Unit 10: Linearization - Harvard University
https://people.math.harvard.edu/~knill/teaching/summer2022/handouts/lecture10.pdf
Web10.12. Linearization is just the first step for more accurate approximations. One could do quadratic approximations for example. In one dimension, one has Q(x) = f(a)+f′(a)(x−a)+f′′(a)(x−a)2 2!. In two dimensions, this becomes Q(x,y) = L(x,y)+ H (a,b)[x−a,y−b] ·[x−a,y−b]/2, where H is the Hessian matrix H(a,b) = f xx(a,b) f ...
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