An Efficient Jacobi-Like Deflationary ICA Algorithm: Application to EEG Denoising

作者：Sardouie Sepideh Hajipour^*; Albera Laurent; Shamsollahi Mohammad Bagher; Merlet Isabelle

来源：IEEE Signal Processing Letters, 2015, 22(8): 1198-1202.

DOI：10.1109/LSP.2014.2385868

• Deflation
• denoising
• ElectroEncephaloGraphy
• higher order statistics
• independent component analysis
• interictal epileptic data
• Jacobi-like optimization

In this paper, we propose a Jacobi-like Deflationary ICA algorithm, named JDICA. More particularly, while a projection-based deflation scheme inspired by Delfosse and Loubaton's ICAtechnique (DelL(R)) is used, a Jacobi-like optimization strategy is proposed in order to maximize a fourth order cumulant-based contrast built from whitened observations. Experimental results obtained from simulated epileptic EEG data mixed with a real muscular activity and from the comparison in terms of performance and numerical complexity with the FastICA, RobustICA and DelL(R) algorithms, show that the proposed algorithm offers the best trade-off between performance and numerical complexity when a low number (similar to 12) of electrodes is available.

• 出版日期2015-8