Bearing Remaining Useful Life Prediction Based on AdCNN and CWGAN under Few Samples

Algorithm 1

AdCNN training process.

(1)	Initialize: discriminator with parameter , predictor with parameter .
(2)	for training iterations do
(3)	for iterations do
(4)	specimen m example from dataset
(5)	obtaining predicted data ,
(6)	update by descending along its gradient
(7)
(8)	end for
(9)	for iterations do
(10)	update by descending along its gradient
(11)
(12)	end for
(13)	end for