In some recent papers new algorithms for blind adaptive equalization were proposed. These algorithms are based on the stochastic gradient method and thus can be regarded as a jblindj counterpart to the classic LMS- (least mean squares-) algorithms. It is well-known that these algorithms show relatively slow convergence speed. The classic solution to get fast convergence is the RLS- (recursive least squares-) algorithm which makes use of the closed-form solution. The purpose of this paper is to derive a closed-form solution in the sense of blind equalization. It will be shown that the equalizer coeOEcients can be uniquely derived from the eigenvectors of a speciøc 4th-order cumulant matrix of the received signal. By means of some examples it will be demonstrated that the eigenvector solution is near the ideal MSE- (mean square error-) solution. In der letzten Zeit wurden verschiedene neue Algorithmen zur blinden adaptiven Entzerrung vorgeschlagen. Diese Algorithmen basieren auf dem stoc..