Choice of Input Signals for Optimal Estimation
Optimal Bandwidth Choice for Interval Estimation in GMM Regression
... bandwidth choice rule for M that optimizes the coverage accuracy of interval estimators in the context of linear GMM ...The optimal bandwidth balances the asymptotic variance with the asymptotic bias of the ...
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Input price risk and optimal timing of energy investment: choice between fossil- and biofuels
... investor must choose both the timing of the investment and the type of the plant. Methodologically the analysis is based on the theory of irreversible investment under uncertainty (see Dixit and Pindyck, 1994, for a ...
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Input estimation for drug discovery using optimal control and Markov chain Monte Carlo approaches
... range 0.2–0.5. The Markov chains were initialised to the MAP estimate given by the optimal-control techniques. 15,000 samples were drawn for each analysis. Obtaining MAP estimates is in general computationally ...
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Micro level Estimation of Optimal Consumption Choice with Intertemporal Nonseparability in Preferences and Measurement Errors
... are given by, for example, C t − αC t − 1 . Two related points motivate the choice of the multiplicative specification. First, individual consumption data are more volatile than aggregate consumption data. As a ...
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Micro-level Estimation of Optimal Consumption Choice with Intertemporal Nonseparability in Preferences and Measurement Errors
... are given by, for example, C t −αC t−1 . Two related points motivate the choice of the multiplicative specification. First, individual consumption data are more volatile than aggregate consumption data. As a ...
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Optimal processing of Doppler signals in OCT
... f ' z arg max FT[ z ] / K (2) Zero padding of the input series Γ j (z) is used to get a finer grading for the discrete velocity values resulting from this calculation. Some authors have called this method the ...
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Variable Window Length Applied To A Modified Hanning Filter For Optimal Amplitude Estimation Of Power Systems Signals
... amplitude estimation, there are a considerable number of algorithm such as the least squares and weighted least squares methods[2], it is also possible to rely on the filterbank approach such as the recursive DFT, ...
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Sequential estimation of intrinsic activity and synaptic input in single neurons by particle filtering with optimal importance density
... Pau Closas 1* and Antoni Guillamon 2 Abstract This paper deals with the problem of inferring the signals and parameters that cause neural activity to occur. The ultimate challenge being to unveil brain’s ...
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A Spline Framework for Optimal Representation of Semiperiodic Signals
... proper choice of threshold, RPA results in initial knot locations that serve as a good starting point for subsequent ...interpolant choice is very important to ensure the goals of a given application of the ...
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Optimal Ownership Structures in the Presence of Investment Signals
... be divided into two groups, investment that generally decreases the produc- tion costs of a class of inputs and investment that is solely oriented at D’s needs, i.e. investment that decreases the costs of producing the ...
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Optimal input design for reduction of parameter correlations
... IV. C ONCLUSION AND FUTRUE WORK In this paper, a new criterion has been proposed which linearly combines the A-optimality criterion and the ME- optimality together to acquire the experimental data with satisfactory ...
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Optimal input design for reduction of parameter correlations
... IV. C ONCLUSION AND FUTRUE WORK In this paper, a new criterion has been proposed which linearly combines the A-optimality criterion and the ME- optimality together to acquire the experimental data with satisfactory ...
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Effective joint DOA DOD estimation for the coexistence of uncorrelated and coherent signals in massive multi input multi output array systems
... angle estimation with respect to tar- get localization will be dramatically improved due to its high resolution of spatial ...angle estimation should be considered ...
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Applications of Optimal Subspace Estimation
... Within the beamforming application in Chapter 2 there may be further pro- cessing desired where OSE may still be desirable regardless of common performance metrics. It was shown in Chapter 2 that the OSE algorithm easily ...
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Optimal choice of electoral preference data
... The estimation of the effect of x 1 thus requires party-specific parameters with respect to some reference category, ...The estimation of the effects of x 2 and x 3 , however, can be performed for all ...
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Matching estimators and optimal bandwidth choice
... Matching estimators attempt to estimate an expected value for a particular population, by using data from a different pop- ulation and adjusting nonparametrically for the different distri- butions of covariates in these ...
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Nonlinear Effects of the LMS Adaptive Predictor for Chirped Input Signals
... narrowband input signals embedded in AWGN, the LMS adaptive predictor can outperform the finite-length Wiener predictor in steady-state ...of input signal and adaptive filter parameters, and it is ...
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DOA Estimation and Blind Separation of Coherent Signals
... of input SNR and output SINR CONCLUSION On the research of DOA estimation and blind separation algorithms of coherent sources, a new separation algorithm based on Toeplitz matrix reconstruction is proposed ...
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On polyhedral estimation of signals via indirect observations
... Abstract: We consider the problem of recovering linear image of unknown signal belonging to a given convex compact signal set from noisy observa- tion of another linear image of the signal. We develop a simple generic ...
Improved moment scaling estimation for multifractal signals
... In Fig. 4, the multifractal parameter C 1 and the resolution level of the observations n dat are kept fixed. We have made similar analyses with different values of these parameters. The results (not shown) are ...
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