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precalc stuff
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algasami committed Jun 21, 2024
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81 changes: 81 additions & 0 deletions app/content/posts/20240621-precalc-zh-tw.mdx
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---
title: 基礎微積分統整
description: 一個基礎微積分概念的統整。
slug: 20240621-precalc
lang: zh-tw
date: 2024-06-21
type: Post
tags:
- math
---

_這不完全與電腦科學有關,所以我沒有貼那個標籤:P。此文中函數只有單參數。_

## 極限

```math
\lim_{x \rightarrow a^{+}}{f(x)} = b
```

表示當$x$由右側趨近$a$時,$f$趨近$b$,這被稱為右極限。

```math
\lim_{x \rightarrow a^{-}}{f(x)} = b
```

表示當$x$由左側趨近$a$時,$f$趨近$b$,這被稱為左極限。當兩者相同時,即

```math
\lim_{x \rightarrow a^{+}}{f(x)} = \lim_{x \rightarrow a^{-}}{f(x)} = b
```

,表示當$x$趨近$a$,$f$趨近$b$,即

```math
\lim_{x \rightarrow a}{f(x)} = b
```

,這也代表$f$在$x=a$極限存在。

## 連續性

若函數在特定區間連續,則它必須先在其極限存在,若$f: R \rightarrow R, f(x)$是連續的,
其中$x \in [a,b]$,則它必須滿足下列事實:

1. 對所有$c \in [a,b]$,$f, x=c$必須極限存在。
2. 對所有$c \in [a,b]$,$f(c) = \lim_{x \rightarrow c}{f(c)}$

## 導數

一個函數對於特定參數的導數是這函數基於特定參數變化的函數,舉例來說,$f: R \rightarrow R, f(x)$對$x$的導數是$\frac{df}{dx}$。
它可以被定義為下

```math
\frac{df(x)}{dx} = \lim_{h \rightarrow 0}{\frac{f(x+h) - f(x)}{h}}
```

## 可微分

如果函數在區間中可微分,則它必須在區間中連續,若$f: R \rightarrow R, f(x)$可微,則它的導數是連續的,於是我們可以總結

```math
\text{可微分} \implies \text{連續} \implies \text{極限存在}
```

## IVT 介質定理

對於在區間$[a,b]$連續的函數$f$而言,它必須滿足下列事實$\forall c \in [\min(f(a), f(b)), \max(f(a), f(b)) ]$,
存在$r$滿足$f(r) = c \{r \in [a,b]\}$。

## 邊界定理

對於在區間$[a,b]的函數$f$,$U$表示上限集合(純量),$L$代表下限集合(純量)。
定義$v, \forall v \in [a, b]$,

```math
l \leq f(v) \leq u, l \in L, u \in U
```

## EVT 極值定理

當我們將上下限集合限制只有對應在區間中$f$的值,我們會得到極值定理,其中$L$與$U$個別被縮減成單一值$f(c)$與$f(d)$。
86 changes: 86 additions & 0 deletions app/content/posts/20240621-precalc.mdx
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---
title: Precalc Summary
description: This is a collection of precalculus concepts.
slug: 20240621-precalc
lang: en
date: 2024-06-21
type: Post
tags:
- math
---

_This isn't completely related to computer science so I didn't include the tag :P. Functions in this article only have
single variables._

## Limit

```math
\lim_{x \rightarrow a^{+}}{f(x)} = b
```

represents the fact that when $x$ approaches $a$ from right, $f$ approaches $b$, which is called a "right limit".

```math
\lim_{x \rightarrow a^{-}}{f(x)} = b
```

represents the fact that when $x$ approaches $a$ from left, $f$ approaches $b$, which is called a "left limit".
When both of them are the same, that is

```math
\lim_{x \rightarrow a^{+}}{f(x)} = \lim_{x \rightarrow a^{-}}{f(x)} = b
```

, we say that when $x$ approaches $a$, $f$ approaches $b$, which is

```math
\lim_{x \rightarrow a}{f(x)} = b
```

, this also shows that $f$ has a limit at $x=a$.

## Continuity

For a function to be continuous in a certain interval, it must first have limit in that interval. If $f: R \rightarrow R, f(x)$ is
continuous given $x \in [a,b]$, then it must satisfy the following facts:

1. For all $c$ in $[a,b]$, $f$ at $x=c$ must have a limit that is defined.
2. For all $c$ in $[a,b]$, $f(c) = \lim_{x \rightarrow c}{f(c)}$

## Derivative

A function's derivative with respect to a specific variable is the function's change regarding the change of the specified variable.
For example, the derivative of $f: R \rightarrow R, f(x)$ regarding $x$ is $\frac{df}{dx}$.
It can be defined like this:

```math
\frac{df(x)}{dx} = \lim_{h \rightarrow 0}{\frac{f(x+h) - f(x)}{h}}
```

## Differentiable

When a function is differentiable in a certain interval, it must first be continuous in that interval. If $f: R \rightarrow R, f(x)$
is differentiable, then its derivative must be continuous, so finally we can say that

```math
\text{Differentiable} \implies \text{Continuous} \implies \text{Limit Existing}
```

## IVT Intermediate Value Theorem

For a continuous function $f$ in interval $[a,b]$, it must satisfy the following fact: $\forall c \in [\min(f(a), f(b)), \max(f(a), f(b)) ]$,
there exists at least one $r$ that fulfills $f(r) = c \{r \in [a,b]\}$.

## Boundedness Theorem

For a function $f$ in interval $[a,b]$, $U$ denotes the set of upper bounds (scalar) and $L$ denotes the set of lower bounds (scalar).
Define $v, \forall v \in [a, b]$,

```math
l \leq f(v) \leq u, l \in L, u \in U
```

## EVT Extreme Value Theorem

When we limit the upper bound set and the lower bound set to only include values that exist as $f$'s output, we get EVT,
where $L$ and $U$ are each reduced respectively to a single value, $f(c)$ and $f(d)$.

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