On the Estimation of Nonrandom Signal Coefficients from Jittered Samples

This paper examines the problem of estimating the parameters of a bandlimited signal from samples corrupted by random jitter (timing noise) and additive iid Gaussian noise, where the signal lies in the span of a finite basis. For the presented classical estimation problem, the Cramer-Rao lower bound (CRB) is computed, and an Expectation-Maximization (EM) algorithm approximating the maximum likelihood (ML) estimator is developed. Simulations are performed to study the convergence properties of the EM algorithm and compare the performance both against the CRB and a basic linear estimator. These simulations demonstrate that by post-processing the jittered samples with the proposed EM algorithm, greater jitter can be tolerated, potentially reducing on-chip ADC power consumption substantially.Comment: 11 pages, 8 figure

Geoadditive Regression Modeling of Stream Biological Condition

Indices of biotic integrity (IBI) have become an established tool to quantify the condition of small non-tidal streams and their watersheds. To investigate the effects of watershed characteristics on stream biological condition, we present a new technique for regressing IBIs on watershed-specific explanatory variables. Since IBIs are typically evaluated on anordinal scale, our method is based on the proportional odds model for ordinal outcomes. To avoid overfitting, we do not use classical maximum likelihood estimation but a component-wise functional gradient boosting approach. Because component-wise gradient boosting has an intrinsic mechanism for variable selection and model choice, determinants of biotic integrity can be identified. In addition, the method offers a relatively simple way to account for spatial correlation in ecological data. An analysis of the Maryland Biological Streams Survey shows that nonlinear effects of predictor variables on stream condition can be quantified while, in addition, accurate predictions of biological condition at unsurveyed locations are obtained

Modelling Organic Dairy Production Systems

In this study, a large number of organic dairy production strategies were compared in terms of physical and financial performance through the integrated use of computer simulation models and organic case study farm data. Production and financial data from three organic case study farms were used as a basis for the modelling process to ensure that the modelled systems were based on real sets of resources that might be available to a farmer. The case study farms were selected to represent a range of farming systems in terms of farm size, concentrate use and location. This paper describes the process used to model the farm systems: the integration of the three models used and the use of indicators to assess the modelled farm systems in terms of physical sustainability and financial performance

Experimental Research on Glass- Polycarbonate Beams

A research project at the Institute of Building Construction explores compositebeams made of glass and transparent polycarbonate. These beams consist of oneinner polycarbonate sheet and two outer panes of glass and are bonded by atransparent adhesive. Several experimental tests demonstrated that the glasspolycarbonatebeams can behave in a ductile manner when the load-bearingcapacity is exceeded. Furthermore, a high residual load-bearing capacity aftercomplete glass-breakage exists. On the contrary, typical laminated glass beams failin cases of complete glass breakage despite the PVB-foil used. Tests with thecomposite beams made of glass and polycarbonate were carried out with varyingcross-sections, glass types and loadings. Moreover, the different elongations due totemperature were investigated in climate tests

Bayesian Post-Processing Methods for Jitter Mitigation in Sampling

Minimum mean-square error (MMSE) estimators of signals from samples corrupted by jitter (timing noise) and additive noise are nonlinear, even when the signal parameters and additive noise have normal distributions. This paper develops a stochastic algorithm based on Gibbs sampling and slice sampling to approximate the optimal MMSE estimator in this Bayesian formulation. Simulations demonstrate that this nonlinear algorithm can improve significantly upon the linear MMSE estimator, as well as the EM algorithm approximation to the maximum likelihood (ML) estimator used in classical estimation. Effective off-chip postprocessing to mitigate jitter enables greater jitter to be tolerated, potentially reducing on-chip ADC power consumption

Domain Dynamics of Magnetic Films with Perpendicular Anisotropy

We study the magnetic properties of nanoscale magnetic films with large perpendicular anisotropy comparing polarization microscopy measurements on Co_28Pt_72 alloy samples based on the magneto-optical Kerr effect with Monte Carlo simulations of a corresponding micromagnetic model. We focus on the understanding of the dynamics especially the temperature and field dependence of the magnetisation reversal process. The experimental and simulational results for hysteresis, the reversal mechanism, domain configurations during the reversal, and the time dependence of the magnetisation are in very good qualitative agreement. The results for the field and temperature dependence of the domain wall velocity suggest that for thin films the hysteresis can be described as a depinning transition of the domain walls rounded by thermal activation for finite temperatures.Comment: 7 pages Latex, Postscript figures included, accepted for publication in Phys.Rev.B, also availible at: http://www.thp.Uni-Duisburg.DE/Publikationen/Publist_Us_R.htm