- #1
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Consider a function ##f : U \subseteq \mathbb{R}^{n} -> \mathbb{R}## that is an element of ##C^{2}## which has an minimum in ##p \in U##.
According to Taylor's theorem for multiple variable functions, for each ##h \in U## there exists a ##t \in ]0,1[## such that :
##f(p+h)-f(p) = h^{T}.D^{2}(p+th).h##
Where ##D^{2}## is the Hessian or the matrix with the mixed partial derivatives, ##D^{2}(p+th)## means it's not in point p. I already assume it's a minimum so the Jacobian matrix that should be there is 0.
Now I should take a limit and somehow show that in both cases where p is a strict or not strict minimum that is ##f(p)<f(x)## of ##f(p)\leq f(x)## that in both cases ##D^{2}## will be negative semi definite. Can someone help me finish/understand this final step formally? Because I'm not sure about how a limit will work in the equation above, the left term just goes to zero.
According to Taylor's theorem for multiple variable functions, for each ##h \in U## there exists a ##t \in ]0,1[## such that :
##f(p+h)-f(p) = h^{T}.D^{2}(p+th).h##
Where ##D^{2}## is the Hessian or the matrix with the mixed partial derivatives, ##D^{2}(p+th)## means it's not in point p. I already assume it's a minimum so the Jacobian matrix that should be there is 0.
Now I should take a limit and somehow show that in both cases where p is a strict or not strict minimum that is ##f(p)<f(x)## of ##f(p)\leq f(x)## that in both cases ##D^{2}## will be negative semi definite. Can someone help me finish/understand this final step formally? Because I'm not sure about how a limit will work in the equation above, the left term just goes to zero.