Multiresolution restoration of medical signals using the renormalization group and the super-coupling transforms

This paper presents a multiresolution approach to the restoration of Magnet oencephalographic (MEG) signals corrupted by colored Gaussian noise. We com pare two methods, namely the renormalization group transform (RGT) and the super-coupling transform (ST). We conclude that although the RGT approach r equires fewer site updates than the ST approach in order to converge, the S T approach is overall much faster. The multiresolution algorithm was tested with real and simulated data. In the case of simulated data, where the ori ginal signal's peak-to-peak value is known, the algorithm worked well with noise levels up to 80% of this value. (C) 1999 Elsevier Science Ltd. All ri ghts reserved.