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Skip to Search Results- 7Resonance
- 2Covariate Shift
- 2Machine Learning
- 1 Damping
- 13rd order high pass filter
- 1Accumulated phase
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Fall 2019
Harmonic filtering is an effective method to mitigate harmonic distortions in power systems. Over the last decades, a number of harmonic filtering techniques have been proposed to deal with the increasing proliferation of harmonic-producing loads. Among these techniques, passive harmonic...
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Spring 2010
The procedure for milling micrometre scale cantilevers of lutetium iron garnet using a focused ion beam microscope was developed. The infrastructure to study these cantilevers using rotational hysteresis loops and ferromagnetic resonance experiments was set up. The cantilevers were shown to...
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Fall 2010
The thesis is divided in three parts based largely on published articles or on manuscripts submitted for publication. First we propose a new method which is called the shooting-bead method. This method is a fast and easy experimental technique for evaluating cantilever stiffness and flexural...
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Modeling and Mitigation of Harmonic Distortions Caused by Mass-Distributed Harmonic Sources
DownloadFall 2017
In recent years, the proliferation of energy-efficient but harmonic-producing home appliances has significantly changed the nature of power system harmonic problems. One of the main concerns nowadays is the harmonics produced by small, mass-distributed harmonic sources. Their unique random and...
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Fall 2013
Many learning situations involve learning the conditional distribution $p(y|x)$ when the training data is drawn from the training distribution $p{tr}(x)$, even though it will later be used to predict for instances drawn from a different test distribution $p{te}(x)$. Most current approaches focus...
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Fall 2017
Resonance is at the heart of sensing and characterization tools in all fields of science. A nanoresonator has achieved the remarkable resolution of a proton mass. The coupling of a micromechanical oscillator to an optical field in a high finesse cavity has allowed sensitive probing even in the...
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Strange springs in many dimensions: how parametric resonance can explain divergence under covariate shift.
DownloadFall 2021
Most convergence guarantees for stochastic gradient descent with momentum (SGDm) rely on independently and identically ditributed (iid) data sampling. Yet, SGDm is often used outside this regime, in settings with temporally correlated inputs such as continual learning and reinforcement learning....