Definition: The vector space is called the direct sum of and if and are subspaces of such that and
We denote that is the direct sum of and by writing .
Now, suppose that is a vector space over a field and is a linear transformation with distinct eigenvalues . Show that , where is the eigenspace of , if and only if is diagonalizable.
Definition: The vector space is called the direct sum of and if and are subspaces of...
Suppose is a finite dimensional vector space. For hyperplanes in say they are linearly independent provided the corresponding linear subspaces in are linearly independent. Set and show that are linearly independent if and only if . (Hint: Write for and consider by ). We were unable to transcribe this imageWe were unable to transcribe this imageWe were unable to transcribe this imageWe were unable to transcribe this imageWe were unable to transcribe this imageWe were unable to transcribe this imageimnH...
Note: In the following, if is a set and both and are positive integers, then matrices with entries from . The problem below has many applications. If is a linear map from complex vector space to itself, and is an eigenvalue of , then is a simple eigenvalue of if . 1. Suppose is a vector space of dimension over field where you may assume that is either or , and let be a linear map from to . Show...
Font Styles Paragraph Definition 1: Given La linear transformation from a vector space V into itself, we say that is diagonalizable iff there exists a basis S relevant to which can be represented by a diagonal matrix D. Definition 2: If the matrix A represents the linear transformation L with respect to the basis S, then the eigenvalues of L are the eigenvalues of the matrix A. I Definition 3: If the matrix A represents the linear transformation L with...
QUESTION 8 Let V = U ㊥ W where V is a finite-dimensional vector space over a field F, and U and w are subspaces of V. Suppose U1 and U2 are subspaces of U and Wi and W2 are subspaces of W Show that QUESTION 8 Let V = U ㊥ W where V is a finite-dimensional vector space over a field F, and U and w are subspaces of V. Suppose U1 and U2 are subspaces of U...
Let V be a finite-dimensional complex vector space and let T from V to V be a linear transformation. Show that V is the direct sum of U and W where W and U are T-invariant subspaces and the restriction of T on U is nilpotent and the restriction of T on W is an isomorphism.
Let C be a curve of length L in space and a vector field of constant norm and tangent to C at each point of the curve. What is the work done by along C? Justify your answer. We were unable to transcribe this imageWe were unable to transcribe this image
Let V be a finite-dimensional vector space and let T L(V) be an operator. In this problem you show that there is a nonzero polynomial such that p(T) = 0. (a) What is 0 in this context? A polynomial? A linear map? An element of V? (b) Define by . Prove that is a linear map. (c) Prove that if where V is infinite-dimensional and W is finite-dimensional, then S cannot be injective. (d) Use the preceding parts to prove...
2 (5 points) Recalled that null space of a matrix A € Mnxn is defined as N(A) = {r € R” : Ar =0}. Now, the eigenspace of A corresponding to the eigenvalue 1 (denoted by Ex(A)) is defined as the nullspace of A-XI, that is, EX(A) = N(A – XI) = {v ER”: (A – XI)v = 0}. You should have three distinct eigenvalues in Problem 1 above. Let say there are li, 12, and 13. (i) Find the...
Let two variables and are bivariately normally distributed with mean vector component and and co-variance matrix shown below: . (a) What is the probability distribution function of joint Gaussian ? (Show it with and ) (b) What is the eigenvalues of co-variance matrix ? (c) Given the condition that the sum of squared values of each eigenvector are equal to 1, what is the eigenvectors of co-variance matrix ? please help with all parts! thank you! X1 We were unable...