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.
Results
Showing 1 to 20 of 58 for “"Approximation Techniques"”.
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Approximation techniques in network information theory
… in the presence of noisy feedback. The key approximation technique used to complete this task is the so-called {linear deterministic model}. It is found that when the feedback link strengths exceed certain thresholds, the performance of the interference channel starts to improve. The second …
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Approximation techniques for the optimal scheduling of the Space-Based Visible satellite
Thesis (M.Eng. and S.B.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2000.
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Exploring Per-Input Filter Selection and Approximation Techniques for Deep Neural Networks
We propose a dynamic, input dependent filter approximation and selection technique to improve the computational efficiency of Deep Neural Networks. The approximation techniques convert 32 bit floating point representation of filter weights in neural networks into smaller precision values. This is …
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Study of many-body approximation techniques in simple non-linear coupled system of fermions and oscillators.
Thesis: M.S., Massachusetts Institute of Technology, Department of Physics, 1978
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Dynamics of a Small Autonomous Underwater Vehicle That Tows a Large Payload
… must be fully modeled. Furthermore, several approximation techniques based on analytic and empirical formulations are investigated for computing the hydrodynamic coefficients of the vehicle. Efficacy and limitations of the approximation techniques are assessed by comparison with hydrodynamic …
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Batch and Online Implicit Weighted Gaussian Processes for Robust Novelty Detection
… or exceeding the performance of other successful techniques. That is the case of a recently proposed approach to GP-based novelty detection that uses standard GPs (i.e. GPs employing Gaussian likelihoods). However, standard GPs are sensitive to outliers in training data, and this limitation …
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Advanced Quantum Mechanical Simulations of Circular Dichroism Spectra
… Schrödinger equation by employing a variety of approximation techniques whose accuracy are typically inversely proportional to their computational cost. This problem is amplified when it comes to chiral molecules, whose stereochemical assignments and associated chiroptical properties can be …
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Framework for a Unified Macroscale Model of Magnetostriction
… model to two dimensions. This requires numerical approximation techniques which take the form of quadrature methods in the existing magnetostrictive literature. Examining the inherent assumptions of models in the literature highlights that they often produce artificial spurious responses due to …
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High-order adaptive methods for computing invariant manifolds of maps
… he proposes using higher-order interpolation/approximation techniques from geometric modeling. He uses Bezier curves/triangles, fundamental objects in curve/surface design, to create adaptive methods. The methods are based on tolerance conditions derived from properties of Bezier …
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Large-signal tools for power electronics: State space analysis and averaging theory
… A theoretical basis for widely used averaging approximation techniques is developed. Three new large-signal tools are introduced which are an outgrowth of the basic theory developed. Three large-signal experiments are reported which test the modeling formalism and the geometric and averaging …
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Uncertainty Estimation for Single Stage Object Detection
… pipelines. However, the application of Bayesian approximation techniques to complex, real-world object detection scenarios remains significantly underexplored, as existing literature focuses predominantly on simplified toy problems and lower-dimensional datasets. To address this gap, this thesis …
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Heterogeneous parallel virtual machine: A portable program representation and compiler for performance and energy optimizations on heterogeneous parallel systems
… a wide range of diverse hardware and software approximation techniques are available for applications targeting heterogeneous SoCs, further exacerbating the programmability challenges. In this thesis, we alleviate the programmability challenges of such systems using flexible compiler …
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The design of adaptive structures for wing morphing
… the design paradigm, in conjunction with global approximation techniques, is emphasized by enhanced roll while drag is minimised. This figure of merit is complemented by structural metrics and constraints so as to maintain product integrity.
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European and American Option Pricing with a Geometric Markov Renewal Process Underlying Asset Model
… processes, Geometric Brownian Motion, and GMRP approximation techniques are presented. We discuss the Aase trading model, with a MATLAB implementation. We discuss the Black-Scholes and binomial Cox-Ross-Rubinstein formulas for European and American options. We present results on Fixed Time …
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View-dependent precomputed light transport using non-linear Gaussian function approximations
… traditional linear and non-linear (truncation) approximation techniques. We present a new data fitting method based on optimization that includes energy terms aimed at enforcing good interpolation. We demonstrate that our method achieves high visual quality for a small storage cost and fast …
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Simple certificate for power distribution network security assessment
… This thesis presents fast and reliable inner approximation techniques for solvable boundaries of power distribution systems based on Banach fixed point theorem and Kantorovich theorem. The novel method is in a simple "certificate" form-a single lined inequality condition that involves the …
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Accurate belief state update for probabilistic constraint automata
… thesis introduces two innovative belief state approximation techniques, called Best-First Belief State Enumeration (BFBSE) and Best-First Belief State Update (BFBSU), that address this limitation by computing estimate probabilities directly from the HMM belief state update equations. …
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Efficient and Robust Black-box Integral-approximation and Optimization
Black-box optimization and black-box integral approximation are important techniques for machine learning, industrial design, and simulation in science. This thesis investigates black-box integral approximation and black-box optimization by considering the closed relationship between them. For …
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A three-dimensional coupled modes solution for range-dependent waveguides
… problems can be classified as: normal-mode techniques (adiabatic or coupled modes); parabolic-approximation techniques (narrow- or wide-angle parabolic equations solved by split-step or finite-difference techniques); and finite-element/finite- difference solutions of the full wave equation. …
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Solving Cyber-Alert Allocation Markov Games with Deep Reinforcement Learning
… iteration based algorithms. We then move into approximation techniques, using deep neural networks and Q-learning to derive near-optimal strategies that allow us to explore much larger models. We assess the effectiveness of our allocation strategies by comparing them to other sensible …
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