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The resulting calibration curves for strength estimation were compared with others from previous published literature.
The results obtained with the proposed ultrasound data acquisition and strain estimation were compared with results from a classic approach and illustrate the improvement produced by considering the medium's local displacements in elevation, with notably an increase in the mean correlation coefficients achieved.
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In order to demonstrate the quality of the new frequency estimator in each analyzed case, its estimation was compared with the responses obtained by four other methods, in terms of performance indices based on the estimation of transitory error and response convergence time.
Finally, the LR-DM estimation is compared with the stratum-wise estimation.
The SigShrink estimation is compared with that of the SURELET "sum of DOGs" (Derivatives Of Gaussian).
The analytical estimation is compared with the Lagrangian model and FE method for validation.
The efficacy of this type of network in function learning and estimation is compared with ANNs.
The MSE performances of parameter estimation are compared with the CRB bound and are shown in the simulation results.
The adsorption behavior of model systems n-C4H9OH+NaCl (A) and 1-AdOH+NaCl (B) is analyzed and the results of estimation are compared with experimental data.
When disparity estimation is performed for the macroblock, the rate-distortion cost of the disparity estimation is compared with that of motion estimation in order to select the best block mode and vectors.
Performance of continuous time Bayesian network classifiers learned when combining conditional log-likelihood scoring and Bayesian parameter estimation are compared with that achieved by continuous time Bayesian network classifiers when learning is based on marginal log-likelihood scoring and to that achieved by dynamic Bayesian network classifiers.
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