  CLEAN algorithms are a class of deconvolution solvers which are widely used
to remove the effect of the telescope Point Spread Function (PSF). Loop gain is
one important parameter in CLEAN algorithms. Currently the parameter is fixed
during deconvolution, which restricts the performance of CLEAN algorithms. In
this paper, we propose a new deconvolution algorithm with an adaptive loop gain
scheme, which is referred to as the adaptive-loop-gain adaptivescale CLEAN
(Algas-Clean) algorithm. The test results show that the new algorithm can give
a more accurate model with faster convergence.
