January 26, 2010
\documentclass[12pt]{article} \pagestyle{empty} \usepackage{amsmath,amssymb,amsthm} \usepackage[papersize={100mm, 130mm}, text={90mm, 120mm}]{geometry} % order: \order[st]{1}, \order{k} \newcommand{\order}[2][th]{\ensuremath{{#2}^{\mathrm{#1}}}} \newcommand{\Abf}{\ensuremath{\mathbf{A}}} \newcommand{\Bbf}{\ensuremath{\mathbf{B}}} \newcommand{\fpd}[2]{\ensuremath{\frac{\partial{#1}}{\partial{#2}}}} \begin{document} We prove the product rule of matrix derivative. \begin{equation*} \fpd{}{t}\Abf\Bbf = \fpd{\Abf}{t}\Bbf + \Abf\fpd{\Bbf}{t} \end{equation*} Let $[\boldsymbol{*}]_{ij}$ be the element of $\boldsymbol{*}$ in the $\order{i}$ row and $\order{j}$ column. Then it's enough to prove \begin{equation*} \fpd{}{t}\left[\Abf\Bbf\right]_{ij} = \left[\fpd{\Abf}{t}\Bbf + \Abf\fpd{\Bbf}{t}\right]_{ij.} \end{equation*} Note that $[\Abf\Bbf]_{ij=}=\sum_ka_{ij}b_{kj}$. \begin{align*} \fpd{}{t}[\Abf\Bbf]_{ij} &= \fpd{}{t}\sum_ka_{ik}b_{ij} \\ &= \sum_k\left( \fpd{a_{ik}}{t}b_{kj} + a_{ik}\fpd{b_{kj}}{t} \right) \\ &= \sum_k\left(\fpd{a_{ik}}{t}b_{kj}\right) + \sum_k\left(a_{ik}\fpd{b_{kj}}{t}\right) \\ &= \left[\fpd{\Abf}{t}\Bbf\right]_{ij} + \left[\Abf\fpd{\Bbf}{t}\right]_{ij} \\ &= \left[ \fpd{\Abf}{t}\Bbf + \Abf\fpd{\Bbf}{t} \right]_{ij} \end{align*} \end{document}
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