Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 317 for “"Squared Error"”.
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Improved Estimators Under Squared Error Loss (Stein Estimator, Decision Theory, Empirical Bayes, Quadratic, Robust Estimation)
… (1964) estimator or an improved estimator under squared error loss has been done with the assumption of independently identically distributed normal errors.
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Quantization for Noisy Channels Using Structured Codes
… vector quantizers with respect to the mean squared error distortion criterion are derived for both noiseless and noisy discrete memoryless channels.
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Improving Survey Methodology Through Matrix Sampling Design, Integrating Statistical Review Into Data Collection, and Synthetic Estimation Evaluation
… surveys in such a way that non-sampling error attributed to data collection is minimized. This proposed methodology requires the inclusion of the statistician in the data editing process during data collection. We implemented the structured procedure during the collection of household …
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Modelling of Wall Pressure Fluctuations Induced by Turbulent Boundary Layer Flow
… by Goody and Smol'yakov have the lowest mean squared error when predicting the power spectral density for wind tunnel experiments. The Rackl and Weston model has the lowest mean squared error when predicting the power spectral density for flight test data. Current advancements in power …
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Model comparison and assessment by cross validation
… repeated and averaged CV and double CV. The mean squared errors of the CV strategies in estimating the best predictive performance are illustrated by using simulated and real data examples. The results show that repeated and averaged CV is a good strategy and outperforms the other two CV …
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Quantum Detector and Process Tomography: Algorithm Design and Optimisation
… based on the minimum upper bound of the mean squared error (UMSE) and the maximum robustness. We establish the lower bounds of the UMSE and the condition number for the probe states, and provide concrete examples that can achieve these lower bounds. In order to enhance the estimation …
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Hybrid Electric Power System Validation through Parameter Optimization
… For the constant current discharge, the mean squared error between measured and simulated data was 0.26 volts for the terminal voltage and 6.07e-4 (%) for state of charge. For the extended variable current discharge, the mean squared error between measured and simulated data was 0.21 volts for …
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Design and fabrication of force sensing robotic foot utilizing the volumetric displacement of a hyperelastic polymer
… forces in the Z-axis up to 80 N with a root mean squared error of 6% but little information about shear forces in the X an Y-axis. The second iteration demonstrates an ability to pick up the presence and direction of shear forces up to 40 N but with a root mean squared error of 70%. This project …
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Online Parameter Adaptation of LQR Controllers via RLS for Prosthetic Joint Control: Experimental Validation on a Quanser Qube-Servo 2 Platform
… for Qube 1 and Qube 2 as follows: mean squared error (MSE) by 36.2% and 69.4%, root mean squared error (RMSE) by 20.1% and 44.7%, mean absolute error (MAE) by 25.0% and 59.8%, and mean absolute percentage error (MAPE) by 25.0% and 59.8%, respectively. The Adaptive LQR also exhibited …
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Machine Learning Methods for Super-Resolution in Sparse Sensor Arrays
… and the network is trained to minimize the squared error between the network output and the normalized log-magnitude of the large aperture array signal in its Fourier Transform domain. In general, given signals from two sets of 12-element sub-arrays, the neural network can reproduce results …
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Monte Carlo methods for the estimation of value-at-risk and related risk measures
… improve efficiency in the sense of reducing mean-squared error.
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Effect of upper stem diameter and errors of measurement on the accuracy of volume equations
… bias ranged from 0.85% for DBH measurement errors to 2.88% for total height measurement errors. Relative standard deviation ranged from 1.52% to 10.13% for DBH and total height errors respectively. When both bias and precision ( standard deviation ) were considered jointly, the relative root …
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Sequential robust response surface strategy
… J<sub>PCA</sub>, considers the average mean squared error of prediction for a first order model over a region where the detection capabilities of the lack of fit test are not strong. J<sub>PCMAX</sub> considers the maximum mean squared error of prediction over the region where the detection …
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Experimental and Prediction Approaches to Determine Dissociation Constants (pKa) of Amines
… regression coefficient was 0.99424 and mean squared error for training, validation and test process was 2.20E-05, 0.0094 and 0.0078, respectively. To compromise the flexibility of the ANN model, the other architecture of 6-5-7- 1 which reduced density and viscosity as inputs was selected, and …
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State Estimation with Unconventional and Networked Measurements
… forms of the batch linear minimum mean-squared error (LMMSE) estimator are obtained to reduce the computational complexity. Inspired by the estimation with quantized measurements developed by Curry [28], under a Gaussian assumption, the minimum mean-squared error (MMSE) state estimator …
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Some Improvement on Convergence Rates of Kernel Density Estimator
… properties such as bias, variance and mean squared error are investigated for this estimator and comparisons with ordinary kernel density estimator and location-scale kernel density estimator are made. Compared with the ordinary density estimator, this estimator has reduced bias and mean …
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Analysis of Machine Learning Algorithms for Time Series Prediction
… was carried out using the Mean Absolute Error (MAE), the Mean Squared Error (MSE), the Root Mean Squared Error (RMSE) and the Mean Absolute Scaled Error (MASE). The second experiment focused on evaluating the stability and robustness of the optimal models identified in the first …
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Feedforward temperature control using a heat flux microsensor
… response to the disturbance. The integral of the squared error between the setpoint and actual temperature was reduced by approximately 90 percent by the addition of feedforward control to the feedback control. The maximum temperature deviation from the setpoint was also reduced by 70 percent with …
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A Naive, Robust and Stable State Estimate
… the filters is carried out using the usual mean squared error. The filters to be included are the classic Kalman filter, Krein space Kalman, two adjustments to the Krein filter with input modeling and a second uncertainty parameter, a newly developed filter called the Naive filter, bias corrected …
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A Unified Framework for Image Modeling and Estimation Using Measurement Constraints
… terms of both perceptual quality as well as mean-squared error over classical approaches such as adaptive Wiener filtering. Under appropriate conditions, a variety of classical wavelet-domain image models and denoising algorithms are shown to be subsumed by the proposed multiple-domain maxent …
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