dependence. A Markov Chain Monte Carlo (MCMC) algorithm is used to estimate quantiles and their posterior distributions. A coefficient of determination for quantiles regression is proposed to evaluate the estimation of the proposed model for each quantile level. The method is applied on annual maximum and minimum streamflow records in Ontario, Canada. Climate indices are considered to describe the non-stationarity in these variables and to estimate the quantiles in this case. The results show large differences between the non-stationary quantiles and their stationary equivalents for annual maximum and minimum discharge with high annual non-exceedance probabilities. Keywords: Quantile regression, B-Splines functions, MCMC, Streamflow, Climate indices, non-stationarity.
In-TFT-Array-Process Micro Defect Inspection Using Nonlinear Principal Component Analysis
Directory of Open Access Journals (Sweden)
Zhi-Hao Kang
2009-10-01
Full Text Available Defect inspection plays a critical role in thin film transistor liquid crystal display (TFT-LCD manufacture, and has received much attention in the field of automatic optical inspection (AOI. Previously, most focus was put on the problems of macro-scale Mura-defect detection in cell process, but it has recently been found that the defects which substantially influence the yield rate of LCD panels are actually those in the TFT array process, which is the first process in TFT-LCD manufacturing. Defect inspection in TFT array process is therefore considered a difficult task. This paper presents a novel inspection scheme based on kernel principal component analysis (KPCA algorithm, which is a nonlinear version of the well-known PCA algorithm. The inspection scheme can not only detect the defects from the images captured from the surface of LCD panels, but also recognize the types of the detected defects automatically. Results, based on real images provided by a LCD manufacturer in Taiwan, indicate that the KPCA-based defect inspection scheme is able to achieve a defect detection rate of over 99% and a high defect classification rate of over 96% when the imbalanced support vector machine (ISVM with 2-norm soft margin is employed as the classifier. More importantly, the inspection time is less than 1 s per input image.
Institute of Scientific and Technical Information of China (English)
Hasan ABBASI NOZARI; Hamed DEHGHAN BANADAKI; Mohammad MOKHTARE; Somaveh HEKMATI VAHED
2012-01-01
This study deals with the neuro-fuzzy (NF) modelling of a real industrial winding process in which the acquired NF model can be exploited to improve control performance and achieve a robust fault-tolerant system.A new simulator model is proposed for a winding process using non-linear identification based on a recurrent local linear neuro-fuzzy (RLLNF) network trained by local linear model tree (LOLIMOT),which is an incremental tree-based learning algorithm.The proposed NF models are compared with other known intelligent identifiers,namely multilayer perceptron (MLP) and radial basis function (RBF).Comparison of our proposed non-linear models and associated models obtained through the least square error (LSE) technique (the optimal modelling method for linear systems) confirms that the winding process is a non-linear system.Experimental results show the effectiveness of our proposed NF modelling approach.
Chen, Xiaowang; Feng, Zhipeng
2016-12-01
Planetary gearboxes are widely used in many sorts of machinery, for its large transmission ratio and high load bearing capacity in a compact structure. Their fault diagnosis relies on effective identification of fault characteristic frequencies. However, in addition to the vibration complexity caused by intricate mechanical kinematics, volatile external conditions result in time-varying running speed and/or load, and therefore nonstationary vibration signals. This usually leads to time-varying complex fault characteristics, and adds difficulty to planetary gearbox fault diagnosis. Time-frequency analysis is an effective approach to extracting the frequency components and their time variation of nonstationary signals. Nevertheless, the commonly used time-frequency analysis methods suffer from poor time-frequency resolution as well as outer and inner interferences, which hinder accurate identification of time-varying fault characteristic frequencies. Although time-frequency reassignment improves the time-frequency readability, it is essentially subject to the constraints of mono-component and symmetric time-frequency distribution about true instantaneous frequency. Hence, it is still susceptible to erroneous energy reallocation or even generates pseudo interferences, particularly for multi-component signals of highly nonlinear instantaneous frequency. In this paper, to overcome the limitations of time-frequency reassignment, we propose an improvement with fine time-frequency resolution and free from interferences for highly nonstationary multi-component signals, by exploiting the merits of iterative generalized demodulation. The signal is firstly decomposed into mono-components of constant frequency by iterative generalized demodulation. Time-frequency reassignment is then applied to each generalized demodulated mono-component, obtaining a fine time-frequency distribution. Finally, the time-frequency distribution of each signal component is restored and superposed to
A Model Predictive Algorithm for Active Control of Nonlinear Noise Processes
Directory of Open Access Journals (Sweden)
Qi-Zhi Zhang
2005-01-01
Full Text Available In this paper, an improved nonlinear Active Noise Control (ANC system is achieved by introducing an appropriate secondary source. For ANC system to be successfully implemented, the nonlinearity of the primary path and time delay of the secondary path must be overcome. A nonlinear Model Predictive Control (MPC strategy is introduced to deal with the time delay in the secondary path and the nonlinearity in the primary path of the ANC system. An overall online modeling technique is utilized for online secondary path and primary path estimation. The secondary path is estimated using an adaptive FIR filter, and the primary path is estimated using a Neural Network (NN. The two models are connected in parallel with the two paths. In this system, the mutual disturbances between the operation of the nonlinear ANC controller and modeling of the secondary can be greatly reduced. The coefficients of the adaptive FIR filter and weight vector of NN are adjusted online. Computer simulations are carried out to compare the proposed nonlinear MPC method with the nonlinear Filter-x Least Mean Square (FXLMS algorithm. The results showed that the convergence speed of the proposed nonlinear MPC algorithm is faster than that of nonlinear FXLMS algorithm. For testing the robust performance of the proposed nonlinear ANC system, the sudden changes in the secondary path and primary path of the ANC system are considered. Results indicated that the proposed nonlinear ANC system can rapidly track the sudden changes in the acoustic paths of the nonlinear ANC system, and ensure the adaptive algorithm stable when the nonlinear ANC system is time variable.
Aires, Filipe; Rossow, William B.; Hansen, James E. (Technical Monitor)
2001-01-01
A new approach is presented for the analysis of feedback processes in a nonlinear dynamical system by observing its variations. The new methodology consists of statistical estimates of the sensitivities between all pairs of variables in the system based on a neural network modeling of the dynamical system. The model can then be used to estimate the instantaneous, multivariate and nonlinear sensitivities, which are shown to be essential for the analysis of the feedbacks processes involved in the dynamical system. The method is described and tested on synthetic data from the low-order Lorenz circulation model where the correct sensitivities can be evaluated analytically.
Schwinger-Dyson equations in large-N quantum field theories and nonlinear random processes
Buividovich, P V
2010-01-01
We study stochastic methods for solving Schwinger-Dyson equations in large-N quantum field theories. Expectation values of single-trace operators are sampled by stationary probability distributions of so-called nonlinear random processes. The set of all histories of such processes corresponds to the set of all planar diagrams in the perturbative expansion of the theory. We describe stochastic algorithms for summation of planar diagrams in matrix-valued scalar field theory and in the Weingarten model of random planar surfaces on the lattice. For compact field variables, the method does not converge in the physically most interesting weak-coupling limit. In this case one can absorb the divergences into the self-consistent redefinition of expansion parameters. Stochastic solution of the self-consistency conditions can be implemented as a random process with memory. We illustrate this idea on the example of two-dimensional O(N) sigma-model. Extension to non-Abelian lattice gauge theories is discussed.
Institute of Scientific and Technical Information of China (English)
Yin-nianHe
2004-01-01
In this article we consider a two-level finite element Galerkin method using mixed finite elements for the two-dimensional nonstationary incompressible Navier-Stokes equations. The method yields a H1-optimal velocity approximation and a L2-optimal pressure approximation. The two-level finite element Galerkin method involves solving one small,nonlinear Navier-Stokes problem on the coarse mesh with mesh size H, one linear Stokes problem on the fine mesh with mesh size h <
Fluctuation-dissipation relation in a spin glass in the non-stationary regime
Energy Technology Data Exchange (ETDEWEB)
Herisson, D.; Ocio, M
2003-05-01
We present the first experimental determination of the time autocorrelation C(t',t) of magnetization in the non-stationary regime of a spin glass. Quantitative comparison with the corresponding response, the magnetic susceptibility {chi}(t',t), is made possible by the use of a new experimental setup allowing both measurements in the same conditions. Clearly, we observe a non-linear fluctuation-dissipation relation between C and {chi}, depending weakly on the waiting time t'. Following theoretical developments on mean-field models, and lately on short range ones, it is predicted that in the limit of long times, the {chi}(C) relationship should become independent on t'. A scaling procedure allows us to extrapolate to the limit of long waiting times.
Non-stationary flow of hydraulic oil in long pipe
Directory of Open Access Journals (Sweden)
Hružík Lumír
2014-03-01
Full Text Available The paper deals with experimental evaluation and numerical simulation of non-stationary flow of hydraulic oil in a long hydraulic line. Non-stationary flow is caused by a quick closing of valves at the beginning and the end of the pipe. Time dependence of pressure is measured by means of pressure sensors at the beginning and the end of the pipe. A mathematical model of a given circuit is created using Matlab SimHydraulics software. The long line is simulated by means of segmented pipe. The simulation is verified by experiment.
THE WAVELET TRANSFORM OF PERIODIC FUNCTION AND NONSTATIONARY PERIODIC FUNCTION
Institute of Scientific and Technical Information of China (English)
刘海峰; 周炜星; 王辅臣; 龚欣; 于遵宏
2002-01-01
Some properties of the wavelet transform of trigonometric function, periodic function and nonstationary periodic function have been investigated. The results show that the peak height and width in wavelet energy spectrum of a periodic function are in proportion to its period. At the same time, a new equation, which can truly reconstruct a trigonometric function with only one scale wavelet coefficient, is presented. The reconstructed wave shape of a periodic function with the equation is better than any term of its Fourier series. And the reconstructed wave shape of a class of nonstationary periodic function with this equation agrees well with the function.
Correlation, Regression, and Cointegration of Nonstationary Economic Time Series
DEFF Research Database (Denmark)
Johansen, Søren
), and Phillips (1986) found the limit distributions. We propose to distinguish between empirical and population correlation coefficients and show in a bivariate autoregressive model for nonstationary variables that the empirical correlation and regression coefficients do not converge to the relevant population...... values, due to the trending nature of the data. We conclude by giving a simple cointegration analysis of two interests. The analysis illustrates that much more insight can be gained about the dynamic behavior of the nonstationary variables then simply by calculating a correlation coefficient...
Fundamental nonlinearities of the reactor-settler interaction in the activated sludge process.
Diehl, Stefan; Farås, Sebastian
2012-01-01
The activated sludge process can be modelled by ordinary and partial differential equations for the biological reactors and secondary settlers, respectively. Because of the complexity of such a system, simulation models are most often used to investigate them. However, simulation models cannot give general rules on how to control a complex nonlinear process. For a reduced-order model with only two components, soluble substrate and particulate biomass, general results on steady-state solutions have recently been obtained, such as existence, uniqueness and stability of solutions. The aim of the present paper is to utilize those results to formulate some implications of practical importance. In particular, strategies are described for the manual control of the effluent substrate concentration subject to the constraint that the settler is maintained in normal operation (with a sludge blanket in the thickening zone) in steady state. Such strategies contain how the two control parameters, the recycle and waste volumetric flow ratios, should be chosen for any (steady-state) values of the input variables.
Sadeghi, Saman; Thompson, Michael
2010-01-01
It is evident that complex animate materials, which operate far from equilibrium, exhibit sensory responses to the environment through emergent patterns. Formation of such patterns is often the underlying mechanism of an active response to environmental changes and can be interpreted as a result of the distributed parallel information processing taking place within the material. Such emergent patterns are not limited to biological entities; indeed there is a wide range of complex nonlinear dissipative systems which exhibit interesting emergent patterns within a range of parameters. As one example, the present paper describes the detection of emergent phenomena associated with surface electrochemical processes that allow the system to respond to input information through evolving patterns in space and time. Associative mapping of this sort offers the opportunity to devise an electrochemical cognitive system (ECS), where pattern formation can be looked at as a macroscopic phenomenon resulting from the extensive distributive computing that occurs at the microscopic level. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.
The dynamics of nonstationary solutions in one-dimensional two-component Bose-Einstein condensates
Institute of Scientific and Technical Information of China (English)
Lü Bin-Bin; Hao Xue; Tian Qiang
2011-01-01
This paper investigates the dynamical properties of nonstationary solutions in one-dimensional two-component Bose-Einstein condensates. It gives three kinds of stationary solutions to this model and develops a general method of constructing nonstationary solutions. It obtains the unique features about general evolution and soliton evolution of nonstationary solutions in this model.
The cost of using stationary inventory policies when demand is non-stationary
Tunc, Huseyin; Kilic, Onur A.; Tarim, S. Armagan; Eksioglu, Burak
Non-stationary stochastic demands are very common in industrial settings with seasonal patterns, trends, business cycles, and limited-life items. In such cases, the optimal inventory control policies are also non-stationary. However, due to high computational complexity, non-stationary inventory
Directory of Open Access Journals (Sweden)
S. I. Samsudin
2014-01-01
Full Text Available The wastewater treatment plant (WWTP is highly known with the nonlinearity of the control parameters, thus it is difficult to be controlled. In this paper, the enhancement of nonlinear PI controller (ENon-PI to compensate the nonlinearity of the activated sludge WWTP is proposed. The ENon-PI controller is designed by cascading a sector-bounded nonlinear gain to linear PI controller. The rate variation of the nonlinear gain kn is automatically updated based on adaptive interaction algorithm. Initiative to simplify the ENon-PI control structure by adapting kn has been proved by significant improvement under various dynamic influents. More than 30% of integral square error and 14% of integral absolute error are reduced compared to benchmark PI for DO control and nitrate in nitrogen removal control. Better average effluent qualities, less number of effluent violations, and lower aeration energy consumption resulted.
