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 33 for “"Non-linear Least Squares"”.
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Methods of non-linear least squares estimation
… of the published techniques for determining the least squares estimates of the parameters in non-linear statistical models. It is first briefly indicated why non-linear models require iterative numerical estimating procedures, unlike the straightforward algebraic estimation possibly in the linear …
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Intelligent Cinematic Camera Control for Real-Time Graphics Applications
… rules as cost functions that are fed into a non-linear least squares solver. These cost functions rely on the geometry of the scene, minimizing residuals based on the 3D positions and 2D reprojections of the geometry. The final cinematic view is found by altering camera position and angle …
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Vector Distance Transform Maps for Autonomous Mobile Robot Navigation
… transform. We propose an approach based on non-linear least squares optimization for robot localization on environments represented by vector distance transform maps, that also captures the uncertainty of the position estimate. We also propose an approach based on extended Kalman filter for …
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Evaluation of dynamic nuclear reactor parameters through analysis of stochastic relationships.
… in a microcomputer system. An efficient non-linear least-squares code was developed to fit experimental data to the theoretical distribution function to obtain reactivity. The system developed for data collection and analysis is fully portable, requiring only a microcomputer to implement. …
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Measurement of the first internal mode of polystyrene in cyclohexane and toluene through dynamic light scattering
… (Discrete) on the Cyber 830 computer and by a non-linear least squares program (NLLSQ) on an Apple IIe computer. The exponential decay constants derived from these fits were further used to obtain a value of {dollar}\tau\sb1{dollar} in each solvent and also to find the power relation between …
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Model identification with application to building control and fault detection
(cont.) may still be solved as an unconstrained linear least squares problem. To enforce the constraint on system eigenvalues, the problem is formulated as an unconstrained mixed (linear and non-linear) least-squares problem, which is easier to solve than the corresponding problem with linear …
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Parametric spatial modal analysis of beams
… approaches include autoregressive methods and non-linear least squares techniques. Significant contributions to sample rate considerations for parametric sinusoidal estimation resulted from this research. The minimum residual methods provide a good connection between the measured data and the …
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Exploring the COVID-19 cases around the World
… project is threefold: i) finding the model with least error for the estimation of the skewness, scale, inflection, and carrying capacity parameter. We will first try to fit Skew Log Logistic Model to the cumulative cases data for the define first wave period for each country without the use of …
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Gauss-newton Based Learning For Fully Recurrent Neural Networks
… tailored to the specific optimization problem, (non-linear least squares), which aims to speed up the process of FRNN training. The new approach stands as a robust and effective compromise between the original gradient-based RTRL (low computational complexity, slow convergence) and Newton-based …
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Simultaneous Localization and Calibration in a Wireless Network of Uncooperative Nodes
… offsets. Based on the Newton-Gauss method for non-linear least squares problems, it performs both calibration and localization by iteratively updating estimates of position and RTT offset. Experimental results show the solution can achieve about 5 meter, two-dimensional accuracy within the area …
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Parallel Gauss-Newton method for CP decomposition
… architectures and comparative to Alternating least squares algorithm for CP decomposition. Alternating least squares may exhibit slow or no convergence, especially when high accuracy is required. CP decomposition problem can be formulated as a non-linear least squares problem to apply …
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Time domain synthesis applied to modeling of microwave structures and material characterization
… waveforms with the simulated ones using a non-linear least squares fit. The conventional optimization algorithms have shown to be inefficient in this specific application. In this dissertation an efficient optimization algorithm which has been developed to suit this application is also …
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Kinematic Modeling and Dynamic Aspects of an Accelerating Quadruped
… camera and deep learning algorithm allow non-invasive image pose extraction of an accelerating cheetah subject, which is represented as a mechanism of rigid links interconnected by joints, and this information forms the data basis of subsequent operations. In addition, a non-linear least …
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Parameter estimation for single-phase induction motor from transient measurements
… algorithm iteratively solves a system of non-linear equations involving the parameter values of leakage inductances, magnetizing inductance, and rotor resistance. Selected parameters are further tuned based on a non-linear least squares (NLS) formulation that minimizes the mismatch between …
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Model Based Decomposition of MUAPS Into Their Constituent SFEAPS
… diameter, loss of fibres and reinnervation. The non linear least squares optimization procedure based on the Levenberg-Marquardt algorithm was used to obtain a solution to the MUAP decomposition problem i.e. fibre distribution, positioning and diameter. Using this method, a satisfactory solution …
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Evaluating and improvement of tree stump volume prediction models in the eastern United States
Forests are considered among the best carbon stocks on the planet. After forest harvest, the residual tree stumps persist on the site for years after harvest continuing to store carbon. A bigger concern is that the component ratio method requires a way to get stump volume to obtain total tree …
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Estimation of astronomical images from the bispectrum of atmospherically distorted infrared data.
… by the Levenberg-Marquardt algorithm for non-linear least squares. The ability of the algorithm to determine binary star parameters from the bispectrum is tested with both simulated and observed data. Since the bispectrum may not always be available, a method is developed which determines …
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CARBON DIOXIDE LASER RADAR FOR MONITORING ATMOSPHERIC TRANSMITTANCE AND THE ATMOSPHERIC AEROSOL (REMOTE SENSING, INFRARED).
… a new solution technique based on a weighted, non-linear least squares fit applied to multi-zenith angle lidar returns has been developed. It is shown how constraints may be applied to rule out solutions which are unlikely on a priori grounds. An error analysis and a discussion of proper …
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A nonlinear least squares inversion to the single-scattering three-dimensional radiative transfer equation for satellite-based tomography
… that is commonly found in medical imaging. A non-linear least squares inversion model was developed to reconstruct the distribution of scattering properties in a heterogeneous domain. The inverse model produced excellent reconstructions in many cases, demonstrating the correctness of our …
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Geometrically-informed methods of wave-based imaging
… in the domain. In the first part, we introduce a nonlinear modification to the standard imaging condition that can produce images with resolutions greater than that ordinarily expected using the standard imaging condition. We show that the phase of the integrand of the imaging condition, in the …
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