Physical Sciences and Mathematics Commons^™

Correction Of Electronic Record For Weighing Bucket Precipitation Gauge Measurements, Anurag Nayak, David G. Chandler, Danny Marks, James P. Mcnamara, Mark Seyfried

Geosciences Faculty Publications and Presentations

Electronic sensors generate valuable streams of forcing and validation data for hydrologic models but are often subject to noise which must be removed as part of model input and testing database development. We developed an automated precipitation correction program (APCP) for weighing bucket precipitation gauge records, which are subject to several types of mechanical and electronic noise and discontinuities, including gauge maintenance, missing data, wind vibration, and sensor drift. Corrected cumulative water year precipitation from APCP did not exhibit an error bias and matched measured water year total precipitation within 2.1% for 58 station years tested. Removal of low-amplitude periodic …

Slides: Energy Production And The West's Wild Places, Amy Mall

Shifting Baselines and New Meridians: Water, Resources, Landscapes, and the Transformation of the American West (Summer Conference, June 4-6)

Presenter: Amy Mall, Senior Policy Analyst, Natural Resources Defense Council

28 slides

Improving Performance Of The Filtered-X Least Mean Square Algorithm For Active Control Of Noise Contatining Multiple Quasi-Stationary Tones, Stephan P. Lovstedt

Theses and Dissertations

The Filtered-X Least-Mean-Square (FXLMS) algorithm is widely used in active noise control due to its robustness, simplicity, and ability to be implemented in real time. In a feedforward implementation of the FXLMS algorithm, a reference signal that is highly correlated with the noise to be controlled is filtered with an estimate of the transfer function of the secondary path. The convergence characteristics of the FXLMS algorithm have been well studied. A convergence parameter is used to optimize the convergence of the algorithm. However, the optimal value for the convergence parameter is frequency dependent. Thus for noise containing multiple tones at …

Multiscale Deformable Registration Of Noisy Medical Images, Dana C. Paquin, Doron Levy, Lei Xing

Mathematics

Multiscale image registration techniques are presented for the registration of medical images using deformable registration models. The techniques are particularly effective for registration problems in which one or both of the images to be registered contains significant levels of noise. A brief overview of existing deformable registration techniques is presented, and experiments using B-spline free-form deformation registration models demonstrate that ordinary deformable registration techniques fail to produce accurate results in the presence of significant levels of noise. The hierarchical multiscale image decomposition described in E. Tadmor, S. Nezzar, and L. Vese’s, ”A multiscale image representation using hierarchical (BV, L^{2 …}