第二步，识别阶段，采用了一种亲笔最近相邻算法（HNN）。首先自学习预处理得到的数据，并得到对象的总的特征。再通过HNN算法来识别对象。
The second step (recognition) is achieved by using a holographic nearest-neighbor algorithm (HNN), in which vectors obtained in the preprocessing step are used as inputs to it .
新算法通过定义反映梯度变化的真假函数，能够充分考虑到未知数据网格点各象限最近相邻点的取值情况。
By this algorithm, the true and false membership functions reflecting the change of gradient are redefined. The known point is reflected with those functions.
新算法通过定义反映梯度变化的真假函数，能够充分考虑到未知数据网格点各象限最近相邻点的取值情况。
By this algorithm, the true and false membership functions reflecting the change of gradient are redefined. The known point is reflected with those functions.
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