@CONFERENCE\{IMM2004-03367,
    author       = "M. Dyrholm and L. K. Hansen",
    title        = "CICAAR: Convolutive {ICA} with an Auto-Regressive Inverse Model",
    year         = "2004",
    month        = "sep",
    keywords     = "Convolutive {ICA} {AR} speech deconvolution maximum likelihood",
    pages        = "594-601",
    booktitle    = "Independent Component Analysis and Blind Signal Separation",
    volume       = "3195",
    series       = "Lecture Notes in Computer Science",
    editor       = "Carlos G. Puntonet and Alberto Prieto",
    publisher    = "Springer",
    organization = "",
    address      = "",
    url          = "http://www2.compute.dtu.dk/pubdb/pubs/3367-full.html",
    abstract     = "We invoke an auto-regressive {IIR} inverse model for convolutive {ICA} and derive expressions for the likelihood and its
gradient. We argue that optimization will give a stable inverse. When there are more sensors than sources the mixing
model parameters are estimated in a second step by least squares estimation. We demonstrate the method on synthetic
data and finally separate speech and music in a real room recording.",
    isbn_issn    = "3-540-23056-4"
}