In　the　far-field　scene　with　noise　and　reverberation,　the　integrated　sidelobe　cancellation　and　linear　prediction　(ISCLP)　method　can　simultaneously　implement　spatial　filtering　and　deconvolution　to　effectively　suppress　additive　noise　and　reverberation,　but　it　has　high　complexity　for　calculating　power　spectral　density　(PSD).　In　order　to　reduce　this　complexity,　the　power-based　PSD　estimation　method　instead　of　the　generalized　eigenvalue　decomposition　(GEVD)　is　proposed　in　this　paper　to　obtain　eigenvalues　and　eigenvectors　used　for　calculating　PSD.　Computational　complexity　is　reduced　to　M　times　as　compared　with　the　GEVD　by　combining　power-based　method　with　Wielandt＇s　deflation　which　is　used　to　solve　the　eigenvalues　and　the　corresponding　eigenvectors　of　correlation　matrix　of　the　observed　signals.　Experimental　results　show　that　the　performance　of　dereverberation　and　noise　reduction　of　the　proposed　method　decreases　slightly　as　compared　with　the　GEVD-based　ISCLP　method.　©　2022　IEEE.