Advanced Engineering Mathematics
10th Edition
ISBN: 9780470458365
Author: Erwin Kreyszig
Publisher: Wiley, John & Sons, Incorporated
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- Assume that V is a finite dimensional real inner product space and T = L(V) and self- adjoint. Show that T²+bT+cI is invertible if b² < 4c. Additionally, provide an example of a real inner product space V and T € L(V) and real numbers b, c with b² < 4c such that T² +bT+cI is not invertible. (Hint: The example shows that the hypothesis that T is self-adjoint is necessary, even for real vector spaces.)arrow_forwardLet p(x) = a, +a,x+ a,x* +a,x' and g(x) = 6, + 6x+ 6,x + b,x' be vectors in P, with the standard inner product space on P,defined by = a,b, + a,b, + a,b, + a,b;. a) Find the distance between fand g f - | angle of f(x) and h(x) b) Use the Gram-Schmidt process to form an orthogonal set for the functions f(x) = 1-x-x* + 2x', g(x) = -2+ 2x - x and h(x) = x - x* + 2xarrow_forward22. Show that there do not exist scalars c₁, c₂, and c² such that c₁(1,0, 1,0) + c₂(1, 0, −2, 1) + c3(2, 0, 1, 2) = (1, -2, 2, 3)arrow_forward
- 11. Let (V, (, )) be a complex inner product space. For vectors v, w, set (v, w) R = ¹/[(v, w)+(w, v)]. Consider V to be a real vector space. Is (V, (, )R) an inner product space? Support your answer with a proof.arrow_forwardShow that if X and Y Hausdorff spaces, then so is the product space X × Y. arearrow_forwardConsider the space P₂ which is the vector space of polynomials of degree not greater than two. We define the inner product in P2 according to the formula -Lpqdz. Also, consider the following two vectors (a) Calculate the inner product (p, q) (b) Calculate the distance between vectors p and q. (c) Calculate the norm ||q||, of vector q. (p, q) (e) For vectors p and q, calculate the inner product (p - q, p + 2q). p = x² = 5x + 1, q= −2x²+x. (d) For vectors p and q, find the orthogonal projection of p on q (projp). Your answer must be a vector from P2, i.e. a polynomial of degree 2 or less.arrow_forward
- 3) Let V = {(5), a, b e R*} note R* = {r € R]r > 0} ). Define “addition" on V by G) +C)=G) Further, define "scalar multiplication for ce R by c () = (). Prove that V is a (b,b2 vector space over R by showing that the set is closed under all the scalar multiplication and vectors addition and that all the axioms pertaining to these operations hold.arrow_forwardLet V be an inner product space with dim V = 2, and suppose that L = {u+v, u+2v} is a linearly independent subset of V. Prove that if 1 is orthogonal to both u and v, then 1 = assume that V contains tuples. Also, be sure to use only results from our linear algebra course in your proof.) 0. (Note: You Imay notarrow_forward
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