Fourier Linear Combiner Research Articles

MSE behavior of biomedical event-related filters.

The mean-squared error (MSE) behavior for Fourier linear combiner (FLC)-based filters is analyzed, using the independence assumption. The advantage of this analysis is its simplicity compared with previous results. The MSE transient behavior for this kind of filters is also presented for the first time. Moreover, a time-varying sequence for the least mean square (LMS) algorithm step-size is proposed to provide fast convergence with small misadjustment error. It is shown that for this sequence, the MSE behaves better as the input signal-to-noise ratio (SNR) decreases, but increases with the number of harmonics. Lastly, we make a brief analysis on the nonstationary behavior of these filters, and again we find simple expressions for the MSE behavior.

Modeling and canceling tremor in human-machine interfaces

Zero-phase modeling and canceling of tremor can improve precision in human-machine control applications. Past methods of tremor suppression have been hindered by feedback delays due to phase lag and by the inability to track tremor frequency over time. The weighted-frequency Fourier linear combiner (WFLC) is an adaptive noise canceller that precisely models tremor with zero phase lag. This article briefly presents the WFLC algorithm and describes its application to computer input filtering, clinical tremor quantification, and active tremor canceling for microsurgery.

Filtering noncorrelated noise in impedance cardiography.

Impedance cardiography (ICG) may be altered by noises as respiration and movement artifacts, mainly during exercise. In this work, a scaled Fourier linear combiner (SFLC) event-related to the R-R interval of ECG is proposed. It estimates the deterministic component of the impedance cardiographic signal and removes the noises uncorrelated to this interval. The impedance cardiographic signal is modeled as Fourier series with the coefficients estimated by the least mean square (LMS) algorithm. Simulations have been carried out to evaluate the filter performance for different noise conditions. Moreover, the method capability to remove uncorrelated noises was also examined in physiological data obtained in rest and exercise, by synchronizing respiration and pedaling with a metronome. Analyzing the ICG power spectrum, it was concluded that the proposed filter could remove the noises that are not synchronized with heart rate.