针对多模型方法中子模型数量过多的问题，提出一种基于模型集在线优化方案的多模型自适应控制算法，并对其实时性进行讨论。
Focus on the question of many sub models in traditional SMM, a SMM adaptive control based on online optimization method of model set is proposed.
这就允许依据网上脉冲数量多少而不断改变频率的“自适应”中断。
This allows for "adaptive" interrupts that vary in frequency depending on the net's burst volume.
通过把原始图像自适应分解成有限数量的子图像，图像的细节能清晰地被分解出来，这在数字图像处理中有很重要的意义。
The clear image details have been extracted by using the method to adaptively decompose a digital image into a finite number of sub-images. That is very important for digital image processing.
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