1976-10-29
clipping level. The nonlinear processing method described in this report provides at least 10 dB of S/N improvement over the performance obtained without...0001s Ii 0110 151 to-, ,n o 151. 1 iK) Il O( M I ( lf clipper performance was also eviden -t in the January 1974 data. Table 7 contains statisti- cal
Non-stationary background intensity and Caribbean seismic events
Valmy, Larissa; Vaillant, Jean
2014-05-01
We consider seismic risk calculation based on models with non-stationary background intensity. The aim is to improve predictive strategies in the framework of seismic risk assessment from models describing at best the seismic activity in the Caribbean arc. Appropriate statistical methods are required for analyzing the volumes of data collected. The focus is on calculating earthquakes occurrences probability and analyzing spatiotemporal evolution of these probabilities. The main modeling tool is the point process theory in order to take into account past history prior to a given date. Thus, the seismic event conditional intensity is expressed by means of the background intensity and the self exciting component. This intensity can be interpreted as the expected event rate per time and / or surface unit. The most popular intensity model in seismology is the ETAS (Epidemic Type Aftershock Sequence) model introduced and then generalized by Ogata [2, 3]. We extended this model and performed a comparison of different probability density functions for the triggered event times [4]. We illustrate our model by considering the CDSA (Centre de Données Sismiques des Antilles) catalog [1] which contains more than 7000 seismic events occurred in the Lesser Antilles arc. Statistical tools for testing the background intensity stationarity and for dynamical segmentation are presented. [1] Bengoubou-Valérius M., Bazin S., Bertil D., Beauducel F. and Bosson A. (2008). CDSA: a new seismological data center for the French Lesser Antilles, Seismol. Res. Lett., 79 (1), 90-102. [2] Ogata Y. (1998). Space-time point-process models for earthquake occurrences, Annals of the Institute of Statistical Mathematics, 50 (2), 379-402. [3] Ogata, Y. (2011). Significant improvements of the space-time ETAS model for forecasting of accurate baseline seismicity, Earth, Planets and Space, 63 (3), 217-229. [4] Valmy L. and Vaillant J. (2013). Statistical models in seismology: Lesser Antilles arc case
Energy Technology Data Exchange (ETDEWEB)
Picozzi, A., E-mail: Antonio.Picozzi@u-bourgogne.fr [Laboratoire Interdisciplinaire Carnot de Bourgogne, Université de Bourgogne, CNRS-UMR 5027, Dijon (France); Garnier, J. [Laboratoire de Probabilités et Modèles Aléatoires and Laboratoire Jacques-Louis Lions, Université Paris VII, 75205 Paris Cedex 13 (France); Hansson, T. [Department of Information Engineering, Università di Brescia, Brescia 25123 (Italy); Suret, P.; Randoux, S. [Laboratoire de Physique des Lasers, Atomes et Molécules, CNRS, Université de Lille (France); Millot, G. [Laboratoire Interdisciplinaire Carnot de Bourgogne, Université de Bourgogne, CNRS-UMR 5027, Dijon (France); Christodoulides, D.N. [College of Optics/CREOL, University of Central Florida, Orlando, FL 32816 (United States)
2014-09-01
The nonlinear propagation of coherent optical fields has been extensively explored in the framework of nonlinear optics, while the linear propagation of incoherent fields has been widely studied in the framework of statistical optics. However, these two fundamental fields of optics have been mostly developed independently of each other, so that a satisfactory understanding of statistical nonlinear optics is still lacking. This article is aimed at reviewing a unified theoretical formulation of statistical nonlinear optics on the basis of the wave turbulence theory, which provides a nonequilibrium thermodynamic description of the system of incoherent nonlinear waves. We consider the nonlinear Schrödinger equation as a representative model accounting either for a nonlocal or a noninstantaneous nonlinearity, as well as higher-order dispersion effects. Depending on the amount of nonlocal (noninstantaneous) nonlinear interaction and the amount of inhomogeneous (nonstationary) statistics of the incoherent wave, different types of kinetic equations are derived and discussed. In the spatial domain, when the incoherent wave exhibits inhomogeneous statistical fluctuations, different forms of the (Hamiltonian) Vlasov equation are obtained depending on the amount of nonlocality. This Vlasov approach describes the processes of incoherent modulational instability and localized incoherent soliton structures. In the temporal domain, the causality property inherent to the response function leads to a kinetic formulation analogous to the weak Langmuir turbulence equation, which describes nonlocalized spectral incoherent solitons. In the presence of a highly noninstantaneous response, this formulation reduces to a family of singular integro-differential kinetic equations (e.g., Benjamin–Ono equation), which describe incoherent dispersive shock waves. Conversely, a non-stationary statistics leads to a (non-Hamiltonian) long-range Vlasov formulation, whose self-consistent potential
Nonstationary Heat Conduction in Atomic Systems
Singh, Amit K.
Understanding heat at the atomistic level is an interesting exercises. It is fascinating to note how the vibration of atoms result into thermodynamic concept of heat. This thesis aims to bring insights into different constitutive laws of heat conduction. We also develop a framework in which the interaction of thermostats to the system can be studied and a well known Kapitza effect can be reduced. The thesis also explores stochastic and continuum methods to model the latent heat release in the first order transition of ideal silicon surfaces into dimers. We divide the thesis into three works which are connected to each other: 1. Fourier's law leads to a diffusive model of heat transfer in which a thermal signal propagates infinitely fast and the only material parameter is the thermal conductivity. In micro- and nano-scale systems, non-Fourier effects involving coupled diffusion and wavelike propagation of heat can become important. An extension of Fourier's law to account for such effects leads to a Jeffreys-type model for heat transfer with two relaxation times. In this thesis, we first propose a new Thermal Parameter Identification (TPI) method for obtaining the Jeffreys-type thermal parameters from molecular dynamics simulations. The TPI method makes use of a nonlinear regression-based approach for obtaining the coefficients in analytical expressions for cosine and sine-weighted averages of temperature and heat flux over the length of the system. The method is applied to argon nanobeams over a range of temperature and system sizes. The results for thermal conductivity are found to be in good agreement with standard Green-Kubo and direct method calculations. The TPI method is more efficient for systems with high diffusivity and has the advantage, that unlike the direct method, it is free from the influence of thermostats. In addition, the method provides the thermal relaxation times for argon. Using the determined parameters, the Jeffreys-type model is able to
Frazier, D. O.; Penn, B. G.; Witherow, W. K.; Paley, M. S.
1991-01-01
Research on the growth of second- and third-order nonlinear optical (NLO) organic thin film by vapor deposition is reviewed. Particular attention is given to the experimental methods for growing thin films of p-chlorophenylurea, diacetylenes, and phthalocyanines; characteristics of the resulting films; and approaches for advancing thin film technology. It is concluded that the growth of NLO thin films by vapor processes is a promising method for the fabrication of planar waveguides for nonlinear optical devices. Two innovative approaches are proposed including a method of controlling the input beam frequency to maximize nonlinear effects in thin films and single crystals, and the alternate approach to the molecular design of organic NLO materials by increasing the transition dipole moment between ground and excited states of the molecule.
Directory of Open Access Journals (Sweden)
Zhen Chen
2016-01-01
Full Text Available Accelerated degradation test (ADT has been widely used to assess highly reliable products’ lifetime. To conduct an ADT, an appropriate degradation model and test plan should be determined in advance. Although many historical studies have proposed quite a few models, there is still room for improvement. Hence we propose a Nonlinear Generalized Wiener Process (NGWP model with consideration of the effects of stress level, product-to-product variability, and measurement errors for a higher estimation accuracy and a wider range of use. Then under the constraints of sample size, test duration, and test cost, the plans of constant-stress ADT (CSADT with multiple stress levels based on the NGWP are designed by minimizing the asymptotic variance of the reliability estimation of the products under normal operation conditions. An optimization algorithm is developed to determine the optimal stress levels, the number of units allocated to each level, inspection frequency, and measurement times simultaneously. In addition, a comparison based on degradation data of LEDs is made to show better goodness-of-fit of the NGWP than that of other models. Finally, optimal two-level and three-level CSADT plans under various constraints and a detailed sensitivity analysis are demonstrated through examples in this paper.
New Space Weather and Nonlinear Waves and Processes Prize announced for 2013
Thompson, Victoria
2012-01-01
At the 2011 Fall Meeting in San Francisco, Calif., AGU announced the creation of a new award: the Space Weather and Nonlinear Waves and Processes Prize. The prize, which is being made possible by a generous contribution from longtime AGU members and NASA Jet Propulsion Laboratory (JPL), California Institute of Technology, scientists Bruce Tsurutani and Olga Verkhoglyadova, will recognize an AGU member scientist and will come with a $10,000 award. Tsurutani has served as a researcher with JPL since 1972 and is currently a senior research scientist. He was also the president of AGU's Space Physics and Aeronomy section from 1990 to 1992 and is a recipient of AGU's John Adam Fleming Medal, given “for original research and technical leadership in geomagnetism, atmospheric electricity, aeronomy, space physics, and related sciences.” Verkhoglyadova served as a professor of space physics in the Department of Astrophysics and Space Physics at Taras Shevchenko National University of Kyiv, in the Ukraine, prior to coming to the United States. Their leadership and dedication to AGU and to their field are apparent in their passion for this prize.
Three novel high-resolution nonlinear methods for fast signal processing
Belkić, Dž.; Dando, P. A.; Main, J.; Taylor, H. S.
2000-10-01
Three novel nonlinear parameter estimators are devised and implemented for accurate and fast processing of experimentally measured or theoretically generated time signals of arbitrary length. The new techniques can also be used as powerful tools for diagonalization of large matrices that are customarily encountered in quantum chemistry and elsewhere. The key to the success and the common denominator of the proposed methods is a considerably reduced dimensionality of the original data matrix. This is achieved in a preprocessing stage called beamspace windowing or band-limited decimation. The methods are decimated signal diagonalization (DSD), decimated linear predictor (DLP), and decimated Padé approximant (DPA). Their mutual equivalence is shown for the signals that are modeled by a linear combination of time-dependent damped exponentials with stationary amplitudes. The ability to obtain all the peak parameters first and construct the required spectra afterwards enables the present methods to phase correct the absorption mode. Additionally, a new noise reduction technique, based upon the stabilization method from resonance scattering theory, is proposed. The results obtained using both synthesized and experimental time signals show that DSD/DLP/DPA exhibit an enhanced resolution power relative to the standard fast Fourier transform. Of the three methods, DPA is found to be the most efficient computationally.
Energy conversion in isothermal nonlinear irreversible processes - struggling for higher efficiency
Ebeling, W.; Feistel, R.
2017-06-01
First we discuss some early work of Ulrike Feudel on structure formation in nonlinear reactions including ions and the efficiency of the conversion of chemical into electrical energy. Then we give some survey about isothermal energy conversion from chemical to higher forms of energy like mechanical, electrical and ecological energy. Isothermal means here that there are no temperature gradients within the model systems. We consider examples of energy conversion in several natural processes and in some devices like fuel cells. Further, as an example, we study analytically the dynamics and efficiency of a simple "active circuit" converting chemical into electrical energy and driving currents which is roughly modeling fuel cells. Finally we investigate an analogous ecological system of Lotka-Volterra type consisting of an "active species" consuming some passive "chemical food". We show analytically for both these models that the efficiency increases with the load, reaches values higher then 50 percent in a narrow regime of optimal load and goes beyond some maximal load abruptly to zero.
Dirac spinor in a nonstationary Godel-type cosmological Universe
Villalba, Victor M
2015-01-01
In the present article we solve, via separation of variables, the massless Dirac equation in a nonstationary rotating, causal G\\"odel-type cosmological universe, having a constant rotational speed in all the points of the space. We compute the frequency spectrum. We show that the spectrum of massless Dirac particles is discrete and unbounded.
Dynamic Memory Model for Non-Stationary Optimization
DEFF Research Database (Denmark)
Bendtsen, Claus Nørgaard; Krink, Thiemo
2002-01-01
Real-world problems are often nonstationary and can cause cyclic, repetitive patterns in the search landscape. For this class of problems, we introduce a new GA with dynamic explicit memory, which showed superior performance compared to a classic GA and a previously introduced memory-based GA...
Fusing Heterogeneous Data for Detection Under Non-stationary Dependence
2012-07-01
In this paper, we consider the problem of detection for dependent, non-stationary signals where the non-stationarity is encoded in the dependence ...allows for a more general description of inter-sensor dependence . We design a copula-based detector using the Neyman-Pearson framework. Our approach
Redefine Water Infrastructure Adaptation to a Nonstationary Climate (Editorial)
The statement “Climate Stationarity is Dead” by Milly et al. (2008) stresses the need to evaluate and when necessary, incorporate non-stationary hydroclimatic changes into water resources and infrastructure planning and engineering. Variations of this theme echo in several other ...
Slow Sphering to Suppress Non-Stationaries in the EEG
Reuderink, Boris; Farquhar, Jason; Poel, Mannes
2011-01-01
Non-stationary signals are ubiquitous in electroencephalogram (EEG) signals and pose a problem for robust application of brain-computer interfaces (BCIs). These non-stationarities can be caused by changes in neural background activity. We present a dynamic spatial filter based on time local whitenin
Robust Forecasting of Non-Stationary Time Series
Croux, C.; Fried, R.; Gijbels, I.; Mahieu, K.
2010-01-01
This paper proposes a robust forecasting method for non-stationary time series. The time series is modelled using non-parametric heteroscedastic regression, and fitted by a localized MM-estimator, combining high robustness and large efficiency. The proposed method is shown to produce reliable foreca
Non-stationary condition monitoring through event alignment
DEFF Research Database (Denmark)
Pontoppidan, Niels Henrik; Larsen, Jan
2004-01-01
. In this paper we apply the technique for non-stationary condition monitoring of large diesel engines based on acoustical emission sensor signals. The performance of the event alignment is analyzed in an unsupervised probabilistic detection framework based on outlier detection with either Principal Component...
Derivation of the generalized Langevin equation in nonstationary environments.
