Proving Schwarz's & Triangle Inequalities for Infinite Sequences

In summary, the Schwarz's inequality and the triangle inequality for infinite sequences state that if the sums of the absolute values of two sequences are convergent, then the sum of the absolute values of their elements is less than or equal to the product of the sums of their absolute values. This can be proven using mathematical induction and the Cauchy-Schwarz inequality.
  • #1
Dustinsfl
2,281
5
I am not getting anywhere with this problem.

Prove the Schwarz's and the triangle inequalities for infinite sequences:
If
$$
\sum_{n = -\infty}^{\infty}|a_n|^2 < \infty\quad\text{and}\quad
\sum_{n = -\infty}^{\infty}|b_n|^2 < \infty
$$
then
$\displaystyle\left(\sum_{n = -\infty}^{\infty}|a_n + b_n|^2\right)^{1/2}\leq \left(\sum_{n = -\infty}^{\infty}|a_n|^2\right)^{1/2}\left(\sum_{n = -\infty}^{\infty}|b_n|^2\right)^{1/2}$.
 
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  • #2
dwsmith said:
I am not getting anywhere with this problem.

Prove the Schwarz's and the triangle inequalities for infinite sequences:
If
$$
\sum_{n = -\infty}^{\infty}|a_n|^2 < \infty\quad\text{and}\quad
\sum_{n = -\infty}^{\infty}|b_n|^2 < \infty
$$
then
$\displaystyle\left(\sum_{n = -\infty}^{\infty}|a_n + b_n|^2\right)^{1/2}\leq \left(\sum_{n = -\infty}^{\infty}|a_n|^2\right)^{1/2}\left(\sum_{n = -\infty}^{\infty}|b_n|^2\right)^{1/2}$.

Hi dwsmith, :)

You can generalize the triangle inequality for a finite sequence of terms using mathematical induction.

\[\left|\sum_{k=1}^{n}a_k\right|\leq\sum_{k=1}^{n}|a_k|\]

If \(\displaystyle\sum_{k=1}^{\infty}|a_k|\) is convergent,

\[\left|\sum_{k=1}^{n}a_k\right|\leq \sum_{k=1}^{n}|a_k|\leq \sum_{k=1}^{\infty}|a_k|\]

Now \((z_n)=\displaystyle\left|\sum_{k=1}^{n}a_k\right|\) is a convergent sequence. By Theorem 3.2.6 (Page 66) of Introduction to Real Analysis by Robert G. Bartle we get,

3.2.6 Theorem: If \(X=(x_{n})\) is a convergent sequence and if \(a\leq x_{n}\leq b\) for all \(n\in\mathbb{N}\), then \(a\leq \lim(x_{n})\leq b\).

\[\left|\sum_{k=1}^{\infty}a_k\right|\leq \sum_{k=1}^{\infty}|a_k|\]

There are various approaches in proving the Cauchy-Schwarz inequality some of which are given >>here<<.

Kind Regards,
Sudharaka.
 

FAQ: Proving Schwarz's & Triangle Inequalities for Infinite Sequences

What is Schwarz's Inequality for Infinite Sequences?

Schwarz's Inequality for Infinite Sequences is a mathematical principle that states the inner product of two infinite sequences is less than or equal to the product of their norms. In simpler terms, it means that the dot product of two infinite sequences cannot be larger than the product of their magnitudes.

How is Schwarz's Inequality for Infinite Sequences proven?

Schwarz's Inequality for Infinite Sequences is proven using the Cauchy-Schwarz Inequality, which states that the dot product of two vectors is less than or equal to the product of their magnitudes. By applying this principle to infinite sequences, Schwarz's Inequality can be derived.

What is the Triangle Inequality for Infinite Sequences?

The Triangle Inequality for Infinite Sequences is a mathematical principle that states the absolute value of the sum of two infinite sequences is less than or equal to the sum of the absolute values of the individual sequences. In simpler terms, it means that the magnitude of the sum of two infinite sequences cannot be larger than the sum of the magnitudes of the individual sequences.

How is the Triangle Inequality for Infinite Sequences proven?

The Triangle Inequality for Infinite Sequences is proven using the Cauchy-Schwarz Inequality in a similar way to the proof of Schwarz's Inequality. By applying the Cauchy-Schwarz Inequality to the sum of two infinite sequences, the Triangle Inequality can be derived.

What are the applications of Schwarz's and Triangle Inequalities for Infinite Sequences?

Schwarz's and Triangle Inequalities for Infinite Sequences have various applications in mathematics and physics. They are used in the study of series and convergence of sequences, as well as in the theory of Hilbert spaces. They also have applications in solving optimization problems and in signal processing.

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