Projection
Projection
Let us have two different points a, b \in \mathbb{R}^n. Prove that the set of points which in the Euclidean norm are closer to the point a than to b make up a half-space. Is this true for another norm?
Find \pi_S (y) = \pi if S = \{x \in \mathbb{R}^n \mid \|x - x_c\| \le R \}, y \notin S
Find \pi_S (y) = \pi if S = \{x \in \mathbb{R}^n \mid c^T x = b \}, y \notin S
Find \pi_S (y) = \pi if S = \{x \in \mathbb{R}^n \mid Ax = b, A \in \mathbb{R}^{m \times n}, b \in \mathbb{R}^{m} \}, y \notin S
Illustrate the geometric inequality that connects \pi_S(y), y \notin S, x \in S, from which it follows that \pi_S(y) is a projection of the y point onto a convex set of S.
For which sets does the projection of the point outside this set exist? Unique?
Find \pi_S (y) = \pi if S = \{x \in \mathbb{R}^n \mid c^T x \ge b \}
Find \pi_S (y) = \pi if S = \{x \in \mathbb{R}^n \mid x = x_0 + X \alpha, X \in \mathbb{R}^{n \times m}, \alpha \in \mathbb{R}^{m}\}, y \in S
Let S \subseteq \mathbb{R}^n be a closed set, and x \in \mathbb{R}^n be a point not lying in it. Show that the projection in l_2 norm will be unique, while in l_\infty norm this statement is not valid.
Find the projection of the matrix X on a set of matrices of rank k, \;\;\; X \in \mathbb{R}^{m \times n}, k \leq n \leq m. In Frobenius norm and spectral norm.
Find a projection of the X matrix on a set of symmetrical positive semi-definite matrices of X \in \mathbb{R}^{n \times n}. In Frobenius norm and the scalar product associated with it.
Find the projection \pi_S(y) of point y onto the set S = \{x_1, x_2 \in \mathbb{R}^2 \mid \mid \vert x_1\vert + \vert x_2\vert = 1 \} in \| \cdot \|_1 norm. Consider the different positions of y.
Find \pi_S (y) = \pi, if S = \{x \in \mathbb{R}^n \mid \alpha_i \le x_i \le \beta_i, i = 1, \ldots, n \}.
Prove that projection is a nonexpansive operator, i.e. prove, that if S \in \mathbb{R}^{n} is nonempty, closed and convex set, then for any (x_{1}, x_{2}) \in \mathbb{R}^{n} \times \mathbb{R}^{n}
\lVert \pi_{S}(x_{2}) - \pi_{S}(x_{1}) \rVert_{2} \leq \lVert x_{2} - x_{1} \rVert_{2}