在最大熵等统计机器学习模型当中，特征函数的选择可以说是对系统整体性能影响最大的部分。

The feature functions were reckoned as the most important part of the maximum entropy model which could affact the last result of system.

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在许多盲信号源分离算法中，大多需要选择合适的非线性函数或者需要计算信号的高阶统计量。

In many algorithms for blind source separation, most of them must select nonlinear function or compute high-order statistical values.

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