Kawai, Shinnosuke; Komatsuzaki, Tamiki
2011-03-21
The generalized Langevin equation (GLE) is extended to the case of nonstationary bath. The derivation starts with the Hamiltonian equation of motion of the total system including the bath, without any assumption on the form of Hamiltonian or the distribution of the initial condition. Then the projection operator formulation is utilized to obtain a low-dimensional description of the system dynamics surrounded by the nonstationary bath modes. In contrast to the ordinary GLE, the mean force becomes a time-dependent function of the position and the velocity of the system. The friction kernel is found to depend on both the past and the current times, in contrast to the stationary case where it only depends on their difference. The fluctuation-dissipation theorem, which relates the statistical property of the random force to the friction kernel, is also derived for general nonstationary cases. The resulting equation of motion is as simple as the ordinary GLE, and is expected to give a powerful framework to analyze the dynamics of the system surrounded by a nonstationary bath.
Dynamic Memory Model for Non-Stationary Optimization
DEFF Research Database (Denmark)
Bendtsen, Claus Nørgaard; Krink, Thiemo
2002-01-01
Real-world problems are often nonstationary and can cause cyclic, repetitive patterns in the search landscape. For this class of problems, we introduce a new GA with dynamic explicit memory, which showed superior performance compared to a classic GA and a previously introduced memory-based GA for...
Convective boundary layers driven by nonstationary surface heat fluxes
Van Driel, R.; Jonker, H.J.J.
2011-01-01
In this study the response of dry convective boundary layers to nonstationary surface heat fluxes is systematically investigated. This is relevant not only during sunset and sunrise but also, for example, when clouds modulate incoming solar radiation. Because the time scale of the associated change
On complete moment convergence for nonstationary negatively associated random variables
Directory of Open Access Journals (Sweden)
Mi-Hwa Ko
2016-05-01
Full Text Available Abstract The purpose of this paper is to establish the complete moment convergence for nonstationary negatively associated random variables satisfying the weak mean domination condition. The result is an improvement of complete convergence in Marcinkiewicz-Zygmund-type SLLN for negatively associated random variables in Kuczmaszewska (Acta Math. Hung. 128:116-130, 2010.
Algorithms for Solving Non-Stationary Heat Conduction Problem for Design of a Technical Device
Ayriyan, Alexander; Donets, Eugeny E; Grigorian, Hovik; Pribis, Jan
2016-01-01
A model of a multilayer device with non-trivial geometrical and material structure and its working process is suggested. The thermal behavior of the device as one principle characteristic is simulated. The algorithm for solving the non-stationary heat conduction problem with a time-dependent periodical heating source is suggested. The algorithm is based on finite difference explicit--implicit method. The OpenCL realization of the algorithm is discussed. The results show that the chosen characteristics of the device configuration are suitable for the working requirements for application.
Mathematical modeling of non-stationary heat and mass transfer in disperse systems
Ermakova, L. A.; Krasnoperov, S. Y.; Kalashnikov, S. N.
2016-09-01
The work describes mathematical model of non-stationary heat and mass transfer processes in dispersed environment, taking into account the phase transition; presents the results of numeric modelling for conditions of direct reduction in high-temperature reducing atmosphere, corresponding to the direct reduction in the jet-emulsion unit according to the principles of self-organization. The method was developed for calculation of heat and mass transfer of the aggregate of iron material particles in accordance with the given distribution law.
Identification of the structure parameters using short-time non-stationary stochastic excitation
Jarczewska, Kamila; Koszela, Piotr; Śniady, PaweŁ; Korzec, Aleksandra
2011-07-01
In this paper, we propose an approach to the flexural stiffness or eigenvalue frequency identification of a linear structure using a non-stationary stochastic excitation process. The idea of the proposed approach lies within time domain input-output methods. The proposed method is based on transforming the dynamical problem into a static one by integrating the input and the output signals. The output signal is the structure reaction, i.e. structure displacements due to the short-time, irregular load of random type. The systems with single and multiple degrees of freedom, as well as continuous systems are considered.
Continuous wavelet transform for non-stationary vibration detection with phase-OTDR.
Qin, Zengguang; Chen, Liang; Bao, Xiaoyi
2012-08-27
We propose the continuous wavelet transform for non-stationary vibration measurement by distributed vibration sensor based on phase optical time-domain reflectometry (OTDR). The continuous wavelet transform approach can give simultaneously the frequency and time information of the vibration event. Frequency evolution is obtained by the wavelet ridge detection method from the scalogram of the continuous wavelet transform. In addition, a novel signal processing algorithm based on the global wavelet spectrum is used to determine the location of vibration. Distributed vibration measurements of 500 Hz and 500 Hz to 1 kHz sweep events over 20 cm fiber length are demonstrated using a single mode fiber.
2015-09-17
processing - optical frequency conversion and optical DSB -to-SSB conversion 5a. CONTRACT NUMBER FA2386-14-1-0006 5b. GRANT NUMBER Grant 134113...nonlinear dynamics of semiconductor lasers for certain optical signal processing functionalities, including optical DSB -to-SSB conversion, photonic...conversion and optical DSB -to-SSB conversion Performance Period May 30, 2014 ~ May 29, 2015 Principal Investigator Name: Sheng-Kwang Hwang Position
Liang, Heng; Jia, Zhenbin
2007-11-01
In the optimal design and control of preparative chromatographic processes, the obstacles appear when one tries to link the Wilson' s framework of chromatographic theories based on partial differential equations (PDEs) with the Eulerian presentation to optimal control approaches based on discrete time states, such as Markov decision processes (MDP) or Model predictive control (MPC). In this paper, the 0-1 model is presented to overcome the obstacles for nonlinear transport chromatography (NTC). With the Lagrangian-Eulerian description (L-ED), one solute cell unit is split into two solute cells, one (SCm) in the mobile phase with the linear velocity of the mobile phase, and the other (SCs) in the stationary phase with zero-velocity. The thermodynamic state vector, S(k), which comprises four vector components, i.e., the sequence number, the position and the local solute concentrations in both SCms and SCses, is introduced to describe the local thermodynamic path (LTP) and the macroscopical thermodynamic path (MTP). For the NTC, the LTP is designed for a solute zone to evolve from the state, S(k), to the virtual migration state, S(M), undergoing the virtual net migration sub-process, and then to the state, S(k+1), undergoing the virtual net inter phase mass transfer sub-process in a short time interval. Complete thermodynamic state iterations with the Markov characteristics are derived by using the local equilibrium isotherm and the local lumped mass transfer coefficient. When the local thermodynamic equilibrium is retained, excellent properties, such as consistency, stability, conservation, accuracy, etc., of the numerical solution of the 0-1 model are observed in the theoretical analysis and in the numerical experiments of the nonlinear ideal chromatography. It is found that the 0-1 model could properly link up with the MDP or optimal control approaches based on discrete time states.
Institute of Scientific and Technical Information of China (English)
V F Kravchenko; V I Lutsenko; I V Lutsenko; D O Popov
2014-01-01
The possibility of describing the time-dependent processes of scattering by underlying surfaces and the clear sky ,as well as the seasonal behaviour of the refractive index of troposphere by using nested semi-Markov processes has been consid-ered .Local Gaussian models can be used to describe the process inside each phase state .The possibility of describing the sta-tistics of reflections from the sea and the refractive index by using Kravchenko finite functions has been shown for the first time .%本文探讨由下垫面和晴朗天空散射引起的以时间为标示过程的可能性，以及对流层的巢式半马尔可夫过程折射率的季节性变化。各阶段状态中的过程都可以用局部高斯模型描述。本文提出了描述海面反射统计数据的可能性，并且首次用克拉夫钦科有限函数给出了折射率。
The Expansion of Dynamic Solving Process About a Class of Non-linear Programming Problems
Institute of Scientific and Technical Information of China (English)
ZANG Zhen-chun
2001-01-01
In this paper, we research non-linear programming problems which have a given specialstructure, some simple forms of this kind structure have been solved in some papers, here we focus on othercomplex ones.
Haroon, Muhammad; Adams, Douglas E.
2007-04-01
Fatigue tests on a stabilizer bar link of an automotive suspension system are used to initiate a crack and grow the crack size. During these tests, slow sine sweeps are used to extract narrowband restoring forces across the stabilizer bar link. The restoring forces are shown to characterize the nonlinear changes in component internal forces due to crack growth. Broadband frequency response domain techniques are used to analyze the durability response data. Nonlinear frequency domain models of the dynamic transmissibility across the cracked region are shown to change as a function of crack growth. Higher order spectra are used to show the increase in nonlinear coupling of response frequency components with the appearance and growth of the crack. It is shown that crack growth can be detected and characterized by the changes in nonlinear indicators.
Uncovering Molecular Relaxation Processes with Nonlinear Spectroscopies in the Deep UV
West, Brantley Andrew
Conical intersections mediate internal conversion dynamics that compete with even the fastest nuclear motions in molecular systems. Traditional kinetic models do not apply in this regime of commensurate electronic and nuclear motion because the surroundings do not maintain equilibrium throughout the relaxation process. This dissertation focuses on uncovering the physics associated with vibronic interactions at conical intersections. Of particular interest are coherent nuclear motions driven by steep excited state potential energy gradients. Technical advances have only recently made these dynamics accessible in many systems including DNA nucleobases and cyclic polyene molecules. Optical analogues of multidimensional NMR spectroscopies have recently yielded transformative insight in relaxation processes ranging from energy transfer in photosynthesis to bond making and breaking in liquids. Prior to the start of this research, such experiments had only been conducted at infrared and visible wavelengths. Applications in the ultraviolet were motivated by studies of numerous biological systems (e.g., DNA, proteins), but had been challenged by technical issues. The work presented in this dissertation combines pulse generation techniques developed in the optical physics community with spectroscopic techniques largely pioneered by physical chemists to implement two-dimensional ultraviolet spectroscopy (2DUV). This technique is applied at the shortest wavelengths and with the best signal-to-noise ratios reported to date. Sub-picosecond excited state deactivation processes provide photo stability to the DNA double helix. Vibrational energy transfer from the solute to surrounding solvent enables relaxation of the highly non-equilibrium ground state produced by fast internal conversion. In this dissertation, nonlinear spectroscopies carried out at cryogenic temperatures are used to uncover the particular nuclear modes in the solvent that primarily accept vibrational energy from
Nonlinear solution for radiation boundary condition of heat transfer process in human eye.
Dehghani, A; Moradi, A; Dehghani, M; Ahani, A
2011-01-01
In this paper we propose a new method based on finite element method for solving radiation boundary condition of heat equation inside the human eye and other applications. Using this method, we can solve heat equation inside human eye without need to model radiation boundary condition to a robin boundary condition. Using finite element method we can obtain a nonlinear equation, and finally we use nonlinear algorithm to solve it. The human eye is modeled as a composition of several homogeneous regions. The Ritz method in the finite element method is used for solving heat differential equation. Applying the boundary conditions, the heat radiation condition and the robin condition on the cornea surface of the eye and on the outer part of sclera are used, respectively. Simulation results of solving nonlinear boundary condition show the accuracy of the proposed method.
Nonlinear reflection process of linearly-polarized, broadband Alfv\\'en waves in the fast solar wind
Shoda, Munehito
2016-01-01
Using one-dimensional numerical simulations, we study the elementary process of Alfv\\'{e}n wave reflection in a uniform medium, including nonlinear effects. In the linear regime, Alfv\\'{e}n wave reflection is triggered only by the inhomogeneity of the medium, whereas in the nonlinear regime, it can occur via nonlinear wave-wave interactions. Such nonlinear reflection (backscattering) is typified by decay instability. In most studies of decay instabilities, the initial condition has been a circularly polarized Alfv\\'{e}n wave. In this study we consider a linearly polarized Alfv\\'en wave, which drives density fluctuations by its magnetic pressure force. For generality, we also assume a broadband wave with a red-noise spectrum. In the data analysis, we decompose the fluctuations into characteristic variables using local eigenvectors, thus revealing the behaviors of the individual modes. Different from circular-polarization case, we find that the wave steepening produces a new energy channel from the parent Alfv\\...
Koons, H. C.; Roeder, J. L.; Bauer, O. H.; Haerendel, G.; Treumann, R.
1987-01-01
Nonlinear wave decay processes have been detected in the solar wind by the plasma wave experiment aboard the Active Magnetospheric Particle Tracer Explorers (AMPTE) IRM spacecraft. The main process is the generation of ultralow-frequency ion acoustic waves from the decay of Langmuir waves near the electron plasma frequency. Frequently, this is accompanied by an enhancement of emissions near twice the plasma frequency. This enhancement is most likely due to the generation of electromagnetic waves from the coalescence of two Langmuir waves. These processes occur within the electron foreshock in front of the earth's bow shock.
Directory of Open Access Journals (Sweden)
Juan Eduardo González
2015-12-01
Full Text Available We present a scheme for conversion of pulsed light from the infrared to the red spectral region, using an aperiodically poled ferroelectric crystal within a resonant cavity in which two cascaded nonlinear optical processes occur when pumped with a pulsed Nd:YAG laser. This device emits 9 ns pulses of over 1 mJ at 710 nm and is a viable source for future biomedical applications.
Li, Yanbin; Mulani, Sameer B.; Kapania, Rakesh K.; Fei, Qingguo; Wu, Shaoqing
2017-07-01
An algorithm that integrates Karhunen-Loeve expansion (KLE) and the finite element method (FEM) is proposed to perform non-stationary random vibration analysis of structures under excitations, represented by multiple random processes that are correlated in both time and spatial domains. In KLE, the auto-covariance functions of random excitations are discretized using orthogonal basis functions. The KLE for multiple correlated random excitations relies on expansions in terms of correlated sets of random variables reflecting the cross-covariance of the random processes. During the response calculations, the eigenfunctions of KLE used to represent excitations are applied as forcing functions to the structure. The proposed algorithm is applied to a 2DOF system, a 2D cantilever beam and a 3D aircraft wing under both stationary and non-stationary correlated random excitations. Two methods are adopted to obtain the structural responses: a) the modal method and b) the direct method. Both the methods provide the statistics of the dynamic response with sufficient accuracy. The structural responses under the same type of correlated random excitations are bounded by the response obtained by perfectly correlated and uncorrelated random excitations. The structural response increases with a decrease in the correlation length and with an increase in the correlation magnitude. The proposed methodology can be applied for the analysis of any complex structure under any type of random excitation.
Bozhokin, S. V.
