External noise removed from magnetoencephalographic signal using independent component analyses of reference channels

Independent component analysis of magnetoencephalographic signals

Adaptive Noise Canceling Using Convolved Reference Noise Based on Independent Component Analysis

This paper presents adaptive noise canceling(ANC) using convolved reference noise. In many practical ANC applications, the reference noise has channel distortion, which may degrade its performance. If the distortion includes nonminimum-phase parts, the inverse cannot be implemented as a causal filter. Therefore, the conventional ANC system may not provide a satisfactory performance. In this pap...

Selective Noise Cancellation Using Independent Component Analysis

Independent Component Analysis for Identification of Artifacts in Magnetoencephalographic Recordings

We have studied the application of an independent component analysis (ICA) approach to the identification and possible removal of artifacts from a magnetoencephalographic (MEG) recording. This statistical technique separates components according to the kurtosis of their amplitude distributions over time, thus distinguishing between strictly periodical signals, and regularly and irregularly occu...

Denoising of Ecg Signal Using Adaptive Independent Component Analysis

It has been observed that denoising of ECG is done in stationary condition i.e. when the patient under scanner is lying on bed or in rest condition. This is very common case and the noise added in this condition can be removed by many different methodologies like FFT, wavelet, ICA etc. However, when the ECG is monitored in dynamic condition e.g., on tread mill testing, the noise inserted due to...