We propose a Bayesian expectation-maximization (EM) algorithm for reconstructing structured approximately sparse signals via belief propagation. The measurements follow an underdetermined linear model where the regression-coefficient vector is the sum of an unknown approximately sparse signal and a zero-mean white Gaussian noise with an unknown variance. The signal is composed of largeand small...

This paper presents a method of diagnosing variance components of process error sources in singular manufacturing systems. The singularity problem is studied and the cause examined in the context of fixture error diagnosis in multi-station assembly processes. The singularity problem results in nondiagnosable fixture errors when standard least-squares (LS) estimation methods are used. This paper...

The Gaussian process model is an example of a flexible, probabilistic, nonparametric model with uncertainty predictions. It can be used for the modelling of complex nonlinear systems and recently it has also been used for a dynamic systems identification. Gaussian process models have become an emerging, complementary method for a nonlinear system identification. The output of the GP model is a ...

An e,;perimental technique for the investigation of the behaviour of acoustic wave propagation through a turbulent medium is discussed. The present study utilizes the ultrasonic travel-time technique to di­ agnose a grid-generated turbulence. Travel-time variance is studied versus mean Dow velocity. travel distance and outer turbulence scale. The effect of therma.l fluctuations. which result in...

Introduction: Monte Carlo (1) and Bootstrap (2) methods provide powerful statistical tools for determining the effects of background noise in diffusion weighted imaging (DWI) data on DTI-derived parameters, and for optimizing the design of DTI experiments. While these empirical methods do not provide analytical relationships between the variance of the distribution of noise in the DWI data and ...

The rapid development of fiber optic communication systems requires higher transmission data rate and longer reach. This thesis deals with the limiting factors in design of long-haul fiber optic communication systems and the techniques used to suppress their resulting impairments. These impairments include fiber chromatic dispersion, the Ker nonlinearity and nonlinear phase noise due to amplifi...

Performance of adaptive optics (AO) compensation for beam control is quantified via wave-optical propagation, sensing, and control methods using wind tunnel measurements of aero-optical disturbances in addition to Kolmogorov turbulence distributed over a laser path. For Kolmogorov turbulence the residual phase variance scales as (fG/f3dB) , where fG is the Greenwood frequency for the propagatio...

We propose techniques for accurate and computationally viable estimation of timing yield using circuit-level Monte Carlo simulation. Our techniques are based on well-known variance reduction approaches from Monte Carlo simulation literature. By adapting these techniques to the yield estimation problem, one can reduce the number of Monte Carlo samples required in order to estimate yield within a...

In an optical communication link between an optical ground station and a geostationary satellite the main problems appear in the uplink and are due to beam wander and to scintillation. Reliable methods for modeling both effects simultaneously are needed to provide an accurate tool with which the robustness of the communication channel can be tested. Numerical tools, especially the split-step me...