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Exponential Modeling with Unknown Model Order Using Structured Nonlinear Total Least Norm
Zhang, Lei; Park, Haesun; Rosen, J. Ben (2000)
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https://hdl.handle.net/11299/215413
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Title
Exponential Modeling with Unknown Model Order Using Structured Nonlinear Total Least Norm
Authors
Issue Date
2000-04-07
Type
Report
Abstract
A method based on Structured Nonlinear Total Least Norm is presented for estimating the parameters of exponentially damped sinusoidal signals in noise when the model order is unknown. It is compared to two other existing methods to show its robustness in recovering correct values of parameters when the model order is unknown, in spite of some large errors in measured data.
Appears in collections
Computer Science & Engineering (CS&E) Technical Reports [747]
Series/Report Number
Technical Report; 00-025
Suggested Citation
Zhang, Lei; Park, Haesun; Rosen, J. Ben. (2000). Exponential Modeling with Unknown Model Order Using Structured Nonlinear Total Least Norm. Retrieved from the University of Minnesota Digital Conservancy, https://hdl.handle.net/11299/215413.
Content distributed via the University of Minnesota's Digital Conservancy may be subject to additional license and use restrictions applied by the depositor.