Virginia Tech. Department of Mechanical Engineering. Vibration and Acoustics LaboratoriesNaval Surface Warfare Center (U.S.). Carderock Division. Structural Acoustics and Hydroacoustics Research BranchRuckman, Christopher E.Fuller, Chris R.2015-05-272015-05-271995-05-01Ruckman, C. E., & Fuller, C. R. (1995). A regression approach for simulating feedforward active noise control. Journal of the Acoustical Society of America, 97(5), 2906-2918. doi: 10.1121/1.4118570001-4966http://hdl.handle.net/10919/52693Regression analysis is used to examine feedforward active noise control from a statistical point of view. Since numerical techniques for simulating feedforward active noise control in the frequency domain are mathematically similar to linear least-squares regression, two regression-based numerical methods can be applied to control problems. The first uses regression diagnostics such as the F-test, the t-test, and confidence intervals to model the effects of error sensor measurement noise. The second uses collinearity diagnostics to address a form of numerical ill conditioning that can corrupt the results. The regression diagnostics allow realistic modeling of random measurement error; the collinearity diagnostics help avoid numerical difficulties that might otherwise go undetected. Numerical results are given for a structural-acoustic control problem involving a fluid-loaded cylindrical shell. 1995 Acoustical Society of America13 pagesapplication/pdfen-USIn CopyrightActive noise controlAcoustic noise measurementNumerical modelingStatistical analysisArticle - Refereedhttp://scitation.aip.org/content/asa/journal/jasa/97/5/10.1121/1.411857https://doi.org/10.1121/1.411857