In this paper, the continuous time recurrent neural network is proposed to solve the functional minimization problem, which is often involved in estimation and control.
针对信息科学和控制理论中经常涉及的一类泛函极值问题，提出基于连续回归神经网络的求解方法。
Exploiting the characteristics of the sun basis image, the computation of sunlight and skylight of every frames is finally reduced to a minimization problem which can be solved in real time.
然后，通过对太阳光基图像的特点进行分析，将太阳光和天空光入射光强的求解归结为一个可实时求解的能量最小化问题。
Exploiting the characteristics of the sun basis image, the computation of sunlight and skylight of every frames is finally reduced to a minimization problem which can be solved in real time.
然后，通过对太阳光基图像的特点进行分析，将太阳光和天空光入射光强的求解归结为一个可实时求解的能量最小化问题。
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