TY - GEN
T1 - Performance analysis of least-squares khatri-rao factorization
AU - Cheng, Yao
AU - Cheema, Sher Ali
AU - Haardt, Martin
AU - Weiss, Amir
AU - Yeredor, Arie
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2018/3/9
Y1 - 2018/3/9
N2 - The least-squares Khatri-Rao factorization is regarded as an important linear- and multilinear-algebraic tool and finds applications in, for instance, computation of the CP decomposition and channel estimation for two-way relaying systems. We conduct a 'first-order' perturbation analysis for it, which is a crucial step towards establishing analytical performance evaluation of various schemes employing the least-squares Khatri-Rao factorization. Numerical results validating our analytical performance analysis are shown. Being new advance in perturbation analysis on matrix decompositions, the performance analysis of the least-squares Khatri-Rao factorization presented in this paper will also contribute to a promising enhancement of the SECSI-GU framework, which is able to estimate the loading matrices in a CP decomposition, both efficiently and accurately.
AB - The least-squares Khatri-Rao factorization is regarded as an important linear- and multilinear-algebraic tool and finds applications in, for instance, computation of the CP decomposition and channel estimation for two-way relaying systems. We conduct a 'first-order' perturbation analysis for it, which is a crucial step towards establishing analytical performance evaluation of various schemes employing the least-squares Khatri-Rao factorization. Numerical results validating our analytical performance analysis are shown. Being new advance in perturbation analysis on matrix decompositions, the performance analysis of the least-squares Khatri-Rao factorization presented in this paper will also contribute to a promising enhancement of the SECSI-GU framework, which is able to estimate the loading matrices in a CP decomposition, both efficiently and accurately.
UR - https://www.scopus.com/pages/publications/85050754369
U2 - 10.1109/CAMSAP.2017.8313178
DO - 10.1109/CAMSAP.2017.8313178
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T3 - 2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2017
SP - 1
EP - 5
BT - 2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 7th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2017
Y2 - 10 December 2017 through 13 December 2017
ER -