The Experts below are selected from a list of 108 Experts worldwide ranked by ideXlab platform
Peter Macmillan - One of the best experts on this subject based on the ideXlab platform.
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Structure, Term PREMIA AND SURVEY-BASED EXPECTATIONS*
2016Co-Authors: Ronald Macdonald, Peter MacmillanAbstract:In this paper UK disaggregate survey data of expected future interest rates are used to test the expectations model of the Term Structure of interest rates at the short end of the maturity spectrum. In the aggregate, the expectations model is rejected, and both time-varying Term premia and expected interest rate changes are demonstrated to be important in explaining the slope of the yield curve. Within the aggregate data, however, we demonstrate that there are some differences with respect to the views of the Term Structure held. For example, for some individuals the pure expectations model cannot be rejected. The expectations model (EM) of the Term Structure of interest rates is often the model that academics and newspaper commentators first reach to when asked for their views about the future course of interest rates. It has also, without doubt, been the most widely tested model of the Term Structure. However, much of the empirical evidence (particularly for the United States) rejects the model as an explanation for the slope of the yield curve.1 Despite this, the EM seems to have an enduring popularity as a benchmark model of the deTermination of relative interest rates: as Shiller et al. (I 983) suggest, just like the cat in the Tom and Jerry cartoons the EM seems to gain a new lease of life after each exposure to real world data. One problem, however, with many of the tests of the EM is that they are testing a joint hypothesis that expectations conform to some particular view, such as rationality, and the assumption about the yield gap implied by the EM. A rejection of this joint hypothesis may, therefore, be due to a failure of the actual model, a failure of the expectational assumption or both. One particularly popular explanation for the rejection lies in the existence of a time-varying Term premium (see, inter alia, Startz, 1982;
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On the expectations view of the Term Structure, Term premia and survey-based expectations
The Economic Journal, 1994Co-Authors: Ronald Macdonald, Peter MacmillanAbstract:In this paper UK disaggregate survey data of expected future interest rates are used to test the expectations model of the Term Structure of interest rates at the short end of the maturity spectrum. In the aggregate, the expectations model is rejected, and both time-varying Term premia and expected interest rate changes are demonstrated to be important in explaining the slope of the yield curve. Within the aggregate data, however, we demonstrate that there are some differences with respect to the views of the Term Structure held. For example, for some individuals the pure expectations model cannot be rejected.
Tie Zhang - One of the best experts on this subject based on the ideXlab platform.
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adaptive neural network finite time control for uncertain robotic manipulators
Journal of Intelligent and Robotic Systems, 2014Co-Authors: Haitao Liu, Tie ZhangAbstract:An adaptive neural network finite-time controller (NNFTC) for a class of uncertain nonlinear systems is proposed by using the backstepping method, which employs an adaptive neural network (NN) system to approximate the Structure uncertainties and uses a variable Structure Term to compensate the approximation errors, thus improving the robustness of the system to external disturbances. The controller is then applied to uncertain robotic manipulators, with a control objective of driving the system state to the original equilibrium point. It is proved that the closed-loop system is finite-time stable. Moreover, simulated and experimental results indicate that the proposed NNFTC is effective and robust.
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neural network based robust finite time control for robotic manipulators considering actuator dynamics
Robotics and Computer-integrated Manufacturing, 2013Co-Authors: Haitao Liu, Tie ZhangAbstract:A novel neural network-based robust finite-time control strategy is proposed for the trajectory tracking of robotic manipulators with Structured and unStructured uncertainties, in which the actuator dynamics is fully considered. The controller, which possesses finite-time convergence and strong robustness, consists of two parts, namely a neural network for approximating the nonlinear uncertainty function and a modified variable Structure Term for eliminating the approximate error and guaranteeing the finite-time convergence. According to the analysis based on the Lyapunov theory and the relative finite-time stability theory, the neural network is asymptotically convergent and the controlled robotic system is finite time stable. The proposed controller is then verified on a two-link robotic manipulator by simulations and experiments, with satisfactory control performance being obtained even in the presence of various uncertainties and external disturbances.
Ronald Macdonald - One of the best experts on this subject based on the ideXlab platform.
