Cauchy-Schwartz inequality • If (a1, a2, ..., an) and (b1, b2, ..., bn) are sequences of real numbers, then (E 7)(E b}) > (E-1 a;b;)² • with equality if and only if there exists some real number r such that (a1, a2, . .., an) = r(bị , b2, ... , bn) • If u = (a1, a2, ..., an) and v = (b1, b2, ..., bn), then this inequality says that |u · v| < || u||| v|| There are many ways to prove this > First note that 2(Σ 1f)(ΣΗ) -2(ΣΗabi) E Ei(a;b; – a;b;)² i=1 |

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**Cauchy-Schwartz Inequality**

**Definition:**
If \((a_1, a_2, \ldots, a_n)\) and \((b_1, b_2, \ldots, b_n)\) are sequences of real numbers, then the Cauchy-Schwartz inequality states that:

\[
\left(\sum_{i=1}^n a_i^2\right)\left(\sum_{i=1}^n b_i^2\right) \geq \left(\sum_{i=1}^n a_i b_i\right)^2
\]

with equality if and only if there exists some real number \(r\) such that \((a_1, a_2, \ldots, a_n) = r(b_1, b_2, \ldots, b_n)\).

**Vector Notation:**
If \(\mathbf{u} = (a_1, a_2, \ldots, a_n)\) and \(\mathbf{v} = (b_1, b_2, \ldots, b_n)\), then this inequality can also be expressed as:

\[
|\mathbf{u} \cdot \mathbf{v}| \leq \|\mathbf{u}\| \|\mathbf{v}\|
\]

**Proof Outline:**
There are many ways to prove this inequality. 

1. Note that:

\[
2\left(\sum_{i=1}^n a_i^2\right)\left(\sum_{i=1}^n b_i^2\right) - 2\left(\sum_{i=1}^n a_i b_i\right)^2 = \sum_{i=1}^n \sum_{j=1}^n (a_i b_j - a_j b_i)^2
\]

2. Recognize that:

\[
\sum_{i=1}^n \sum_{j=1}^n (a_i b_j - a_j b_i)^2 \geq 0
\]

This follows by the trivial inequality that squares are non-negative.

3. By dividing by 2 and adding the second sum to both sides, we obtain:

\[
\left(\sum_{i=1}^n a_i^2\right)\left(\sum_{i=1}
Transcribed Image Text:**Cauchy-Schwartz Inequality** **Definition:** If \((a_1, a_2, \ldots, a_n)\) and \((b_1, b_2, \ldots, b_n)\) are sequences of real numbers, then the Cauchy-Schwartz inequality states that: \[ \left(\sum_{i=1}^n a_i^2\right)\left(\sum_{i=1}^n b_i^2\right) \geq \left(\sum_{i=1}^n a_i b_i\right)^2 \] with equality if and only if there exists some real number \(r\) such that \((a_1, a_2, \ldots, a_n) = r(b_1, b_2, \ldots, b_n)\). **Vector Notation:** If \(\mathbf{u} = (a_1, a_2, \ldots, a_n)\) and \(\mathbf{v} = (b_1, b_2, \ldots, b_n)\), then this inequality can also be expressed as: \[ |\mathbf{u} \cdot \mathbf{v}| \leq \|\mathbf{u}\| \|\mathbf{v}\| \] **Proof Outline:** There are many ways to prove this inequality. 1. Note that: \[ 2\left(\sum_{i=1}^n a_i^2\right)\left(\sum_{i=1}^n b_i^2\right) - 2\left(\sum_{i=1}^n a_i b_i\right)^2 = \sum_{i=1}^n \sum_{j=1}^n (a_i b_j - a_j b_i)^2 \] 2. Recognize that: \[ \sum_{i=1}^n \sum_{j=1}^n (a_i b_j - a_j b_i)^2 \geq 0 \] This follows by the trivial inequality that squares are non-negative. 3. By dividing by 2 and adding the second sum to both sides, we obtain: \[ \left(\sum_{i=1}^n a_i^2\right)\left(\sum_{i=1}
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