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 394 for “"Mean square error"”.
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Minimum mean square error without coding.
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering, 1970
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Information theoretic bounds for distributed computation
… the initial values in the network, so that the mean square error in the estimate is within a prescribed interval. Here, the nodes do not know the distribution of the source, but have unlimited computation power to run whatever algorithm needed to ensure the mean square error criterion. The …
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Using a gimbal to calibrate an inertial measurement unit
… are found to track the pitch angle with a mean-square-error of 1.7427 degrees, and the roll angle with a mean-square-error of 3.1387 degrees. The novel outcome of this thesis is that it defines a technique for calibrating IMUs with component sensors that need not be orthogonal in placement.
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Utilizing Machine Learning Methods for Usability Evaluation in Learning Management Systems
… Forest produces the best performance of average mean square error and root mean square error among machine learning algorithms. The results are promising, though there are alternatives for improvements for better performance of the System Usability Scale and UseLearn scores prediction. This …
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Estimation and forecasting team strength dynamics in football : investigation into structural breaks
… to more recent matches. This weighting scheme means that a pseudo-likelihood is used to estimate strength parameters. A rolling window approach is used to obtain a time series for the attack and defence strengths of teams in order to investigate the presence of structural breaks. We show that …
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ENHANCING POLYMER INFORMATICS: A STUDY ON THE IMPACT OF FINGERPRINTING METHODS AND MACHINE LEARNING MODELS
… fingerprinting consistently yielded lower root mean square error (RMSE) and normalized root mean square error (NRMSE) values than Morgan fingerprinting, indicating a more accurate representation of polymer structure. The work demonstrates the significant potential of multi-task learning and …
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Coding and Equalization for Radio Channels
… sequence estimation (RSSE), and combined minimum-mean-square error decision-feedback equalization (MMSE-DFE) and Viterbi decoding.
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Parametric survival models with interval censored data in determining prognostic factors of patients of lung cancer
… Standard estimation values such as, the mean square error (MSE), root mean square error (RMSE), mean absolute error (MAE), and mean asolute percentage error (MAPE) were employed in comparing different distributions and number of sample sizes. Besides, Akaike Information Criterion (AIC), …
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Genetic and Genetic-Feeding Regimen Interaction Effects on Lactation, Growth and Carcass Traits in Dairy Cattle
… using simulation. Estimated generalized least-squares regression of body-weight on age was a better estimator of ADG (gave lower mean square error of ADG and variance components) than the usual estimator, which itself was better than ordinary least-squares regression.
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Application of fuzzy linear regression models for predicting tumor size of colorectal cancer in Malaysia's Hospital
… best model by using statistical measurements of mean square error (MSE) and root mean square error (RMSE). The results showed that the fuzzy linear regression with symmetric parameter (Zolfaghari) was found to be the best model, having the lowest MSE and RMSE value by 98.21 and 9.91. Hence, the …
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A case study of weather research and forecasting model over the Midwest USA
… better temperature (0.35 K decrease in hourly mean bias and 0.26 K decrease in hourly root mean square error), pressure (4.3 Pa decrease in hourly mean bias and 3.91 K decrease in hourly root mean square error) and relative humidity (1.44 % decrease in hourly mean bias and 1.76 % decrease in …
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Optimal entropy estimation on large alphabet: fundamental limits and fast algorithms
… n independent samples. We obtain the minimax mean- square error within universal multiplicative constant factors if n exceeds a constant factor of k/log(k); otherwise there exists no consistent estimator. This refines the recent result of Valiant and Valiant (2011) that the mini- mal sample …
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Modeling the temperature response of small rivers to land cover changes using satellite-based spatial data
… Estimation) had a median validation Root Mean Square Error across gages of about 1.7 K. Building on the outputs from this model as well as validation against paired stream temperature gages, a second machine learning model was developed to predict the relationship between longitudinal …
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Adaptive Channel Estimation for Turbo Decoding
… we re-estimate the channel and the minimum mean square error (m.m.s.e.) and further update the channel reliability factor and decision variables at each iteration. Simulations show that signal to noise (SNR) gain is improved by up to about 1dB at bit error probability of 3.5×10-4.
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Switching adaptive filter structures for improved performance
… in order to produce fast convergence and low mean Square error (MSE). The switching system employs two adaptive filters for two different tasks; one is intended to yield fast convergence, and logically called the "fast convergence structure", while the other is intended to give small MSE, and …
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Comparison of GPS Point Selection Methods for GIS Area Measurement of Small Jurisdictional Wetlands
… area calculation. Analysis of variance and Root Mean Square Error analyses determine that the transect method is an inferior point selection method in terms of accuracy and efficiency.
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Two stages hybrid model of fuzzy linear regression with support vector machines for colorectal cancer
… cancer data. Other than that, the parameter, error and explanation of the five procedures to both new models were included. These models applying five statistical models such as multiple linear regression, fuzzy linear regression, fuzzy linear regression with symmetric parameter, fuzzy linear …
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Differential Privacy and Opacity for Positive Linear Systems and Observers
… present explicit formulae for the bias and the mean square error of the mechanisms constructed. We derive two results showing that bias is unavoidable for both approaches. Forpost-processing with a ramp function, we determine the optimal such function that minimises the worst case bias. We also …
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A new estimation procedure for response surface models
… a response which will have a smaller integrated mean square error than existing procedures. In this work another such attempt is made by introducing a shrinkage procedure. Suppose the true functional relationship between a response η and ρ independent variables is η<x> = β₀ + …
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