Publication: An Approximation of FOCUSS Mean Squared Error
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Issued Date
2023
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application/pdf
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Scopus
Bibliographic Citation
Proceedings of JCSSE 2023 - 20th International Joint Conference on Computer Science and Software Engineering. Vol , No. (2023), p.231-236
Suggested Citation
Tausiesakul B., Asavaskulkiet K. An Approximation of FOCUSS Mean Squared Error. Proceedings of JCSSE 2023 - 20th International Joint Conference on Computer Science and Software Engineering. Vol , No. (2023), p.231-236. doi:10.1109/JCSSE58229.2023.10202042 Retrieved from: https://hdl.handle.net/20.500.14740/9045
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Abstract
FOCal Underdetermined System Solver (FOCUSS) is an estimation method for finding a n unknown vector that potentially has a sparse structure. The application of this estimation technique can be found in several areas, e.g., sparse signal recovery in image reconstruction, wireless communications, etc. The convergence analysis performance and order of convergence of this technique are the focuses of this study. In this work, we investigate its estimation error performance on the second order, in terms of error variance or mean squared error. Since the computation in this algorithm is nonlinear, an exact form of the error performance seems infeasible. Therefore, we derive a closed-form expression that approximates the mean squared error of the FOCUSS. Numerical simulation was conducted to illustrate the closeness of our prediction to the real estimation error. © 2023 IEEE.