  We address the problem of noise regression in the output of
gravitational-wave (GW) interferometers, using data from the physical
environmental monitors (PEM). The objective of the regression analysis is to
predict environmental noise in the gravitational-wave channel from the PEM
measurements. One of the most promising regression method is based on the
construction of Wiener-Kolmogorov filters. Using this method, the seismic noise
cancellation from the LIGO GW channel has already been performed. In the
presented approach the Wiener-Kolmogorov method has been extended,
incorporating banks of Wiener filters in the time-frequency domain,
multi-channel analysis and regulation schemes, which greatly enhance the
versatility of the regression analysis. Also we presents the first results on
regression of the bi-coherent noise in the LIGO data.
