Abstract
The lack of global convergence of existing blind equalization
algorithms prompts the need for studying their mean cost functions and
the whereabouts of local and global minima. The authors explore the
location of minima for several general families of cost functions for
blind equalization. It is shown that minima are unique along any radial
direction in the equalizer parameter space. The authors characterize the
resident manifold on which all minima and all saddle points of the cost
function must reside. This information can be helpful in designing
initialization strategies and parameter constraints to avoid convergence
under adaptation to undesirable local minima
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