diff --git a/semester3/analysis-ii/cheat-sheet-jh/analysis-ii-cheat-sheet.pdf b/semester3/analysis-ii/cheat-sheet-jh/analysis-ii-cheat-sheet.pdf index 1571a40..a7e7d5f 100644 Binary files a/semester3/analysis-ii/cheat-sheet-jh/analysis-ii-cheat-sheet.pdf and b/semester3/analysis-ii/cheat-sheet-jh/analysis-ii-cheat-sheet.pdf differ diff --git a/semester3/analysis-ii/cheat-sheet-jh/parts/vectors/differentiation/02_differential.tex b/semester3/analysis-ii/cheat-sheet-jh/parts/vectors/differentiation/02_differential.tex index 7f4b9f0..8b77900 100644 --- a/semester3/analysis-ii/cheat-sheet-jh/parts/vectors/differentiation/02_differential.tex +++ b/semester3/analysis-ii/cheat-sheet-jh/parts/vectors/differentiation/02_differential.tex @@ -34,7 +34,17 @@ This implies that most elementary functions are differentiable.\\ \compactproposition{Chain Rule} For $X \subseteq \R^n$ and $Y \subseteq \R^m$ both open and $f: X \rightarrow Y$ and $g : Y \rightarrow \R^p$ are both differentiable. Then $g \circ f$ is differentiable on $X$ and for any $x \in X$, its differential is given by $\dx (g \circ f)(x_0) = \dx g(f(x_0)) \circ \dx f(x_0)$. -The Jacobi matrix is $J_{g \circ f}(x_0) = J_g(f(x_0)) J_f(x_0)$ (RHS is a matrix product, i.e. multiply rows of first with cols of second matrix)\\ +The Jacobi matrix is $J_{g \circ f}(x_0) = J_g(f(x_0)) J_f(x_0)$ (RHS is a matrix product, i.e. multiply rows of first with cols of second matrix) + +\bi{For tasks} where we are given the value of a gradient at a certain point, as well as the function +(could not be explicitly given, but could instead be individually for each component), +we can compute the partial derivative using the chain rule as follows: +$\frac{\partial g}{\partial \phi} = \frac{\partial g}{\partial x} \cdot \frac{\partial x}{\partial \phi} ++ \frac{\partial g}{\partial y} \cdot \frac{\partial y}{\partial \phi} + \frac{\partial g}{\partial z} \cdot \frac{\partial z}{\partial \phi}$ +where all $\frac{\partial g}{\partial x}$, etc are known from the gradient and the other elements can be computed quickly from the known equations. + +Finally, evaluate $\frac{\partial g}{\partial \phi}$ at the required points and compute the result. + % ──────────────────────────────────────────────────────────────────── \setLabelNumber{all}{11} \compactdef{Tangent space} The graph of the affine linear approximation $g(x) = f(x_0) + u(x - x_0)$, or the set