Chapter 5: Problem 3
Show that the Chebyshev polynomials have the following properties: (a) \(2 T_{m}(x) T_{n}(x)=T_{m+n}(x)+T_{m-n}(x),\) for \(m>n\) (b) \(T_{m}\left(T_{n}(x)\right)=T_{m n}(x)\)
/*! This file is auto-generated */ .wp-block-button__link{color:#fff;background-color:#32373c;border-radius:9999px;box-shadow:none;text-decoration:none;padding:calc(.667em + 2px) calc(1.333em + 2px);font-size:1.125em}.wp-block-file__button{background:#32373c;color:#fff;text-decoration:none}
Learning Materials
Features
Discover
Chapter 5: Problem 3
Show that the Chebyshev polynomials have the following properties: (a) \(2 T_{m}(x) T_{n}(x)=T_{m+n}(x)+T_{m-n}(x),\) for \(m>n\) (b) \(T_{m}\left(T_{n}(x)\right)=T_{m n}(x)\)
All the tools & learning materials you need for study success - in one app.
Get started for free
In \(C[0,1],\) with inner product defined by \((3),\) compute (a) \(\left\langle e^{x}, e^{-x}\right\rangle\) (b) \(\langle x, \sin \pi x\rangle\) (c) \(\left\langle x^{2}, x^{3}\right\rangle\)
Let $$\begin{array}{c} S=\\{1 / \sqrt{2}, \cos x, \cos 2 x, \ldots, \cos n x, \\ \sin x, \sin 2 x, \ldots, \sin n x\\} \end{array}$$ Show that \(S\) is an orthonormal set in \(C[-\pi, \pi]\) with inner product defined by (2)
Consider the vector space \(\mathbb{R}^{n}\) with inner product \(\langle\mathbf{x}, \mathbf{y}\rangle=\mathbf{x}^{T} \mathbf{y} .\) Show that, for any \(n \times n\) matrix \(A\) (a) \(\langle A \mathbf{x}, \mathbf{y}\rangle=\left\langle\mathbf{x}, A^{T} \mathbf{y}\right\rangle\) (b) \(\left\langle A^{T} A \mathbf{x}, \mathbf{x}\right\rangle=\|A \mathbf{x}\|^{2}\)
Let \(\mathbf{x}\) and \(\mathbf{y}\) be linearly independent vectors in \(\mathbb{R}^{n}\) and let \(S=\operatorname{Span}(\mathbf{x}, \mathbf{y}) .\) We can use \(\mathbf{x}\) and \(\mathbf{y}\) to define a matrix \(A\) by setting $$A=\mathbf{x y}^{T}+\mathbf{y} \mathbf{x}^{T}$$ (a) Show that \(A\) is symmetric. (b) Show that \(N(A)=S^{\perp}\) (c) Show that the rank of \(A\) must be 2
In \(\mathbb{R}^{n}\) with inner product $$\langle\mathbf{x}, \mathbf{y}\rangle=\mathbf{x}^{T} \mathbf{y}$$ derive a formula for the distance between two vectors \(\mathbf{x}=\left(x_{1}, \ldots, x_{n}\right)^{T}\) and \(\mathbf{y}=\left(y_{1}, \ldots, y_{n}\right)^{T}\)
What do you think about this solution?
We value your feedback to improve our textbook solutions.