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Structure, Term PREMIA AND SURVEY-BASED EXPECTATIONS*
2016Co-Authors: Ronald Macdonald, Peter MacmillanAbstract:In this paper UK disaggregate survey data of expected future interest rates are used to test the expectations model of the Term Structure of interest rates at the short end of the maturity spectrum. In the aggregate, the expectations model is rejected, and both time-varying Term premia and expected interest rate changes are demonstrated to be important in explaining the slope of the yield curve. Within the aggregate data, however, we demonstrate that there are some differences with respect to the views of the Term Structure held. For example, for some individuals the pure expectations model cannot be rejected. The expectations model (EM) of the Term Structure of interest rates is often the model that academics and newspaper commentators first reach to when asked for their views about the future course of interest rates. It has also, without doubt, been the most widely tested model of the Term Structure. However, much of the empirical evidence (particularly for the United States) rejects the model as an explanation for the slope of the yield curve.1 Despite this, the EM seems to have an enduring popularity as a benchmark model of the deTermination of relative interest rates: as Shiller et al. (I 983) suggest, just like the cat in the Tom and Jerry cartoons the EM seems to gain a new lease of life after each exposure to real world data. One problem, however, with many of the tests of the EM is that they are testing a joint hypothesis that expectations conform to some particular view, such as rationality, and the assumption about the yield gap implied by the EM. A rejection of this joint hypothesis may, therefore, be due to a failure of the actual model, a failure of the expectational assumption or both. One particularly popular explanation for the rejection lies in the existence of a time-varying Term premium (see, inter alia, Startz, 1982;
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On the expectations view of the Term Structure, Term premia and survey-based expectations
The Economic Journal, 1994Co-Authors: Ronald Macdonald, Peter MacmillanAbstract:In this paper UK disaggregate survey data of expected future interest rates are used to test the expectations model of the Term Structure of interest rates at the short end of the maturity spectrum. In the aggregate, the expectations model is rejected, and both time-varying Term premia and expected interest rate changes are demonstrated to be important in explaining the slope of the yield curve. Within the aggregate data, however, we demonstrate that there are some differences with respect to the views of the Term Structure held. For example, for some individuals the pure expectations model cannot be rejected.
Haitao Liu - One of the best experts on this subject based on the ideXlab platform.
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adaptive neural network finite time control for uncertain robotic manipulators
Journal of Intelligent and Robotic Systems, 2014Co-Authors: Haitao Liu, Tie ZhangAbstract:An adaptive neural network finite-time controller (NNFTC) for a class of uncertain nonlinear systems is proposed by using the backstepping method, which employs an adaptive neural network (NN) system to approximate the Structure uncertainties and uses a variable Structure Term to compensate the approximation errors, thus improving the robustness of the system to external disturbances. The controller is then applied to uncertain robotic manipulators, with a control objective of driving the system state to the original equilibrium point. It is proved that the closed-loop system is finite-time stable. Moreover, simulated and experimental results indicate that the proposed NNFTC is effective and robust.
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neural network based robust finite time control for robotic manipulators considering actuator dynamics
Robotics and Computer-integrated Manufacturing, 2013Co-Authors: Haitao Liu, Tie ZhangAbstract:A novel neural network-based robust finite-time control strategy is proposed for the trajectory tracking of robotic manipulators with Structured and unStructured uncertainties, in which the actuator dynamics is fully considered. The controller, which possesses finite-time convergence and strong robustness, consists of two parts, namely a neural network for approximating the nonlinear uncertainty function and a modified variable Structure Term for eliminating the approximate error and guaranteeing the finite-time convergence. According to the analysis based on the Lyapunov theory and the relative finite-time stability theory, the neural network is asymptotically convergent and the controlled robotic system is finite time stable. The proposed controller is then verified on a two-link robotic manipulator by simulations and experiments, with satisfactory control performance being obtained even in the presence of various uncertainties and external disturbances.
A Foti - One of the best experts on this subject based on the ideXlab platform.
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heavy ion double charge exchange reactions a tool toward 0 nu beta beta nuclear matrix elements
European Physical Journal A, 2015Co-Authors: F Cappuzzello, M Cavallaro, C Agodi, M Ondi, D Carbone, A Cunsolo, A FotiAbstract:The knowledge of the nuclear matrix elements for the neutrinoless double beta decay is fundamental for neutrino physics. In this paper, an innovative technique to extract information on the nuclear matrix elements by measuring the cross section of a double charge exchange nuclear reaction is proposed. The basic point is that the initial- and final-state wave functions in the two processes are the same and the transition operators are similar. The double charge exchange cross sections can be factorized in a nuclear Structure Term containing the matrix elements and a nuclear reaction factor. First pioneering experimental results for the 40Ca(18O,18Ne)40Ar reaction at 270 MeV incident energy show that such cross section factorization reasonably holds for the crucial 0+ \( \rightarrow\) 0+ transition to 40Args, at least at very forward angles.
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heavy ion double charge exchange reactions a tool towards 0v b eta b eta nuclear matrix elements
arXiv: Nuclear Experiment, 2015Co-Authors: F Cappuzzello, M Cavallaro, C Agodi, D Carbone, A Cunsolo, A FotiAbstract:The knowledge of the nuclear matrix elements for the neutrinoless double beta decay is fundamental for neutrino physics. In this paper, an innovative technique to extract information on the nuclear matrix elements by measuring the cross section of a double charge exchange nuclear reaction is proposed. The basic point is that the initial and final state wave functions in the two processes are the same and the transition operators are similar. The double charge exchange cross sections can be factorized in a nuclear Structure Term containing the matrix elements and a nuclear reaction factor. First pioneering experimental results for the 40Ca(18O,18Ne)40Ar reaction at 270 MeV incident energy show that such cross section factorization reasonably holds for the crucial 0+ --> 0+ transition to 40Args, at least at very forward angles.
