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 41 for “"Spectral Estimation"”.
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Spectral estimation using nonuniform sampling
Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1995.
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Spectral estimation for sensor arrays
Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering, 1981.
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Spectral Estimation of Hidden Markov Models
… key quantities of hidden Markov models through spectral method-of-moments estimation. Unlike traditional estimation methods like EM and Gibbs sampling, the set of estimation methods, which we call spectral HMMs (sHMMs), are incredibly fast, do not require multiple restarts, and come with …
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Computationally fast algorithms for ARMA spectral estimation
… performance method for obtaining an ARMA model spectral estimate of a wide-sense stationary time series has been found to provide typically superior performance when compared to such contemporary approaches as the Box-Jenkins and maximum entropy methods. In this dissertation, fast recursive …
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Modern spectral estimation methods applied to FOPEN SAR imagery
Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2000.
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The effects of spectral estimation on matched filter design
… structure of the signal and the noise. If the spectral density of the noise is not known or is changing with time its spectral characteristics must be estimated. Since spectral estimators derive their estimates from a random process realization, the estimates themselves are probabilistic in …
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Robust Blind Spectral Estimation in the Presence of Impulsive Noise
Robust nonparametric spectral estimation includes generating an accurate estimate of the Power Spectral Density (PSD) for a given set of data while trying to minimize the bias due to data outliers. Robust nonparametric spectral estimation is applied in the domain of electrical communications and …
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Spectral estimation with spatio-spectral constraints for magnetic resonance spectroscopic imaging
… to acquire in vivo biochemical information, and spectral estimation (quantification) of MRSI data is an important step towards quantitative studies. Although a large body of work has been done on spectral estimation over the past decades, it remains challenging due to model nonlinearity and …
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Plasma line generation and spectral estimation from Arecibo Observatory radar data
… and ion-acoustic waves, respectively. Such ISR spectral measurements can be conducted at the Arecibo Observatory, one of the most important centers in the world for research in radio astronomy, planetary radar and terrestrial aeronomy [Altschuler, 2002]. Although ISR measurements have been …
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Recursive estimation and spectral estimation for 2-D isotropic random fields
Thesis (Sc. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1987.
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Radar cross-section data encoding based on parametric spectral estimation techniques
… applications. These applications include data estimation and interpolation, modern spectral estimation, and data encoding. This research applies parametric modeling to radar cross section data in an attempt to encode it as well as preserve its spectrum. Traditionally, radar data has been …
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A linear prediction approach to two-dimensional spectral factorization and spectral estimation.
Thesis. 1978. Ph.D.--Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
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Exploiting pitch dynamics for speech spectral estimation using a two-dimensional processing framework
… addresses the problem of obtaining an accurate spectral representation of speech formant structure when the voicing source exhibits a high fundamental frequency. Our work is inspired by auditory perception and physiological modeling studies implicating the use of temporal changes in speech by …
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A function space approach to the generalized nonlinear model with applications to frequency domain spectral estimation
… (1983) outlined the theory of quasi-likelihood estimation in generalized linear models. Chiu (1988) showed that an iterated, reweighted least squares procedure applied to the periodogram produces estimates of spectral density model parameters for Gaussian univariate time series which have the …
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Parameter estimation of models with many damped complex exponentials
Parameter estimation techniques for data modelled as a sum of damped complex exponentials are proving to be a successful alternative to Fourier transform methods for spectral estimation.
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Parameter estimation of models with many damped complex exponentials
Parameter estimation techniques for data modelled as a sum of damped complex exponentials are proving to be a successful alternative to Fourier transform methods for spectral estimation.
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Digital spectral analysis and adaptive processing techniques for phase modulated optical fiber sensors
… information from the fiber sensor. Classical spectral analysis utilizing the Fourier transform as a mathematical foundation for relating a time or space signal to its frequency-domain representation was shown to be inadequate for mitigating the bias errors caused by harmonic distortions. A …
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DIGITAL ANALYSIS OF PULSE CODE MODULATED SIGNALS IN TELECOMMUNICATIONS CHANNELS
… hardware. Windowing of data to improve spectral estimation is discussed as well as the conditions where special test signals may be synthesized to preclude the need for windowing. Conjugate-periodic functions encountered in prime radix transforms are defined and their fast transform …
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Model-based spectral inference in noisy physical time series: applications in laser linewidth estimation and precision magnetometry
… and applies model-based inference techniques for spectral analysis of noisy physical time series. Two distinct experimental settings – narrow-linewidth semiconductor lasers and spin-precession-based magnetometry – pose inverse problems that traditional methods struggle with due to low signal-to- …
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