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Weighted Dynamic Time Warping for Time Series
International Journal of Bifurcation and Chaos, 2023Recurrence network is a typical time series analysis method. However, irregular sampling may overshadow the dynamic features characterized by traditional recurrence network method, which makes the method ineffective. This paper introduces dynamic time warping method to determine the distance between time series segments.
Guangyu Yang, Shuyan Xia
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IEEE transactions on industrial electronics (1982. Print), 2019
Series connection of individual semiconductors is an effective way to achieve higher voltage switches. However, the inherent unequal dynamic voltage sharing problem needs to be solved, even when well-matched gate drivers and semiconductors are used.
A. Marzoughi, R. Burgos, D. Boroyevich
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Series connection of individual semiconductors is an effective way to achieve higher voltage switches. However, the inherent unequal dynamic voltage sharing problem needs to be solved, even when well-matched gate drivers and semiconductors are used.
A. Marzoughi, R. Burgos, D. Boroyevich
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Generalized series dynamic imaging
Proceedings International Workshop on Medical Imaging and Augmented Reality, 2002Many imaging applications require the acquisition of a time series of images. In conventional Fourier transform-based imaging methods, each of these images is acquired independently. As a result, the temporal resolution possible is limited by the number of data points collected for each data set, or one often was to sacrifice spatial resolution for ...
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Dynamical Realizations of Finite Volterra Series
SIAM Journal on Control and Optimization, 1980In this paper, realizations of finite Volterra series are viewed as nonlinear analytic input–output systems, with state space described by an analytic manifold. For a minimal realization guaranteed by H. J. Sussmann, the state space, which is unique up to diffeomorphism, is shown to have the homogeneous space structure of a nilmanifold, the quotient of
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Dynamics from multivariate time series
Physica D: Nonlinear Phenomena, 1998zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Cao, Lianguye +2 more
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Minimum cost dynamic flows: The series-parallel case
Networks, 1995AbstractA dynamic network consists of a directed graph with capacities, costs, and integral transit times on the arcs. In the minimum‐cost dynamic flow problem (MCDFP), the goal is to compute, for a given dynamic network with source s, sink t, and two integers v and T, a feasible dynamic flow from s to t of value v, obeying the time bound T, and having
Klinz, Bettina, Woeginger, Gerhard
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Time Series and Dynamic Models
2004Abstract This chapter treats the modelling of variables that are observed sequentially over time. The main focus is on univariate time series models for a single economic variable, but we also discuss regression models with lags and multivariate time series models.
Christiaan Heij +4 more
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Dynamics extraction in multivariate biomedical time series
Biological Cybernetics, 1998A nonlinear analysis of the underlying dynamics of a biomedical time series is proposed by means of a multi-dimensional testing of nonlinear Markovian hypotheses in the observed time series. The observed dynamics of the original N-dimensional biomedical time series is tested against a hierarchy of null hypotheses corresponding to N-dimensional ...
Silipo, R. +3 more
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Side-chain dynamics analysis of KE07 series
Computational Biology and Chemistry, 2016The significant improvement of KE07 series in catalytic activities shows the great success of computational design approaches combined with directed evolution in protein design. Understanding the protein dynamics in the evolutionary optimization process of computationally designed enzyme will provide profound implication to study enzyme function and ...
Xin, Geng, Jiaogen, Zhou, Jihong, Guan
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2004
Abstract This chapter presents the finite sample analysis of the time series models used in economics and finance. It considers the autoregressive model (AR), AR with regressors, and autoregressive moving average models with regressors. The exact and approximate moments, as well as distributions of the estimators of the lag coefficients ...
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Abstract This chapter presents the finite sample analysis of the time series models used in economics and finance. It considers the autoregressive model (AR), AR with regressors, and autoregressive moving average models with regressors. The exact and approximate moments, as well as distributions of the estimators of the lag coefficients ...
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