Error propagation modeling for terrain analysis can provide insights into the robustness of terrain derivatives. For unconstrained terrain derivatives, such as stream and watershed delineation, the most widely used technique for error propagation modeling employs a Monte Carlo simulation of a spatially autocorrelated error model. The current study seeks to make this methodology more accessible ...

The static pull-in instability of beam-type micro-electromechanical systems is theoretically investigated. Two engineering cases including cantilever and double cantilever micro-beam are considered. Considering the mid-plane stretching as the source of the nonlinearity in the beam behavior, a nonlinear size-dependent Euler-Bernoulli beam model is used based on a modified couple stress theory, c...

A new decoding algorithm for some convolution~l codes constructed from block codes is given. The algorithm utilizes the decoding algorithm for the corresponding block code. It is shown that the codes obtained from one-step orthogonalizable block codes are majority deeodable. Error propagation in some of these convolutional codes is studied. It is shown that if decoded with moderately reduced ca...

A comparative study of artificial neural network (ANN) and multiple regression is made to predict the fat tail weight of Balouchi sheep from birth, weaning and finishing weights. A multilayer feed forward network with back propagation of error learning mechanism was used to predict the sheep body weight. The data (69 records) were randomly divided into two subsets. The first subset is the train...

A system level fault injection experiment measuring changes in probability of failure and error propagation as a function of failure acceleration. It demonstrates that: (1) Probability of failure increases with failure acceleration, and (2) Error propagation decreases with failure acceleration .

The central theme is the study of error propagation effects in decision feedback equalizers (DFEs). The thesis contains: a stochastic analysis of error propagation in a tuned DFE; an analysis of the effects of error propagation in a blindly adapted DFE; a deterministic analysis of error propagation through input-output stability ideas; and testing procedures for establishing correct tap converg...

The prediction uncertainty of a hydrologic model is closely related to model formulation and the uncertainties in model parameters and inputs. Currently, the foremost challenges concern not only whether hydrologic model outputs match observations, but also whether or not model predictions are meaningful and useful in the contexts of land use and climate change. The latter is difficult to determ...