2010-09-01
Quantitative parameters characterizing transient processes of mastering and forgetting of photostimulation (PST) rhythms for a nonstationary electroencephalogram (EEG) are developed on the basis of a continuous wavelet transformation. Nonstationarity factor K nst(μ), as well as rhythm mastering K M (μ) and confinement K C (μ) factors are calculated for various spectral ranges μ. Photoflash mastering time τ M = τ S + τ I , which is the sum of latent silence period τ S after PST actuation and the rhythm increasing period τ I is calculated. In the case of PST, the EEG rhythm retardation time τ R relative to the beginning of PST is calculated. Rhythm forgetting time τ F = τ P + τ D after PST actuation is the sum of the preservation time τ P of the corresponding rhythm over a certain time interval and its decay period τ D . The lag time τ L of the EEG signal relative to the PST signal after its removal is determined. The proposed method is used in quantitative analysis and classification of transient processes characterizing the properties of the central nervous system. Possible applications of the method in analysis of various nonstationary signals in physics are discussed.
Tene, Yair; Tene, Noam; Tene, G.
1993-08-01
An interactive data fusion methodology of video, audio, and nonlinear structural dynamic analysis for potential application in forensic engineering is presented. The methodology was developed and successfully demonstrated in the analysis of heavy transportable bridge collapse during preparation for testing. Multiple bridge elements failures were identified after the collapse, including fracture, cracks and rupture of high performance structural materials. Videotape recording by hand held camcorder was the only source of information about the collapse sequence. The interactive data fusion methodology resulted in extracting relevant information form the videotape and from dynamic nonlinear structural analysis, leading to full account of the sequence of events during the bridge collapse.
A 3-D nonlinear recursive digital filter for video image processing
Bauer, P. H.; Qian, W.
1991-01-01
This paper introduces a recursive 3-D nonlinear digital filter, which is capable of performing noise suppression without degrading important image information such as edges in space or time. It also has the property of unnoticeable bandwidth reduction immediately after a scene change, which makes the filter an attractive preprocessor to many interframe compression algorithms. The filter consists of a nonlinear 2-D spatial subfilter and a 1-D temporal filter. In order to achieve the required computational speed and increase the flexibility of the filter, all of the linear shift-variant filter modules are of the IIR type.
Modelling non-stationary annual maximum flood heights in the lower Limpopo River basin of Mozambique
Directory of Open Access Journals (Sweden)
Daniel Maposa
2016-03-01
Full Text Available In this article we fit a time-dependent generalised extreme value (GEV distribution to annual maximum flood heights at three sites: Chokwe, Sicacate and Combomune in the lower Limpopo River basin of Mozambique. A GEV distribution is fitted to six annual maximum time series models at each site, namely: annual daily maximum (AM1, annual 2-day maximum (AM2, annual 5-day maximum (AM5, annual 7-day maximum (AM7, annual 10-day maximum (AM10 and annual 30-day maximum (AM30. Non-stationary time-dependent GEV models with a linear trend in location and scale parameters are considered in this study. The results show lack of sufficient evidence to indicate a linear trend in the location parameter at all three sites. On the other hand, the findings in this study reveal strong evidence of the existence of a linear trend in the scale parameter at Combomune and Sicacate, whilst the scale parameter had no significant linear trend at Chokwe. Further investigation in this study also reveals that the location parameter at Sicacate can be modelled by a nonlinear quadratic trend; however, the complexity of the overall model is not worthwhile in fit over a time-homogeneous model. This study shows the importance of extending the time-homogeneous GEV model to incorporate climate change factors such as trend in the lower Limpopo River basin, particularly in this era of global warming and a changing climate.Keywords: nonstationary extremes; annual maxima; lower Limpopo River; generalised extreme value
Yu, G. Y.; Luo, E. C.; Dai, W.; Hu, J. Y.
2007-10-01
This article focuses on using computational fluid dynamics (CFD) method to study several important nonlinear phenomenon and processes of a large experimental thermoacoustic-Stirling heat engine. First, the simulated physical model was introduced, and the suitable numerical scheme and algorithm for the time-dependent compressible thermoacoustic system was determined through extensive numerical tests. Then, the simulation results of the entire evolution process of self-excited thermoacoustic oscillation and the acoustical characteristics of pressure and velocity waves were presented and analyzed. Especially, the onset temperature and the saturation process of dynamic pressure were captured by the CFD simulation. In addition, another important nonlinear phenomenon accompanying the acoustic wave, which is the steady mass flow through the traveling-wave loop inside the thermoacoustic engine, was studied. To suppress the steady mass flow numerically, a fan model was adopted in the simulation. Finally, the multidimensional effects of vortex formation in the thermal buffer tube and other components were displayed numerically. Most importantly, a substantial comparison between the simulation and experiments was made, which demonstrated well the validity and powerfulness of the CFD simulation for characterizing several complicated nonlinear phenomenon involved in the self-excited thermoacoustic heat engine.
Truccolo, Wilson
2017-01-01
Point process generalized linear models (PP-GLMs) provide an important statistical framework for modeling spiking activity in single-neurons and neuronal networks. Stochastic stability is essential when sampling from these models, as done in computational neuroscience to analyze statistical properties of neuronal dynamics and in neuro-engineering to implement closed-loop applications. Here we show, however, that despite passing common goodness-of-fit tests, PP-GLMs estimated from data are often unstable, leading to divergent firing rates. The inclusion of absolute refractory periods is not a satisfactory solution since the activity then typically settles into unphysiological rates. To address these issues, we derive a framework for determining the existence and stability of fixed points of the expected conditional intensity function (CIF) for general PP-GLMs. Specifically, in nonlinear Hawkes PP-GLMs, the CIF is expressed as a function of the previous spike history and exogenous inputs. We use a mean-field quasi-renewal (QR) approximation that decomposes spike history effects into the contribution of the last spike and an average of the CIF over all spike histories prior to the last spike. Fixed points for stationary rates are derived as self-consistent solutions of integral equations. Bifurcation analysis and the number of fixed points predict that the original models can show stable, divergent, and metastable (fragile) dynamics. For fragile models, fluctuations of the single-neuron dynamics predict expected divergence times after which rates approach unphysiologically high values. This metric can be used to estimate the probability of rates to remain physiological for given time periods, e.g., for simulation purposes. We demonstrate the use of the stability framework using simulated single-neuron examples and neurophysiological recordings. Finally, we show how to adapt PP-GLM estimation procedures to guarantee model stability. Overall, our results provide a
Climate variance influence on the non-stationary plankton dynamics.
Molinero, Juan Carlos; Reygondeau, Gabriel; Bonnet, Delphine
2013-08-01
We examined plankton responses to climate variance by using high temporal resolution data from 1988 to 2007 in the Western English Channel. Climate variability modified both the magnitude and length of the seasonal signal of sea surface temperature, as well as the timing and depth of the thermocline. These changes permeated the pelagic system yielding conspicuous modifications in the phenology of autotroph communities and zooplankton. The climate variance envelope, thus far little considered in climate-plankton studies, is closely coupled with the non-stationary dynamics of plankton, and sheds light on impending ecological shifts and plankton structural changes. Our study calls for the integration of the non-stationary relationship between climate and plankton in prognostic models on the productivity of marine ecosystems.
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....
ADSL Transceivers Applying DSM and Their Nonstationary Noise Robustness
Directory of Open Access Journals (Sweden)
Bostoen Tom
2006-01-01
Full Text Available Dynamic spectrum management (DSM comprises a new set of techniques for multiuser power allocation and/or detection in digital subscriber line (DSL networks. At the Alcatel Research and Innovation Labs, we have recently developed a DSM test bed, which allows the performance of DSM algorithms to be evaluated in practice. With this test bed, we have evaluated the performance of a DSM level-1 algorithm known as iterative water-filling in an ADSL scenario. This paper describes the results of, on the one hand, the performance gains achieved with iterative water-filling, and, on the other hand, the nonstationary noise robustness of DSM-enabled ADSL modems. It will be shown that DSM trades off nonstationary noise robustness for performance improvements. A new bit swap procedure is then introduced to increase the noise robustness when applying DSM.
On-line blind separation of non-stationary signals
Directory of Open Access Journals (Sweden)
Todorović-Zarkula Slavica
2005-01-01
Full Text Available This paper addresses the problem of blind separation of non-stationary signals. We introduce an on-line separating algorithm for estimation of independent source signals using the assumption of non-stationary of sources. As a separating model, we apply a self-organizing neural network with lateral connections, and define a contrast function based on correlation of the network outputs. A separating algorithm for adaptation of the network weights is derived using the state-space model of the network dynamics, and the extended Kalman filter. Simulation results obtained in blind separation of artificial and real-world signals from their artificial mixtures have shown that separating algorithm based on the extended Kalman filter outperforms stochastic gradient based algorithm both in convergence speed and estimation accuracy.
Testing for long memory in potentially nonstationary perturbed fractional processes
DEFF Research Database (Denmark)
Nielsen, Frank; Frederiksen, Per S.
¤er simulation results that show good size properties of the tests, with power against spurious long memory. An empirical study of daily log-squared returns series of exchange rates and DJIA30 stocks shows that indeed there is long memory in exchange rate volatility and stock return volatility....
Cultural Evolution as a Non-Stationary Stochastic Process
Nicholson, Arwen E
2016-01-01
We present an individual based model of cultural evolution, where interacting agents are coded by binary strings standing for strategies for action, blueprints for products or attitudes and beliefs. The model is patterned on an established model of biological evolution, the Tangled Nature Model (TNM), where a `tangle' of interactions between agents determines their reproductive success. In addition, our agents also have the ability to copy part of each other's strategy, a feature inspired by the Axelrod model of cultural diversity. Unlike the latter, but similarly to the TNM, the model dynamics goes through a series of metastable stages of increasing length, each characterized by mutually enforcing cultural patterns. These patterns are abruptly replaced by other patterns characteristic of the next metastable period. We analyze the time dependence of the population and diversity in the system, show how different cultures are formed and merge, and how their survival probability lacks, in the model, a finite ave...
Comparative Analysis of Radiometer Systems Using Non-Stationary Processes
Racette, Paul; Lang, Roger; Krebs, Carolyn A. (Technical Monitor)
2002-01-01
Radiometers require periodic calibration to correct for instabilities in the receiver response. Various calibration techniques exist that minimize the effect of instabilities in the receivers. The optimal technique depends upon many parameters. Some parameters are constrained by the particular application and others can be chosen in the system design. For example, the measurement uncertainty may be reduced to the limits of the resolution of the measurement (sensitivity) if periodic absolute calibration can be performed with sufficient frequency. However if the period between calibrations is long, a reference-differencing technique, i.e. Dicke-type design, can yield better performance. The measurement uncertainty not only depends upon the detection scheme but also on the number of pixels between calibrations, the integration time per pixel, integration time per calibration reference measurement, calibration reference temperature, and the brightness temperature of what is being measured. The best scheme for reducing the measurement uncertainty also depends, in large part, on the stability of the receiver electronics. In this presentation a framework for evaluating calibration schemes for a wide range of system architectures is presented. Two methods for treating receiver non-stationarity are compared with radiometer measurements.
Mathematical modeling suggests that periodontitis behaves as a non-linear chaotic dynamical process
Papantonopoulos, G.H.; Takahashi, K.; Bountis, T.; Loos, B.G.
2013-01-01
Background: This study aims to expand on a previously presented cellular automata model and further explore the non-linear dynamics of periodontitis. Additionally the authors investigated whether their mathematical model could predict the two known types of periodontitis, aggressive (AgP) and
The Nonlinear Interaction Process in the Wave Assimilation Model and Its Experiments
Institute of Scientific and Technical Information of China (English)
杨永增; 纪永刚; 袁业立
2003-01-01
This paper presents a composite interaction formula based on the discrete-interactionoperator of wave-wave nonlinear interaction for deriving its adjoint source function in the wave assimilation model. Assimilation experiments were performed using the significant wave heights observed by the TOPES/POSEIDON satellite, and the gradient distribution in the physical space wasalso analyzed preliminarily.
Mathematical modeling suggests that periodontitis behaves as a non-linear chaotic dynamical process
Papantonopoulos, G.H.; Takahashi, K.; Bountis, T.; Loos, B.G.
2013-01-01
Background: This study aims to expand on a previously presented cellular automata model and further explore the non-linear dynamics of periodontitis. Additionally the authors investigated whether their mathematical model could predict the two known types of periodontitis, aggressive (AgP) and chroni
Quantum entanglement for two qubits in a nonstationary cavity
Berman, Oleg L.; Kezerashvili, Roman Ya.; Lozovik, Yurii E.
2016-11-01
The quantum entanglement and the probability of the dynamical Lamb effect for two qubits caused by nonadiabatic fast change of the boundary conditions are studied. The conditional concurrence of the qubits for each fixed number of created photons in a nonstationary cavity is obtained as a measure of the dynamical quantum entanglement due to the dynamical Lamb effect. We discuss the physical realization of the dynamical Lamb effect, based on superconducting qubits.
Robust estimation of nonstationary, fractionally integrated, autoregressive, stochastic volatility
Mark J. Jensen
2015-01-01
Empirical volatility studies have discovered nonstationary, long-memory dynamics in the volatility of the stock market and foreign exchange rates. This highly persistent, infinite variance - but still mean reverting - behavior is commonly found with nonparametric estimates of the fractional differencing parameter d, for financial volatility. In this paper, a fully parametric Bayesian estimator, robust to nonstationarity, is designed for the fractionally integrated, autoregressive, stochastic ...
Quantum entanglement for two qubits in a nonstationary cavity
Berman, Oleg L; Lozovik, Yurii E
2016-01-01
The quantum entanglement and the probability of the dynamical Lamb effect for two qubits caused by non-adiabatic fast change of the boundary conditions are studied. The conditional concurrence of the qubits for each fixed number of created photons in a nonstationary cavity is obtained as a measure of the dynamical quantum entanglement due to the dynamical Lamb effect. We discuss the physical realization of the dynamical Lamb effect, based on superconducting qubits.
