By using the atom function, you get an atom object that is a wrapper around the initial value.
利用atom函数，可获得作为初始值包装的atom对象。
Through cooperation with psychologist, design questionnaire, initial investigation, get the standard value of every term, and then transfer to computer system to processing systematically.
通过和心理学专家合作，设计问卷、经初步调查获得各项常规指标后，转换到计算机系统进行系统化处理。
Traditional K-Means algorithm is sensitive to the initial centers and easy to get stuck at locally optimal value.
传统K均值算法对初始聚类中心敏感，聚类结果随不同的初始输入而波动，容易陷入局部最优值。
So firstly to get a better estimation of parameter using iterate inversion on wide scale, then using this estimation as initial value on mini scale till to get global optimum of original problem.
因此可先在粗尺度上迭代反演，得到一个较好的参数估计，再将这个估计作为较精细尺度的初值进行反演，直至原问题的全局最优解。
So firstly to get a better estimation of parameter using iterate inversion on wide scale, then using this estimation as initial value on mini scale till to get global optimum of original problem.
因此可先在粗尺度上迭代反演，得到一个较好的参数估计，再将这个估计作为较精细尺度的初值进行反演，直至原问题的全局最优解。
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