Furthermore, the condition of the faster convergence of the proposed algorithm comparing with the conventional gradient descent algorithm with momentum term is derived.
进而给出了在梯度一定的条件下，所提出的算法比传统的带动量的梯度法收敛快的条件。
Simulation results show that the natural gradient approach has faster convergence speed and better separation performance than the conventional gradient based algorithm.
仿真结果显示，自然梯度算法比传统梯度算法收敛速度更快，分离效果更好。
Conventional high gradient magnetic separators are easy to be blocked in separation pro-cess with large water consumption, resulting in lower separating efficiency.
传统高梯度磁选机在分选过程中容易堵塞，以致分选效率不高，且耗水量大。
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