Laplacian

Laplacian

参考文献

https://en.wikipedia.org/wiki/Second_derivative

拉普拉斯是将二阶导数推广到高维空间的一种方式。
Another common generalization of the second derivative is the Laplacian. This is the differential operator 2 \nabla^{2} defined by
2 f = 2 f x 2 + 2 f y 2 + 2 f z 2 \nabla^{2} f=\frac{\partial^{2} f}{\partial x^{2}}+\frac{\partial^{2} f}{\partial y^{2}}+\frac{\partial^{2} f}{\partial z^{2}}

The Laplacian of a function is equal to the divergence of the gradient and the trace of the Hessian matrix.

什么是Hessian matrix?什么是梯度的divergence?
先不研究。

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转载自blog.csdn.net/ChenglinBen/article/details/91973666