Nonstationary Root Causes of Cobb’s Paradox
2010-07-01
Stability, Change Management , Configuration Management image designed by Miracle Riese » Report Documentation Page Form ApprovedOMB No. 0704-0188...growth due to nonstationary environments. conFiGuRAtion AnD cHAnGe MAnAGeMent This article is not deliberately focused on a single weapon system or...political climate, or changes in leadership or ownership. Therefore, change management deals with nonphysical aspects of a system, such as
Nonstationary ETAS models for nonstandard earthquakes
Kumazawa, Takao; Ogata, Yosihiko
2014-01-01
The conditional intensity function of a point process is a useful tool for generating probability forecasts of earthquakes. The epidemic-type aftershock sequence (ETAS) model is defined by a conditional intensity function, and the corresponding point process is equivalent to a branching process, assuming that an earthquake generates a cluster of offspring earthquakes (triggered earthquakes or so-called aftershocks). Further, the size of the first-generation cluster depends on the magnitude of...
Directory of Open Access Journals (Sweden)
P. Y. Rogov
2015-09-01
Full Text Available The paper deals with mathematical model of linear and nonlinear processes occurring at the propagation of femtosecond laser pulses in the vitreous of the human eye. Methods of computing modeling are applied for the nonlinear spectral equation solution describing the dynamics of a two-dimensional TE-polarized radiation in a homogeneous isotropic medium with cubic fast-response nonlinearity without the usage of slowly varying envelope approximation. Environments close to the optical media parameters of the eye were used for the simulation. The model of femtosecond radiation propagation takes into account the process dynamics for dispersion broadening of pulses in time and the occurence of the self-focusing near the retina when passing through the vitreous body of the eye. Dependence between the pulse duration on the retina has been revealed and the duration of the input pulse and the values of power density at which there is self-focusing have been found. It is shown that the main mechanism of radiation damage with the use of titanium-sapphire laser is photoionization. The results coincide with those obtained by the other scientists, and are usable for creation Russian laser safety standards for femtosecond laser systems.
Starosvetsky, Y; Manevitch, L I
2011-04-01
An analytical investigation of nonstationary processes in a Duffing oscillator subject to biharmonic forcing, under conditions of primary resonance, is carried out. The earlier developed methodology of limiting phase trajectories (LPTs) for studying highly nonstationary regimes, characterized by intense energy exchanges between the different degrees of freedom, is successfully applied to the system under investigation. Two distinct types of LPT trajectories are described in the first part of the study. Conditions for the recurrent transitions in time from one type of LPT to another were derived in the first part of the analysis corresponding to the undamped case. An approximation of the LPT related to the higher amplitude of oscillations was derived using nonsmooth transformations. An analysis carried out in the study has revealed the necessary and sufficient conditions for excitation of relaxation oscillations exhibited by a lightly damped system. It was also demonstrated that the mechanism of relaxations may be approximated and explained by the methodology of LPTs, characterized by strong energy exchanges between the coupled oscillators or, alternatively, a single oscillator and an external source of energy. The results of analytical approximations and numerical simulations are observed to be in quite satisfactory agreement.
Local multifractal detrended fluctuation analysis for non-stationary image's texture segmentation
Wang, Fang; Li, Zong-shou; Li, Jin-wei
2014-12-01
Feature extraction plays a great important role in image processing and pattern recognition. As a power tool, multifractal theory is recently employed for this job. However, traditional multifractal methods are proposed to analyze the objects with stationary measure and cannot for non-stationary measure. The works of this paper is twofold. First, the definition of stationary image and 2D image feature detection methods are proposed. Second, a novel feature extraction scheme for non-stationary image is proposed by local multifractal detrended fluctuation analysis (Local MF-DFA), which is based on 2D MF-DFA. A set of new multifractal descriptors, called local generalized Hurst exponent (Lhq) is defined to characterize the local scaling properties of textures. To test the proposed method, both the novel texture descriptor and other two multifractal indicators, namely, local Hölder coefficients based on capacity measure and multifractal dimension Dq based on multifractal differential box-counting (MDBC) method, are compared in segmentation experiments. The first experiment indicates that the segmentation results obtained by the proposed Lhq are better than the MDBC-based Dq slightly and superior to the local Hölder coefficients significantly. The results in the second experiment demonstrate that the Lhq can distinguish the texture images more effectively and provide more robust segmentations than the MDBC-based Dq significantly.
Hydrodynamic studies of gas objects of the Shurtan field with nonstationary filtering regimes
Energy Technology Data Exchange (ETDEWEB)
Zhumayev, Kh.B.; Abayev, M.Kh.
1978-01-01
In the prospecting and exploratory wells of west and south Uzbekistan, hydrodynamic studies of the influx of gas and oil during their testing were made with stationary filtering regimes. Analysis of results of the well studies with stationary and nonstationary filtering regimes made it possible to reveal greater information content of the latter. Results are compared of hydrodynamic studies on both filtering regimes in the example of the gas-condensate field Shurtan. A technique is presented for the studies. The results were processed according to ''Instructions for Studying Gas Wells.'' In order to compare the results of hydrodynamic studies, the coefficience of filtering resistance A and V were defined, the absolutely free output of wells and the coefficient of hydraulic conductance of bed Ye. Data are presented in a table and are analyzed. It is indicated that by making hydrodynamic studies with nonstationary filtering regimes of gas, one can obtain the most important data regarding the hydrodynamic condition of the gas formations, and reduce the periods for well testing. The economic effect is calculated and recommendations are made for studying the fields.
A Novel Approach for Nonstationary Time Series Analysis with Time-Invariant Correlation Coefficient
Directory of Open Access Journals (Sweden)
Chengrui Liu
2014-01-01
Full Text Available We will concentrate on the modeling and analysis of a class of nonstationary time series, called correlation coefficient stationary series, which commonly exists in practical engineering. First, the concept and scope of correlation coefficient stationary series are discussed to get a better understanding. Second, a theorem is proposed to determine standard deviation function for correlation coefficient stationary series. Third, we propose a moving multiple-point average method to determine the function forms for mean and standard deviation, which can help to improve the analysis precision, especially in the context of limited sample size. Fourth, the conditional likelihood approach is utilized to estimate the model parameters. In addition, we discuss the correlation coefficient stationarity test method, which can contribute to the verification of modeling validity. Monte Carlo simulation study illustrates the authentication of the theorem and the validity of the established method. Empirical study shows that the approach can satisfactorily explain the nonstationary behavior of many practical data sets, including stock returns, maximum power load, China money supply, and foreign currency exchange rate. The effectiveness of these processes is addressed by forecasting performance.
Around and about an application of the GAMLSS package to non-stationary flood frequency analysis
Debele, S. E.; Bogdanowicz, E.; Strupczewski, W. G.
2017-08-01
The non-stationarity of hydrologic processes due to climate change or human activities is challenging for the researchers and practitioners. However, the practical requirements for taking into account non-stationarity as a support in decision-making procedures exceed the up-to-date development of the theory and the of software. Currently, the most popular and freely available software package that allows for non-stationary statistical analysis is the GAMLSS (generalized additive models for location, scale and shape) package. GAMLSS has been used in a variety of fields. There are also several papers recommending GAMLSS in hydrological problems; however, there are still important issues which have not previously been discussed concerning mainly GAMLSS applicability not only for research and academic purposes, but also in a design practice. In this paper, we present a summary of our experiences in the implementation of GAMLSS to non-stationary flood frequency analysis, highlighting its advantages and pointing out weaknesses with regard to methodological and practical topics.
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
Dual-point composition control for a high-purity ideal heat integrated distillation column (HIDiC) is addressed in this work. Three measures are suggested and combined for overcoming process inherent nonlinearities:(1) variable scaling; (2) multi-model representation of process dynamics and (3) feedforward compensation. These strategies can offer the developed control systems with several distinct advantages: (1) capability of dealing with severe disturbances; (2) tight tuning of controller parameters and (3) high robustness with respect to variation of operating conditions. Simulation results demonstrate the effectiveness of the proposed methodology.
ON NONSTATIONARY STOCHASTIC MODELS FOR EARTHQUAKES.
Safak, Erdal; Boore, David M.
1986-01-01
A seismological stochastic model for earthquake ground-motion description is presented. Seismological models are based on the physical properties of the source and the medium and have significant advantages over the widely used empirical models. The model discussed here provides a convenient form for estimating structural response by using random vibration theory. A commonly used random process for ground acceleration, filtered white-noise multiplied by an envelope function, introduces some errors in response calculations for structures whose periods are longer than the faulting duration. An alternate random process, filtered shot-noise process, eliminates these errors.
Directory of Open Access Journals (Sweden)
E. D. Resende
2007-09-01
Full Text Available The freezing process is considered as a propagation problem and mathematically classified as an "initial value problem." The mathematical formulation involves a complex situation of heat transfer with simultaneous changes of phase and abrupt variation in thermal properties. The objective of the present work is to solve the non-linear heat transfer equation for food freezing processes using orthogonal collocation on finite elements. This technique has not yet been applied to freezing processes and represents an alternative numerical approach in this area. The results obtained confirmed the good capability of the numerical method, which allows the simulation of the freezing process in approximately one minute of computer time, qualifying its application in a mathematical optimising procedure. The influence of the latent heat released during the crystallisation phenomena was identified by the significant increase in heat load in the early stages of the freezing process.
Nonlinear analysis on the coupling process of electromagnetic vibrator and earth
Institute of Scientific and Technical Information of China (English)
CHEN; Zubin; TENG; Jiwen; LIN; Jun; ZHANG; Linhang; JIANG
2005-01-01
The linear model based on the hydraulic pressure vibrator has been no longer adaptable to the electromagnetic vibrator. In order to realize the effective transmission of the limited energy from the vibrator to the ground, it is important to study the coupling model of the electromagnetic vibrator and the earth. In this paper, a nonlinear restore term was introduced to the coupling model because of the existence of a large amount of harmonics in the vibrator baseplate. The nonlinear vibration analysis was applied to the model by the multiscale method. In the course of energy transmission from the vibrator to the ground, ultraharmonic resonance was used to explain the generation of harmonics. An improved scheme was advanced to select the cross correlation reference signal in the vibrator seismic exploration. Good application results were obtained in field experiments.
Non-linear processes in thin titanium nitride transmission lines for parametric amplification
Vissers, Michael; Gao, Jiansong; Chaudhuri, Suptarshi; Bockstiegel, Clint; Sandberg, Martin; Pappas, David P.
2013-03-01
Nitride superconductors, such as titanium nitride and niobium titanium nitride, are a non-linear, low dissipation medium at microwave frequencies. The lossless nonlinearity may be probed and utilized. Important applications include generation of higher harmonics, e.g. 3f, and a microwave version of the optical paramagnetic amplifier, i.e. the degenerate-pump case of four-photon mixing (FPM). An amplifier based on these principles should allow for very wide bandwidth, low noise (quantum limited) and high dynamic range devices. These measurements are performed via a single layer, 3 meter long TiN spiral and measured at temperatures below 100 mK. Initial results of the design, fabrication, testing, and impedance optimization of a titanium nitride based parametric amplifier are presented.
Partial and total actuator faults accommodation for input-affine nonlinear process plants.
Mihankhah, Amin; Salmasi, Farzad R; Salahshoor, Karim
2013-05-01
In this paper, a new fault-tolerant control system is proposed for input-affine nonlinear plants based on Model Reference Adaptive System (MRAS) structure. The proposed method has the capability to accommodate both partial and total actuator failures along with bounded external disturbances. In this methodology, the conventional MRAS control law is modified by augmenting two compensating terms. One of these terms is added to eliminate the nonlinear dynamic, while the other is reinforced to compensate the distractive effects of the total actuator faults and external disturbances. In addition, no Fault Detection and Diagnosis (FDD) unit is needed in the proposed method. Moreover, the control structure has good robustness capability against the parameter variation. The performance of this scheme is evaluated using a CSTR system and the results were satisfactory.
4th International Conference on Condition Monitoring of Machinery in Non-Stationary Operations
Zimroz, Radoslaw; Bartelmus, Walter; Haddar, Mohamed
2016-01-01
The book provides readers with a snapshot of recent research and technological trends in the field of condition monitoring of machinery working under a broad range of operating conditions. Each chapter, accepted after a rigorous peer-review process, reports on an original piece of work presented and discussed at the 4th International Conference on Condition Monitoring of Machinery in Non-stationary Operations, CMMNO 2014, held on December 15-16, 2014, in Lyon, France. The contributions have been grouped into three different sections according to the main subfield (signal processing, data mining, or condition monitoring techniques) they are related to. The book includes both theoretical developments as well as a number of industrial case studies, in different areas including, but not limited to: noise and vibration; vibro-acoustic diagnosis; signal processing techniques; diagnostic data analysis; instantaneous speed identification; monitoring and diagnostic systems; and dynamic and fault modeling. This book no...
Energy Technology Data Exchange (ETDEWEB)
Morsi, Walid G. [University of New Brunswick, Fredericton, New Brunswick (Canada); El-Hawary, M.E. [Dalhousie University, Halifax, Nova Scotia (Canada)
2010-07-15
High power quality (PQ) level represents one of the main objectives towards smart grid. The currently used PQIs that are a measure of the PQ level are defined under the umbrella of the Fourier foundation that produces unrealistic results in case of non-stationary PQ disturbances. In order to accurately measure those indices, wavelet packet transform (WPT) is used in this paper to reformulate the recommended PQIs and hence benefiting from the WPT capabilities in accurately analyzing non-stationary waveforms and providing a uniform time-frequency sub-bands leading to reduced size of the data to be processed which is a necessity to facilitate the implementation of smart grid. Numerical examples' results considering non-stationary waveforms prove the suitability of the WPT for PQIs measurement; also the results indicate that Daubechies 10 could be the best candidate wavelet basis function that could provide acceptable accuracy while requiring less number of wavelet coefficients and hence reducing the data size. Moreover, a new time-frequency overall and node crest factors are introduced in this paper. The new node crest factor is able to determine the node or the sub-band that is responsible for the largest impact which could not be achieved using traditional approaches. (author)
Noury, Nima; Hipp, Joerg F; Siegel, Markus
2016-10-15
Transcranial electric stimulation (tES) is a promising tool to non-invasively manipulate neuronal activity in the human brain. Several studies have shown behavioral effects of tES, but stimulation artifacts complicate the simultaneous investigation of neural activity with EEG or MEG. Here, we first show for EEG and MEG, that contrary to previous assumptions, artifacts do not simply reflect stimulation currents, but that heartbeat and respiration non-linearly modulate stimulation artifacts. These modulations occur irrespective of the stimulation frequency, i.e. during both transcranial alternating and direct current stimulations (tACS and tDCS). Second, we show that, although at first sight previously employed artifact rejection methods may seem to remove artifacts, data are still contaminated by non-linear stimulation artifacts. Because of their complex nature and dependence on the subjects' physiological state, these artifacts are prone to be mistaken as neural entrainment. In sum, our results uncover non-linear tES artifacts, show that current techniques fail to fully remove them, and pave the way for new artifact rejection methods.
