Advanced Calculus: Difference between revisions

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Advanced Calculus as taught in [https://bookstore.ams.org/amstext-5/ Fitzpatrick's book].
Advanced Calculus as taught in [https://bookstore.ams.org/amstext-5/ Fitzpatrick's book].
 
This is content covered in MATH410 and MATH411 at UMD.
 


==Sequences==
==Sequences==
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===Closed===
===Closed===
The folllowing definitions of Closed Sets are equivalent.
The folllowing definitions of Closed Sets are equivalent.
* (Order)
* (Order) A set <math>S</math> is open if for every number <math>x \in S</math>, there is an epsilon <math>\epsilon > 0</math> such that the epsilon ball is a subset of s: <math>\{ y | d(x, \epsilon) \} \subset S</math>. The compliment of an open set is closed.
* (Sequences) A set <math>S</math> is clsoed if it contains all its limit points. That is <math>\forall \{x_i\} \subseteq S</math>, <math>\{x_i\} \rightarrow x_0 \implies x_0 \in S</math>.
* (Sequences) A set <math>S</math> is closed if it contains all its limit points. That is <math>\forall \{x_i\} \subseteq S</math>, <math>\{x_i\} \rightarrow x_0 \implies x_0 \in S</math>.
* (Topology)


; Notes
* Union of infinitely many closed sets can be open.
* Intersection of infinitely many open sets can be closed.
* <math>\{\}</math> and <math>\mathbb{R}</math> are both open and closed


Union of infinitely many closed sets can be open.
Intersection of infinitely many open sets can be closed.
===Compact===
===Compact===
Compactness is a generalization of closed and bounded.<br>
;Definitions
* (Sequence) A set is sequentially compact if for every sequence from the set, there exists a subsequence which converges to a point in the set.
* (Topology) A set is compact if for every covering by infinitely many open sets, there exists a covering by a finite subset of the open sets.
;Notes
* A set is sequentially compact iff it is closed and bounded
===Metric Space===
===Metric Space===


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==Implicit Function Theorem==
==Implicit Function Theorem==
==Line and Surface Integrals==
==Line and Surface Integrals==
==Derivatives with respect to vectors and matrices==
Not typically covered in undergraduate analysis and calculus classes but necessary for machine learning.<br>
See [https://www.math.uwaterloo.ca/~hwolkowi/matrixcookbook.pdf The Matrix Cookbook]
* <math>\partial_{x} x^t x = \partial_{x} \operatorname{Tr}(x^t x) = \operatorname{Tr}( (\partial x)^t x + x^t (\partial x)) = 2 * \operatorname{Tr}(x^t (\partial x)) = 2x</math>