Sentence examples for ica methods from inspiring English sources

Our results indicate that adequate high-pass filtering may be more important than the choice of the ICA method: all three ICA methods achieved a better ERD peak score when the data had been high-pass-filtered at the cutoff frequency just below the frequency band of interest before decomposition.

The brain activated regions were extracted by the SPM and ICA methods respectively.

ICA methods have been applied to raw magnetoencephalography (MEG) and electroencephalography (EEG) signals to remove artifacts, especially when sources such as power line or cardiac activity generate strong components that dominate the signal.

One of the most popular independent component analysis (ICA) methods, the fast fixed-point algorithm for ICA (fastICA), was implemented by the genetic algorithm (geneticICA) to avoid the local maxima problem commonly observed with fastICA.

Different from conventional multiplexed ICA methods which usually require two or more test lines, this strategy was developed for detection of two β-agonists by using only one test line on the nitrocellulose membrane.

The method designed is able to extract the mixing matrix and some statistical features of the noise and the sources, notably improving the performance of the standard ICA methods when the mixture is contaminated by multiplicative noise.

The original ICA method often converges to local optima.

The proposed modified techniques for ICA method provide better results compared to the original ICA and other methods recently reported in the literature as demonstrated by simulation results.

In this paper, we introduce a new kernel-based nonlinear ICA method and compare it to standard BSS techniques.

We show that LIANA provides almost identical results with each ICA method despite the fact that each method yields different individual components.

The extraction of weak components has often been erratic, depending on which ICA method is employed and even on what parameters are used.