Directory of Open Access Journals (Sweden)
Maruthai Suresh
2010-10-01
Full Text Available A nonlinear process, the heat exchanger whose parameters vary with respect to the process variable, is considered. The time constant and gain of the chosen process vary as a function of temperature. The limitations of the conventional feedback controller tuned using Ziegler-Nichols settings for the chosen process are brought out. The servo and regulatory responses through simulation and experimentation for various magnitudes of set-point changes and load changes at various operating points with the controller tuned only at a chosen nominal operating point are obtained and analyzed. Regulatory responses for output load changes are studied. The efficiency of feedforward controller and the effects of modeling error have been brought out. An IMC based system is presented to understand clearly how variations of system parameters affect the performance of the controller. The present work illustrates the effectiveness of Feedforward and IMC controller.
3rd International Conference on Condition Monitoring of Machinery in Non-Stationary Operations
Rubini, Riccardo; D'Elia, Gianluca; Cocconcelli, Marco; Chaari, Fakher; Zimroz, Radoslaw; Bartelmus, Walter; Haddar, Mohamed
2014-01-01
This book presents the processings of the third edition of the Condition Monitoring of Machinery in Non-Stationary Operations (CMMNO13) which was held in Ferrara, Italy. This yearly event merges an international community of researchers who met – in 2011 in Wroclaw (Poland) and in 2012 in Hammamet (Tunisia) – to discuss issues of diagnostics of rotating machines operating in complex motion and/or load conditions. The growing interest of the industrial world on the topics covered by the CMMNO13 involves the fields of packaging, automotive, agricultural, mining, processing and wind machines in addition to that of the systems for data acquisition.The participation of speakers and visitors from industry makes the event an opportunity for immediate assessment of the potential applications of advanced methodologies for the signal analysis. Signals acquired from machines often contain contributions from several different components as well as noise. Therefore, the major challenge of condition monitoring is to po...
Heterodyne-Detected Ultrafast X-Ray Diffraction and Scattering from Nonstationary States
Bennett, Kochise; Mukamel, Shaul
2016-01-01
Free-electron laser hard X-ray light sources can provide high fluence, femtosecond pulses, enabling the time-resolved probing of structural dynamics and elementary relaxation processes in molecules. Traditional X-ray elastic scattering from crystals in the ground state consists of sharp Bragg diffraction peaks that arise from pairs of molecules and reveal the ground state charge density. Scattering of ultrashort X-ray pulses from gases, liquids, and even single molecules is more complex and involves both single- and two- molecule contributions, diffuse (non-Bragg) features, elastic and inelastic components, contributions of electronic coherences in nonstationary states, and interferences between scattering off different states (heterodyne detection). We present a unified description that covers all these processes and discuss their relative magnitudes for gas-phase NaI. Conditions for the observation of holographic (heterodyne) interference, which has been recently discussed [1], are clarified.
Zhukov, A. A.; Shapiro, D. S.; Remizov, S. V.; Pogosov, W. V.; Lozovik, Yu. E.
2017-02-01
We consider a superconducting qubit coupled to the nonstationary transmission line cavity with modulated frequency taking into account energy dissipation. Previously, it was demonstrated that in the case of a single nonadiabatical modulation of a cavity frequency there are two channels of a two-level system excitation which are due to the absorption of Casimir photons and due to the counterrotating wave processes responsible for the dynamical Lamb effect. We show that the parametric periodical modulation of the resonator frequency can increase dramatically the excitation probability. Remarkably, counterrotating wave processes under such a modulation start to play an important role even in the resonant regime. Our predictions can be used to control qubit-resonator quantum states as well as to study experimentally different channels of a parametric qubit excitation.
Schertzer, D.; Lovejoy, S.
1. The conference The third conference on "Nonlinear VAriability in Geophysics: scaling and multifractal processes" (NVAG 3) was held in Cargese, Corsica, Sept. 10-17, 1993. NVAG3 was joint American Geophysical Union Chapman and European Geophysical Society Richardson Memorial conference, the first specialist conference jointly sponsored by the two organizations. It followed NVAG1 (Montreal, Aug. 1986), NVAG2 (Paris, June 1988; Schertzer and Lovejoy, 1991), five consecutive annual sessions at EGS general assemblies and two consecutive spring AGU meeting sessions. As with the other conferences and workshops mentioned above, the aim was to develop confrontation between theories and experiments on scaling/multifractal behaviour of geophysical fields. Subjects covered included climate, clouds, earthquakes, atmospheric and ocean dynamics, tectonics, precipitation, hydrology, the solar cycle and volcanoes. Areas of focus included new methods of data analysis (especially those used for the reliable estimation of multifractal and scaling exponents), as well as their application to rapidly growing data bases from in situ networks and remote sensing. The corresponding modelling, prediction and estimation techniques were also emphasized as were the current debates about stochastic and deterministic dynamics, fractal geometry and multifractals, self-organized criticality and multifractal fields, each of which was the subject of a specific general discussion. The conference started with a one day short course of multifractals featuring four lectures on a) Fundamentals of multifractals: dimension, codimensions, codimension formalism, b) Multifractal estimation techniques: (PDMS, DTM), c) Numerical simulations, Generalized Scale Invariance analysis, d) Advanced multifractals, singular statistics, phase transitions, self-organized criticality and Lie cascades (given by D. Schertzer and S. Lovejoy, detailed course notes were sent to participants shortly after the conference). This
Directory of Open Access Journals (Sweden)
D. Schertzer
1994-01-01
Full Text Available 1. The conference The third conference on "Nonlinear VAriability in Geophysics: scaling and multifractal processes" (NVAG 3 was held in Cargese, Corsica, Sept. 10-17, 1993. NVAG3 was joint American Geophysical Union Chapman and European Geophysical Society Richardson Memorial conference, the first specialist conference jointly sponsored by the two organizations. It followed NVAG1 (Montreal, Aug. 1986, NVAG2 (Paris, June 1988; Schertzer and Lovejoy, 1991, five consecutive annual sessions at EGS general assemblies and two consecutive spring AGU meeting sessions. As with the other conferences and workshops mentioned above, the aim was to develop confrontation between theories and experiments on scaling/multifractal behaviour of geophysical fields. Subjects covered included climate, clouds, earthquakes, atmospheric and ocean dynamics, tectonics, precipitation, hydrology, the solar cycle and volcanoes. Areas of focus included new methods of data analysis (especially those used for the reliable estimation of multifractal and scaling exponents, as well as their application to rapidly growing data bases from in situ networks and remote sensing. The corresponding modelling, prediction and estimation techniques were also emphasized as were the current debates about stochastic and deterministic dynamics, fractal geometry and multifractals, self-organized criticality and multifractal fields, each of which was the subject of a specific general discussion. The conference started with a one day short course of multifractals featuring four lectures on a Fundamentals of multifractals: dimension, codimensions, codimension formalism, b Multifractal estimation techniques: (PDMS, DTM, c Numerical simulations, Generalized Scale Invariance analysis, d Advanced multifractals, singular statistics, phase transitions, self-organized criticality and Lie cascades (given by D. Schertzer and S. Lovejoy, detailed course notes were sent to participants shortly after the
DEFF Research Database (Denmark)
Koefoed, Jacob Gade; Christensen, Jesper Bjerge; Rottwitt, Karsten
2017-01-01
We present a general model, based on a Hamiltonian approach, for the joint quantum state of photon pairs generated through pulsed spontaneous four-wave mixing, including nonlinear phase modulation and a finite material response time. For the case of a silica fiber, it is found that the pair......-dependent change in quantum-mechanical purity may be observed in silica. This shows that Raman scattering not only introduces noise, but can also drastically change the spectral correlations in photon pairs when pumped with short pulses....
Institute of Scientific and Technical Information of China (English)
CHEN Yu-Li; LIU Bin; YIN Ya-Jun; HUANG Yong-Gang; HWUANG Keh-Chih
2008-01-01
The tensile deformations and fractures of super carbon nanotubes (SCNTs) with armchair-armchair topology are investigated by using the atomic-scale finite element method. SCNTs generated from carbon nanotubes (CNTs) with different characteristic aspect ratios are found to have different nonlinear behaviours under uniaxiai tensions. Specifically, an SCNT with higher aspect ratio has three distinct stages: rotation, stretch and rupture, while an SCNT with lower aspect ratio has only two stages. This information may compensate for previous work and enrich our knowledge about Y-branched CNTs and SCNTs.
DEFF Research Database (Denmark)
Nielsen, Søren R. K.; Peng, Yongbo; Sichani, Mahdi Teimouri
2016-01-01
The paper deals with the response and reliability analysis of hysteretic or geometric nonlinear uncertain dynamical systems of arbitrary dimensionality driven by stochastic processes. The approach is based on the probability density evolution method proposed by Li and Chen (Stochastic dynamics...... of structures, 1st edn. Wiley, London, 2009; Probab Eng Mech 20(1):33–44, 2005), which circumvents the dimensional curse of traditional methods for the determination of non-stationary probability densities based on Markov process assumptions and the numerical solution of the related Fokker–Planck and Kolmogorov......–Feller equations. The main obstacle of the method is that a multi-dimensional convolution integral needs to be carried out over the sample space of a set of basic random variables, for which reason the number of these need to be relatively low. In order to handle this problem an approach is suggested, which...
Neubert, M.; Winkler, J.
2012-12-01
This contribution continues an article series [1,2] about the nonlinear model-based control of the Czochralski crystal growth process. The key idea of the presented approach is to use a sophisticated combination of nonlinear model-based and conventional (linear) PI controllers for tracking of both, crystal radius and growth rate. Using heater power and pulling speed as manipulated variables several controller structures are possible. The present part tries to systematize the properties of the materials to be grown in order to get unambiguous decision criteria for a most profitable choice of the controller structure. For this purpose a material specific constant M called interface mobility and a more process specific constant S called system response number are introduced. While the first one summarizes important material properties like thermal conductivity and latent heat the latter one characterizes the process by evaluating the average axial thermal gradients at the phase boundary and the actual growth rate at which the crystal is grown. Furthermore these characteristic numbers are useful for establishing a scheduling strategy for the PI controller parameters in order to improve the controller performance. Finally, both numbers give a better understanding of the general thermal system dynamics of the Czochralski technique.
Ding, Shun-Liang; Song, En-Zhe; Yang, Li-Ping; Yao, Chong; Ma, Xiu-Zhen
2017-02-01
The nonlinear dynamics of the combustion process in the lean-burn premixed natural gas engine are studied in this paper. Based on nonlinear dynamic theory, the complexity of the combustion process is analyzed under different injection timing conditions. The phase spaces are reconstructed for the experimentally obtained in-cylinder pressure real-time series and the return maps are plotted for the IMEP time series. The results of phase space reconstruction manifest that the attractors are limited to the finite range in the reconstructed phase space. The attractors have a folded and twist geometry structure. The attractors under medium injection timing conditions are looser and more complex. The return maps indicate the coexistence of the stochastic and deterministic components in the patterns combustion process. With the injection timing increasing, there are both a transition from stochastic to deterministic and a transition from deterministic to stochastic, forming the region of deterministic behavior. The largest Lyapunov exponents (LLE) for in-cylinder pressure time series are calculated and the coefficients of variations (COV) of IMEP are also analyzed. The results express that the LLE values are positive. There are a "steep increase" and a "steep decrease" for the LLE and COV values as the injection timing increasing.
Finite-dimensional constrained fuzzy control for a class of nonlinear distributed process systems.
Wu, Huai-Ning; Li, Han-Xiong
2007-10-01
This correspondence studies the problem of finite-dimensional constrained fuzzy control for a class of systems described by nonlinear parabolic partial differential equations (PDEs). Initially, Galerkin's method is applied to the PDE system to derive a nonlinear ordinary differential equation (ODE) system that accurately describes the dynamics of the dominant (slow) modes of the PDE system. Subsequently, a systematic modeling procedure is given to construct exactly a Takagi-Sugeno (T-S) fuzzy model for the finite-dimensional ODE system under state constraints. Then, based on the T-S fuzzy model, a sufficient condition for the existence of a stabilizing fuzzy controller is derived, which guarantees that the state constraints are satisfied and provides an upper bound on the quadratic performance function for the finite-dimensional slow system. The resulting fuzzy controllers can also guarantee the exponential stability of the closed-loop PDE system. Moreover, a local optimization algorithm based on the linear matrix inequalities is proposed to compute the feedback gain matrices of a suboptimal fuzzy controller in the sense of minimizing the quadratic performance bound. Finally, the proposed design method is applied to the control of the temperature profile of a catalytic rod.
Rapid prediction method for nonlinear expansion process of medical vascular stent
Institute of Scientific and Technical Information of China (English)
无
2009-01-01
A neural network model with high nonlinear recognition capability was constructed to describe the relationship between the deformation impact factors and the deformation results of vascular stent.Then,using the weighted correction method with the attached momentum term,the network training algorithm was optimized by introducing learning factor η and momentum factor ψ,so the speed of the network training and the system robustness were enhanced.The network was trained by some practi-cal cases,and the statistical hypothesis validation was made for the predictive errors.It was shown that the average difference between the intelligent predictive result of vascular stent deformation neu-ral network and the nonlinear finite element analysis result was less than 0.03%,and the trained net-work could perfectly predict the vascular stent deformation.Further more,the rapid evaluation tool for the vascular stent mechanics performance was established using the Pro/Toolkit and the intelligent neural network predictive model of vascular stent expansion.The proposed tool system with strong practicality and high efficiency can significantly shorten the product development cycle of vascular stent.
