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A decoupled relative Newton algorithm is proposed for the matrix optimization problem encountered in blind source separation (BSS) and independent component analysis (ICA). The algorithm decouples the matrix optimization problem into a series of small vector optimization problems. The nonsingularity of separation matrix enables a simple and efficient relative Newton learning algorithm for the vector optimization problems. Simulation results are reported to confirm its superior performance.