Sensitivity of polynomial composition and decomposition for signal processing applications
Name
Oppenheim_Sensitivity of.pdf
Size
943.44 KB
Format
Adobe PDF
Checksum (MD5)
8e0b64a26f811a97d4b634f5a849c590
Author(s)
Demirtas, Sefa
Su, Guolong
Oppenheim, Alan V.
Date Issued
November 2012
Journal
Proceedings of the 2012 Conference Record of the Forty Sixth Asilomar Conference on Signals, Systems and Computers (ASILOMAR)
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Demirtas, Sefa, Guolong Su, and Alan V. Oppenheim. “Sensitivity of Polynomial Composition and Decomposition for Signal Processing Applications.” 2012 Conference Record of the Forty Sixth Asilomar Conference on Signals, Systems and Computers (ASILOMAR) (November 2012).
Version
Author's final manuscript
Abstract
Polynomial composition is well studied in mathematics but has only been exploited indirectly and informally in signal processing. Potential future application of polynomial composition for filter implementation and data representation is dependent on its robustness both in forming higher degree polynomials from ones of lower degree and in exactly or approximately decomposing a polynomial into a composed form. This paper addresses robustness in this context, developing sensitivity bounds for both polynomial composition and decomposition and illustrates the sensitivity through simulations. It also demonstrates that sensitivity can be reduced by exploiting composition with first order polynomials and commutative polynomials.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology. Research Laboratory of Electronics
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/ACSSC.2012.6489032