Seider, Warren D.; Ungar, Lyle H.
1987-01-01
Describes a course in nonlinear mathematics courses offered at the University of Pennsylvania which provides an opportunity for students to examine the complex solution spaces that chemical engineers encounter. Topics include modeling many chemical processes, especially those involving reaction and diffusion, auto catalytic reactions, phase…
Grigoryeva, Lyudmila; Henriques, Julie; Larger, Laurent; Ortega, Juan-Pablo
2016-07-01
This letter addresses the reservoir design problem in the context of delay-based reservoir computers for multidimensional input signals, parallel architectures, and real-time multitasking. First, an approximating reservoir model is presented in those frameworks that provides an explicit functional link between the reservoir architecture and its performance in the execution of a specific task. Second, the inference properties of the ridge regression estimator in the multivariate context are used to assess the impact of finite sample training on the decrease of the reservoir capacity. Finally, an empirical study is conducted that shows the adequacy of the theoretical results with the empirical performances exhibited by various reservoir architectures in the execution of several nonlinear tasks with multidimensional inputs. Our results confirm the robustness properties of the parallel reservoir architecture with respect to task misspecification and parameter choice already documented in the literature.
THz Generation by Optical Rectification and Competition with Other Nonlinear Processes
Institute of Scientific and Technical Information of China (English)
ZHAO Zhen-Yu; HAMEAU Sophie; TIGNON Jér(o)me
2008-01-01
We present a study of the competition between tera-hertz (THz) generation by optical rectification in (110)Zn Te crystals,two-photon absorption,second harmonic generation and flee-carrier absorption.The two-photon nonlinear absorption coefficient,second harmonic generation efficiency and flee-carrier absorption coefficient in the THz range are measured independently.The incident pump field is shown to be depleted by two-photon absorption and the THz radiation is shown to be reduced,upon focusing,by free-carrier absorption.The reduction of the generated THz radiation upon tight focusing is explained,provided that one also takes into account diffraction effects from the sub-wavelength THz source.
Jamali, A.; Khaleghi, E.; Gholaminezhad, I.; Nariman-zadeh, N.
2016-05-01
In this paper, a new multi-objective genetic programming (GP) with a diversity preserving mechanism and a real number alteration operator is presented and successfully used for Pareto optimal modelling of some complex non-linear systems using some input-output data. In this study, two different input-output data-sets of a non-linear mathematical model and of an explosive cutting process are considered separately in three-objective optimisation processes. The pertinent conflicting objective functions that have been considered for such Pareto optimisations are namely, training error (TE), prediction error (PE), and the length of tree (complexity of the network) (TL) of the GP models. Such three-objective optimisation implementations leads to some non-dominated choices of GP-type models for both cases representing the trade-offs among those objective functions. Therefore, optimal Pareto fronts of such GP models exhibit the trade-off among the corresponding conflicting objectives and, thus, provide different non-dominated optimal choices of GP-type models. Moreover, the results show that no significant optimality in TE and PE may occur when the TL of the corresponding GP model exceeds some values.
Directory of Open Access Journals (Sweden)
V. K. Bityukov
2016-01-01
Full Text Available Analytical study of the processes of heat conduction is one of the main topics of modern engineering research in engineering, energy, nuclear industry, process chemical, construction, textile, food, geological and other industries. Suffice to say that almost all processes in one degree or another are related to change in the temperature condition and the transfer of warmth. It should also be noted that engineering studies of the kinetics of a range of physical and chemical processes are similar to the problems of stationary and nonstationary heat transfer. These include the processes of diffusions, sedimentation, viscous flow, slowing down the neutrons, flow of fluids through a porous medium, electric fluctuations, adsorption, drying, burning, etc. There are various methods for solving the classical boundary value problems of nonstationary heat conduction and problems of the generalized type: the method of separation of variables (Fourier method method; the continuation method; the works solutions; the Duhamel's method; the integral transformations method; the operating method; the method of green's functions (stationary and non-stationary thermal conductivity; the reflection method (method source. In this paper, based on the consistent application of the Laplace transform on the dimensionless time θ and finite sine integral transformation in the spatial coordinates X and Y solves the problem of unsteady temperature distribution on the mechanism of heat conduction in a parallelepiped with boundary conditions of first kind. As a result we have the analytical solution of the temperature distribution in the parallelepiped to a conductive mode free convection, when one of the side faces of the parallelepiped is maintained at a constant temperature, and the others with the another same constant temperature.
Barros, A. P.; Wilson, A. M.; Miller, D. K.; Tao, J.; Genereux, D. P.; Prat, O.; Petersen, W. A.; Brunsell, N. A.; Petters, M. D.; Duan, Y.
2015-12-01
Using the planet as a study domain and collecting observations over unprecedented ranges of spatial and temporal scales, NASA's EOS (Earth Observing System) program was an agent of transformational change in Earth Sciences over the last thirty years. The remarkable space-time organization and variability of atmospheric and terrestrial moist processes that emerged from the analysis of comprehensive satellite observations provided much impetus to expand the scope of land-atmosphere interaction studies in Hydrology and Hydrometeorology. Consequently, input and output terms in the mass and energy balance equations evolved from being treated as fluxes that can be used as boundary conditions, or forcing, to being viewed as dynamic processes of a coupled system interacting at multiple scales. Measurements of states or fluxes are most useful if together they map, reveal and/or constrain the underlying physical processes and their interactions. This can only be accomplished through an integrated observing system designed to capture the coupled physics, including nonlinear feedbacks and tipping points. Here, we first review and synthesize lessons learned from hydrometeorology studies in the Southern Appalachians and in the Southern Great Plains using both ground-based and satellite observations, physical models and data-assimilation systems. We will specifically focus on mapping and understanding nonlinearity and multiscale memory of rainfall-runoff processes in mountainous regions. It will be shown that beyond technical rigor, variety, quantity and duration of measurements, the utility of observing systems is determined by their interpretive value in the context of physical models to describe the linkages among different observations. Second, we propose a framework for designing science-grade and science-minded process-oriented integrated observing and modeling platforms for hydrometeorological studies.
Reproducing pairs and the continuous nonstationary Gabor transform on LCA groups
Speckbacher, Michael; Balazs, Peter
2015-10-01
In this paper we introduce and investigate the concept of reproducing pairs as a generalization of continuous frames. Reproducing pairs yield a bounded analysis and synthesis process while the frame condition can be omitted at both stages. Moreover, we will investigate certain continuous frames (resp. reproducing pairs) on LCA groups, which can be described as a continuous version of nonstationary Gabor systems and state sufficient conditions for these systems to form a continuous frame (resp. reproducing pair). As a byproduct we identify the structure of the frame operator (resp. resolution operator). We will apply our results to systems generated by a unitary action of a subset of the affine Weyl-Heisenberg group in {L}2({{R}}). This setup will also serve as a nontrivial example of a system for which, whereas continuous frames exist, no dual system with the same structure exists even if we drop the frame property.
Scaling in Non-stationary Time Series II Teen Birth Phenomenon
Ignaccolo, M; Grigolini, P; Hamilton, P; West, B J
2003-01-01
This paper is devoted to the problem of statistical mechanics raised by the analysis of an issue of sociological interest: the teen birth phenomenon. It is expected that these data are characterized by correlated fluctuations, reflecting the cooperative properties of the process. However, the assessment of the anomalous scaling generated by these correlations is made difficult, and ambiguous as well, by the non-stationary nature of the data that show a clear dependence on seasonal periodicity (periodic component) and an average changing slowly in time (slow component), as well. We use the detrending techniques described in the companion paper \\cite{paper1}, to safely remove all the biases and to derive the genuine scaling of the teen birth phenomenon.
Instantaneous Purified Orbit: A New Tool for Analysis of Nonstationary Vibration of Rotor System
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Shi Dongfeng
2001-01-01
Full Text Available In some circumstances, vibration signals of large rotating machinery possess time-varying characteristics to some extent. Traditional diagnosis methods, such as FFT spectrum and orbit diagram, are confronted with a huge challenge to deal with this problem. This work aims at studying the four intrinsic drawbacks of conventional vibration signal processing method and instantaneous purified orbit (IPO on the basis of improved Fourier spectrum (IFS to analyze nonstationary vibration. On account of integration, the benefits of short period Fourier transform (SPFT and regular holospectrum, this method can intuitively reflect vibration characteristics of’a rotor system by means of parameter analysis for corresponding frequency ellipses. Practical examples, such as transient vibration in run-up stages and bistable condition of rotor show that IPO is a powerful tool for diagnosis and analysis of the vibration behavior of rotor systems.
Woźniak, M.
2016-06-02
We study the features of a new mixed integration scheme dedicated to solving the non-stationary variational problems. The scheme is composed of the FEM approximation with respect to the space variable coupled with a 3-leveled time integration scheme with a linearized right-hand side operator. It was applied in solving the Cahn-Hilliard parabolic equation with a nonlinear, fourth-order elliptic part. The second order of the approximation along the time variable was proven. Moreover, the good scalability of the software based on this scheme was confirmed during simulations. We verify the proposed time integration scheme by monitoring the Ginzburg-Landau free energy. The numerical simulations are performed by using a parallel multi-frontal direct solver executed over STAMPEDE Linux cluster. Its scalability was compared to the results of the three direct solvers, including MUMPS, SuperLU and PaSTiX.
Auto-Regressive Models of Non-Stationary Time Series with Finite Length
Institute of Scientific and Technical Information of China (English)
FEI Wanchun; BAI Lun
2005-01-01
To analyze and simulate non-stationary time series with finite length, the statistical characteristics and auto-regressive (AR) models of non-stationary time series with finite length are discussed and studied. A new AR model called the time varying parameter AR model is proposed for solution of non-stationary time series with finite length. The auto-covariances of time series simulated by means of several AR models are analyzed. The result shows that the new AR model can be used to simulate and generate a new time series with the auto-covariance same as the original time series. The size curves of cocoon filaments regarded as non-stationary time series with finite length are experimentally simulated. The simulation results are significantly better than those obtained so far, and illustrate the availability of the time varying parameter AR model. The results are useful for analyzing and simulating non-stationary time series with finite length.
Incremental learning of concept drift in nonstationary environments.
Elwell, Ryan; Polikar, Robi
2011-10-01
We introduce an ensemble of classifiers-based approach for incremental learning of concept drift, characterized by nonstationary environments (NSEs), where the underlying data distributions change over time. The proposed algorithm, named Learn(++). NSE, learns from consecutive batches of data without making any assumptions on the nature or rate of drift; it can learn from such environments that experience constant or variable rate of drift, addition or deletion of concept classes, as well as cyclical drift. The algorithm learns incrementally, as other members of the Learn(++) family of algorithms, that is, without requiring access to previously seen data. Learn(++). NSE trains one new classifier for each batch of data it receives, and combines these classifiers using a dynamically weighted majority voting. The novelty of the approach is in determining the voting weights, based on each classifier's time-adjusted accuracy on current and past environments. This approach allows the algorithm to recognize, and act accordingly, to the changes in underlying data distributions, as well as to a possible reoccurrence of an earlier distribution. We evaluate the algorithm on several synthetic datasets designed to simulate a variety of nonstationary environments, as well as a real-world weather prediction dataset. Comparisons with several other approaches are also included. Results indicate that Learn(++). NSE can track the changing environments very closely, regardless of the type of concept drift. To allow future use, comparison and benchmarking by interested researchers, we also release our data used in this paper.
Sampling design optimisation for rainfall prediction using a non-stationary geostatistical model
Wadoux, Alexandre M. J.-C.; Brus, Dick J.; Rico-Ramirez, Miguel A.; Heuvelink, Gerard B. M.
2017-09-01
The accuracy of spatial predictions of rainfall by merging rain-gauge and radar data is partly determined by the sampling design of the rain-gauge network. Optimising the locations of the rain-gauges may increase the accuracy of the predictions. Existing spatial sampling design optimisation methods are based on minimisation of the spatially averaged prediction error variance under the assumption of intrinsic stationarity. Over the past years, substantial progress has been made to deal with non-stationary spatial processes in kriging. Various well-documented geostatistical models relax the assumption of stationarity in the mean, while recent studies show the importance of considering non-stationarity in the variance for environmental processes occurring in complex landscapes. We optimised the sampling locations of rain-gauges using an extension of the Kriging with External Drift (KED) model for prediction of rainfall fields. The model incorporates both non-stationarity in the mean and in the variance, which are modelled as functions of external covariates such as radar imagery, distance to radar station and radar beam blockage. Spatial predictions are made repeatedly over time, each time recalibrating the model. The space-time averaged KED variance was minimised by Spatial Simulated Annealing (SSA). The methodology was tested using a case study predicting daily rainfall in the north of England for a one-year period. Results show that (i) the proposed non-stationary variance model outperforms the stationary variance model, and (ii) a small but significant decrease of the rainfall prediction error variance is obtained with the optimised rain-gauge network. In particular, it pays off to place rain-gauges at locations where the radar imagery is inaccurate, while keeping the distribution over the study area sufficiently uniform.
Energy Technology Data Exchange (ETDEWEB)
Sayyar-Rodsari, Bijan; Schweiger, Carl; Hartman, Eric
2007-10-07
The difficult problems being tackled in the accelerator community are those that are nonlinear, substantially unmodeled, and vary over time. Such problems are ideal candidates for model-based optimization and control if representative models of the problem can be developed that capture the necessary mathematical relations and remain valid throughout the operation region of the system, and through variations in system dynamics. The goal of this proposal is to develop the methodology and the algorithms for building high-fidelity mathematical representations of complex nonlinear systems via constrained training of combined first-principles and neural network models.
