Blind Deconvolution and Blind Source Separation (A Summary)

1 Summary The goal of blind deconvolution and source separation is to unravel the effects of an unknown linear transformation on a unknown signal source. For blind deconvolution, the transformation is a linear finite-impulse response (FIR) filter, and for blind source separation it is a matrix of mixing coefficients. A general architecture for these blind adaptive algorithms consists of an adjustable linear transformation and a non-linear function. In this presentation, we will examine the Bussgang algorithm for blind deconvolution [2] and an informationmaximization algorithm to perform blind source separation [1].