中文说明：
黑塞矩阵（Hessian Matrix），又译作海森矩阵、海瑟矩阵、海塞矩阵等，是一个多元函数的二阶偏导数构成的方阵，描述了函数的局部曲率。黑塞矩阵最早于19世纪由德国数学家Ludwig Otto Hesse提出，并以其名字命名。黑塞矩阵常用于牛顿法解决优化问题，利用黑塞矩阵可判定多元函数的极值问题。在工程实际问题的优化设计中，所列的目标函数往往很复杂，为了使问题简化，常常将目标函数在某点邻域展开成泰勒多项式来逼近原函数，此时函数在某点泰勒展开式的矩阵形式中会涉及到黑塞矩阵。
English Description：
Hessian matrix, also translated as Hessian matrix, Hessian matrix, Hessian matrix, etc., is a square matrix composed of the second partial derivatives of multivariate functions, which describes the local curvature of functions. Hesse matrix was first proposed by Ludwig Otto Hesse, a German mathematician, in the 19th century. Hesse matrix is often used in Newton method to solve optimization problems, and it can be used to determine the extremum of multivariate function. In the optimization design of practical engineering problems, the listed objective function is often very complex. In order to simplify the problem, the objective function is often expanded into Taylor Polynomials in the neighborhood of a certain point to approximate the original function. At this time, the Hessian matrix is involved in the matrix form of Taylor expansion of a certain point.