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The recent deep learning methods can offer state-of-the-art performance for Monaural Singing Voice Separation (MSVS). In these deep methods, the recurrent neural network (RNN) is widely employed. This work proposes a novel type of Deep RNN (DRNN), namely Proximal DRNN (P-DRNN) for MSVS, which improves the conventional Stacked RNN (S-RNN) by introducing a novel interlayer structure. The interlayer structure is derived from an optimization problem for Monaural Source Separation (MSS).