Ambiguity resolution in sparse linear prediction
Document Type
Conference Proceeding
Date of Original Version
12-1-1993
Abstract
We present some results of our analysis of Kumaresan's sparse linear prediction method for estimation of frequencies of sinusoids. Refinements of Kumaresan's method are proposed for the case of two sinusoids which are not close in frequency. When the data is corrupted by additive white Gaussian noise, the probability of correctly resolving ambiguities is used to evaluate the performance. Comparisons between statistical performance analyses and computer simulations demonstrate that the analyses are accurate.
Publication Title, e.g., Journal
Conference Record of the Asilomar Conference of Signals, Systems & Computers
Volume
2
Citation/Publisher Attribution
Ge, Hongya, Donald W. Tufts, and R. Kumaresan. "Ambiguity resolution in sparse linear prediction." Conference Record of the Asilomar Conference of Signals, Systems & Computers 2, (1993): 1162-1166. https://digitalcommons.uri.edu/ele_facpubs/692