A New Adaptive Square-Root Unscented Kalman Filter for Nonlinear Systems with Additive Noise
Directory of Open Access Journals (Sweden)
Yong Zhou
2015-01-01
Full Text Available The Kalman filter (KF, extended KF, and unscented KF all lack a self-adaptive capacity to deal with system noise. This paper describes a new adaptive filtering approach for nonlinear systems with additive noise. Based on the square-root unscented KF (SRUKF, traditional Maybeck’s estimator is modified and extended to nonlinear systems. The square root of the process noise covariance matrix Q or that of the measurement noise covariance matrix R is estimated straightforwardly. Because positive semidefiniteness of Q or R is guaranteed, several shortcomings of traditional Maybeck’s algorithm are overcome. Thus, the stability and accuracy of the filter are greatly improved. In addition, based on three different nonlinear systems, a new adaptive filtering technique is described in detail. Specifically, simulation results are presented, where the new filter was applied to a highly nonlinear model (i.e., the univariate nonstationary growth model (UNGM. The UNGM is compared with the standard SRUKF to demonstrate its superior filtering performance. The adaptive SRUKF (ASRUKF algorithm can complete direct recursion and calculate the square roots of the variance matrixes of the system state and noise, which ensures the symmetry and nonnegative definiteness of the matrixes and greatly improves the accuracy, stability, and self-adaptability of the filter.
2015-01-01
From the Back Cover: The emphasis throughout the present volume is on the practical application of theoretical mathematical models helping to unravel the underlying mechanisms involved in processes from mathematical physics and biosciences. It has been conceived as a unique collection of abstract methods dealing especially with nonlinear partial differential equations (either stationary or evolutionary) that are applied to understand concrete processes involving some important applications re...
Müller, M. F.; Thompson, S. E.
2016-02-01
The prediction of flow duration curves (FDCs) in ungauged basins remains an important task for hydrologists given the practical relevance of FDCs for water management and infrastructure design. Predicting FDCs in ungauged basins typically requires spatial interpolation of statistical or model parameters. This task is complicated if climate becomes non-stationary, as the prediction challenge now also requires extrapolation through time. In this context, process-based models for FDCs that mechanistically link the streamflow distribution to climate and landscape factors may have an advantage over purely statistical methods to predict FDCs. This study compares a stochastic (process-based) and statistical method for FDC prediction in both stationary and non-stationary contexts, using Nepal as a case study. Under contemporary conditions, both models perform well in predicting FDCs, with Nash-Sutcliffe coefficients above 0.80 in 75 % of the tested catchments. The main drivers of uncertainty differ between the models: parameter interpolation was the main source of error for the statistical model, while violations of the assumptions of the process-based model represented the main source of its error. The process-based approach performed better than the statistical approach in numerical simulations with non-stationary climate drivers. The predictions of the statistical method under non-stationary rainfall conditions were poor if (i) local runoff coefficients were not accurately determined from the gauge network, or (ii) streamflow variability was strongly affected by changes in rainfall. A Monte Carlo analysis shows that the streamflow regimes in catchments characterized by frequent wet-season runoff and a rapid, strongly non-linear hydrologic response are particularly sensitive to changes in rainfall statistics. In these cases, process-based prediction approaches are favored over statistical models.
Directory of Open Access Journals (Sweden)
Meleiro L.A.C.
2000-01-01
Full Text Available Most advanced computer-aided control applications rely on good dynamics process models. The performance of the control system depends on the accuracy of the model used. Typically, such models are developed by conducting off-line identification experiments on the process. These experiments for identification often result in input-output data with small output signal-to-noise ratio, and using these data results in inaccurate model parameter estimates [1]. In this work, a multivariable adaptive self-tuning controller (STC was developed for a biotechnological process application. Due to the difficulties involving the measurements or the excessive amount of variables normally found in industrial process, it is proposed to develop "soft-sensors" which are based fundamentally on artificial neural networks (ANN. A second approach proposed was set in hybrid models, results of the association of deterministic models (which incorporates the available prior knowledge about the process being modeled with artificial neural networks. In this case, kinetic parameters - which are very hard to be accurately determined in real time industrial plants operation - were obtained using ANN predictions. These methods are especially suitable for the identification of time-varying and nonlinear models. This advanced control strategy was applied to a fermentation process to produce ethyl alcohol (ethanol in industrial scale. The reaction rate considered for substratum consumption, cells and ethanol productions are validated with industrial data for typical operating conditions. The results obtained show that the proposed procedure in this work has a great potential for application.
Non-linear dynamics of inlet film thickness during unsteady rolling process
Fu, Kuo; Zang, Yong; Gao, Zhiying; Qin, Qin; Wu, Diping
2016-05-01
The inlet film thickness directly affects film and stress distribution of rolling interfaces. Unsteady factors, such as unsteady back tension, may disturb the inlet film thickness. However, the current models of unsteady inlet film thickness lack unsteady disturbance factors and do not take surface topography into consideration. In this paper, based on the hydrodynamic analysis of inlet zone an unsteady rolling film model which concerns the direction of surface topography is built up. Considering the small fluctuation of inlet angle, absolute reduction, reduction ratio, inlet strip thickness and roll radius as the input variables and the fluctuation of inlet film thickness as the output variable, the non-linear relationship between the input and output is discussed. The discussion results show that there is 180° phase difference between the inlet film thickness and the input variables, such as the fluctuant absolute reduction, the fluctuant reduction ratio and non-uniform inlet strip thickness, but there is no phase difference between unsteady roll radius and the output. The inlet angle, the steady roll radius and the direction of surface topography have significant influence on the fluctuant amplitude of unsteady inlet film thickness. This study proposes an analysis method for unsteady inlet film thickness which takes surface topography and new disturbance factors into consideration.
Lei, Dangyuan
2016-09-01
In the first part of this talk, I will show our experimental investigation on the linear and nonlinear optical properties of metal film-coupled nanosphere monomers and dimers both with nanometric gaps. We have developed a new methodology - polarization resolved spectral decomposition and color decoding to "visualizing" unambiguously the spectral and radiation properties of the complex plasmonic gap modes in these hybrid nanostructures. Single-particle spectroscopic measurements indicate that these hybrid nanostructures can simultaneously enhance several nonlinear optical processes, such as second harmonic generation, two-photon absorption induced luminescence, and hyper-Raman scattering. In the second part, I will show how the polarization state of the emissions from sub-10 nm upconversion nanocrystals (UCNCs) can be modulated when they form a hybrid complex with a gold nanorod (GNR). Our single-particle scattering experiments expose how an interplay between excitation polarization and GNR orientation gives rise to an extraordinary polarized nature of the upconversion emissions from an individual hybrid nanostructure. We support our results by numerical simulations and, using Förster resonance energy transfer theory, we uncover how an overlap between the UCNC emission and GNR extinction bands as well as the mutual orientation between emission and plasmonic dipoles jointly determine the polarization state of the UC emissions.
Prasad, Paras N.
2017-02-01
Chiral control of nonlinear optical functions holds a great promise for a wide range of applications including optical signal processing, bio-sensing and chiral bio-imaging. In chiral polyfluorene thin films, we demonstrated extremely large chiral nonlinearity. The physics of manipulating excitation dynamics for photon transformation will be discussed, along with nanochemistry control of upconversion in hierarchically built organic chromophore coupled-core-multiple shell nanostructures which enable introduce new, organic-inorganic energy transfer routes for broadband light harvesting and increased upconversion efficiency via multistep cascaded energy transfer. We are pursuing the applications of photon conversion technology in IR harvesting for photovoltaics, high contrast bioimaging, photoacoustic imaging, photodynamic therapy, and optogenetics. An important application is in Brain research and Neurophotonics for functional mapping and modulation of brain activities. Another new direction pursued is magnetic field control of light in in a chiral polymer nanocomposite to achieve large magneto-optic coefficient which can enable sensing of extremely weak magnetic field due to brain waves. Finally, we will consider the thought provoking concept of utilizing photons to quantify, through magneto-optics, and augment - through nanoptogenetics, the cognitive states, thus paving the path way to a quantified human paradigm.
Directory of Open Access Journals (Sweden)
J. Azaña
2012-01-01
Full Text Available We review recent work on all-fiber (long-period fiber grating devices for optical pulse shaping, particularly flat-top pulse generation, down to the subpicosecond range and their application for nonlinear switching (demultiplexing of optical time-division multiplexed (OTDM data signals in fiber-optic telecommunication links operating up to 640 Gbit/s. Experiments are presented demonstrating error-free 640-to-10 Gbit/s demultiplexing of the 64 tributary channels using the generated flat-top pulses for temporal gating in a Kerr-effect-based nonlinear optical loop mirror. The use of flat-top pulses has critical benefits in the demultiplexing process, including a significantly increased timing-jitter tolerance (up to ~500 fs, i.e., 30% of the bit period and the associated improvement in the bit-error-rate performance (e.g., with a sensitivity increase of up to ~13 dB as compared with the use of Gaussian-like gating pulses. Long-period fiber grating pulse shapers with reduced polarization dependence are fabricated and successfully used for polarization-independent 640-to-10 Gbit/s demultiplexing experiments.
Directory of Open Access Journals (Sweden)
Daniel C Medina
Full Text Available BACKGROUND: Much of the developing world, particularly sub-Saharan Africa, exhibits high levels of morbidity and mortality associated with diarrhea, acute respiratory infection, and malaria. With the increasing awareness that the aforementioned infectious diseases impose an enormous burden on developing countries, public health programs therein could benefit from parsimonious general-purpose forecasting methods to enhance infectious disease intervention. Unfortunately, these disease time-series often i suffer from non-stationarity; ii exhibit large inter-annual plus seasonal fluctuations; and, iii require disease-specific tailoring of forecasting methods. METHODOLOGY/PRINCIPAL FINDINGS: In this longitudinal retrospective (01/1996-06/2004 investigation, diarrhea, acute respiratory infection of the lower tract, and malaria consultation time-series are fitted with a general-purpose econometric method, namely the multiplicative Holt-Winters, to produce contemporaneous on-line forecasts for the district of Niono, Mali. This method accommodates seasonal, as well as inter-annual, fluctuations and produces reasonably accurate median 2- and 3-month horizon forecasts for these non-stationary time-series, i.e., 92% of the 24 time-series forecasts generated (2 forecast horizons, 3 diseases, and 4 age categories = 24 time-series forecasts have mean absolute percentage errors circa 25%. CONCLUSIONS/SIGNIFICANCE: The multiplicative Holt-Winters forecasting method: i performs well across diseases with dramatically distinct transmission modes and hence it is a strong general-purpose forecasting method candidate for non-stationary epidemiological time-series; ii obliquely captures prior non-linear interactions between climate and the aforementioned disease dynamics thus, obviating the need for more complex disease-specific climate-based parametric forecasting methods in the district of Niono; furthermore, iii readily decomposes time-series into seasonal
Shi, Huaitao; Liu, Jianchang; Wu, Yuhou; Zhang, Ke; Zhang, Lixiu; Xue, Peng
2016-04-01
It is pretty significant for fault diagnosis timely and accurately to improve the dependability of industrial processes. In this study, fault diagnosis of nonlinear and large-scale processes by variable-weighted kernel Fisher discriminant analysis (KFDA) based on improved biogeography-based optimisation (IBBO) is proposed, referred to as IBBO-KFDA, where IBBO is used to determine the parameters of variable-weighted KFDA, and variable-weighted KFDA is used to solve the multi-classification overlapping problem. The main contributions of this work are four-fold to further improve the performance of KFDA for fault diagnosis. First, a nonlinear fault diagnosis approach with variable-weighted KFDA is developed for maximising separation between the overlapping fault samples. Second, kernel parameters and features selection of variable-weighted KFDA are simultaneously optimised using IBBO. Finally, a single fitness function that combines erroneous diagnosis rate with feature cost is created, a novel mixed kernel function is introduced to improve the classification capability in the feature space and diagnosis accuracy of the IBBO-KFDA, and serves as the target function in the optimisation problem. Moreover, an IBBO approach is developed to obtain the better quality of solution and faster convergence speed. On the one hand, the proposed IBBO-KFDA method is first used on Tennessee Eastman process benchmark data sets to validate the feasibility and efficiency. On the other hand, IBBO-KFDA is applied to diagnose faults of automation gauge control system. Simulation results demonstrate that IBBO-KFDA can obtain better kernel parameters and feature vectors with a lower computing cost, higher diagnosis accuracy and a better real-time capacity.
Nonlinear Time Series Analysis in Earth Sciences - Potentials and Pitfalls
Kurths, Jürgen; Donges, Jonathan F.; Donner, Reik V.; Marwan, Norbert; Zou, Yong
2010-05-01
The application of methods of nonlinear time series analysis has a rich tradition in Earth sciences and has enabled substantially new insights into various complex processes there. However, some approaches and findings have been controversially discussed over the last decades. One reason is that they are often bases on strong restrictions and their violation may lead to pitfalls and misinterpretations. Here, we discuss three general concepts of nonlinear dynamics and statistical physics, synchronization, recurrence and complex networks and explain how to use them for data analysis. We show that the corresponding methods can be applied even to rather short and non-stationary data which are typical in Earth sciences. References Marwan, N., Romano, M., Thiel, M., Kurths, J.: Recurrence plots for the analysis of complex systems, Physics Reports 438, 237-329 (2007) Arenas, A., Diaz-Guilera, A., Kurths, J., Moreno, Y., Zhou, C.: Synchronization in complex networks, Physics Reports 469, 93-153 (2008) Marwan, N., Donges, J.F., Zou, Y., Donner, R. and Kurths, J., Phys. Lett. A 373, 4246 (2009) Donges, J.F., Zou, Y., Marwan, N. and Kurths, J. Europhys. Lett. 87, 48007 (2009) Donner, R., Zou, Y., Donges, J.F., Marwan, N. and Kurths, J., Phys. Rev. E 81, 015101(R) (2010)
Shortell, Matthew P; Jaatinen, Esa A; Chang, Jin; Waclawik, Eric R
2014-03-24
We report a new approach that uses the single beam Z-scan technique, to discriminate between excited state absorption (ESA) and two and three photon nonlinear absorption. By measuring the apparent delay or advance of the pulse in reaching the detector, the nonlinear absorption can be unambiguously identified as either instantaneous or transient. The simple method does not require a large range of input fluences or sophisticated pulse-probe experimental apparatus. The technique is easily extended to any absorption process dependent on pulse width and to nonlinear refraction measurements. We demonstrate in particular, that the large nonlinear absorption in ZnO nanocones when exposed to nanosecond 532 nm pulses, is due mostly to ESA, not pure two-photon absorption.