利用一个分段学习方案可保证学习控制总在有效线性近似区域内进行。
A segmented learning scheme is proposed to keep the learning only in the linear approximation region.
针对复杂背景及目标的分形特性差异，提取图像四个方向的灰度梯度，选择最小梯度大于阈值的区域进行平滑滤波，最后对分维参数进行分段线性拉伸。
Aiming at characteristic differences of background and target, four-direction gradient is extracted out and areas with large gradient are smoothed by a linear threshold filter.
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