definition of Markov matrix
and related theorems are showed below
Definition 8.7 Let A = (aij) A satisfies R(n, n) so that aij-0 for i, j = I, . . . , n. If j-1 243 8.4 Markov matrices that is, the components of each row vector in A sum up to 1, then A is called a Markov or stochastic matrix. If there is an integer such that A is a positive matrix, then A is called a regular Markov or regular stochastic matrix. A few immediate consequences follow directly from the definition of a Markov matrix and are stated below.
Theorem 8.8 Let A (aij E R(n, n) be a Markov matrix. Then 1 is an eigenvalue of A which enjoys the following properties. (1) The vector(1, ..., 1)' ER" is an eigenvector of A associated to the eigenvalue1 (2) Any eigenvalue λ E C of A satisfies (8.4.2)
Theorem 8.9 IfA e R(n, ) is a regular Markov matrix, then the eigenvalue 1 of A is the dominant eigenvalue of A which satisfies the following properties. (1〉 The absolute value of any other eigenvalue λ E C of A s less than 1. That is, Al1 (2) 1 is a simple root of the characteristic polynomial of A
Homework Answers
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definition of Markov matrix and related theorems are showed below 8.4.2Show that the matrix (8.4.21) is a Markov matrix which is not regular. Is A stable? Definition 8.7 Let A = (aij) A satisfies R(n...
2 is the question Question 4 [35 marks in total] An n xn matrix A is...
2 is the question
Question 4 [35 marks in total] An n xn matrix A is called a stochastic matriz if it satisfies two conditions: (i) all entries of A are non-negative; and (ii) the sum of entries in each column is one. If the (i, j) entry of A is denoted by aij for i,j e {1, 2, ..., n}, then A is a stochastic matrix when aij > 0 for all i and j and in dij =...
Material: 8.3.2 Consider the matrix (1 2 3 A-2 3 1 (8.3.28) (i) Use (8.3.27) to find the dominant eigenvalue of A. (ii) Check to see that u-(1 , I , î ), is a positive eigenvector of A. Use 11 and T...
Material:
8.3.2 Consider the matrix (1 2 3 A-2 3 1 (8.3.28) (i) Use (8.3.27) to find the dominant eigenvalue of A. (ii) Check to see that u-(1 , I , î ), is a positive eigenvector of A. Use 11 and Theorem 8.6 to find the dominant eigenvalue of A and confirm that this is exactly what was obtained in part 0) obtained in part (i) or(ii ii) Compute all the eigenvalues of A directly and confirm the result...
A1. Let (A, B, C, D) be a SISO system in which A is a (n x n) complex matrix and B a (n x 1) column vector, let -1 V =...
A1. Let (A, B, C, D) be a SISO system in which A is a (n x n) complex matrix and B a (n x 1) column vector, let -1 V = {£ajA*B: aj e C; j= 0, ...,n- (i) Show that V is a complex vector space. (ii) Show that V has dimension one, if and only if B is an eigenvector of A AX for X E V. Show that S defines a linear map from S: V...
Review 4: question 1 Let A be an n x n matrix. Which of the below...
Review 4: question 1 Let A be an n x n matrix. Which of the below is not true? A. A scalar 2 is an eigenvalue of A if and only if (A - 11) is not invertible. B. A non-zero vector x is an eigenvector corresponding to an eigenvalue if and only if x is a solution of the matrix equation (A-11)x= 0. C. To find all eigenvalues of A, we solve the characteristic equation det(A-2) = 0. D)....
Question 4 [35 marks in totalj An n x n matrix A is called a stochastic...
Question 4 [35 marks in totalj An n x n matrix A is called a stochastic matrix if it! satisfies two conditions: (i) all entries of A are non-negative; and (ii) the sum of entries in each column is one. If the (,) entry of A is denoted by any for ij € {1, 2,...,n}, then A is a stochastic matrix when alij 20 for all i and j and I j = 1 for all j. These matrices are...
3. Let I be a left ideal of R and let (: R) reRRCI (a) : R) is an ideal of R. If l is regular, th...
3. Let I be a left ideal of R and let (: R) reRRCI (a) : R) is an ideal of R. If l is regular, then (: R) is the largest ideal of R that is contained in 1 (b) If I is a regular maximal left ideal of Rand AR/I, then (A(R). Therefore J(R) na:R), where /runs over all the regular maximal left ideals of R. Theorem 1.4. Let B be a subset of a left module A...
2 (5 points) Recalled that null space of a matrix A € Mnxn is defined as...
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...
Prove Theorem 4.2.21. The Singular Value Decomposition. PROVE THAT IF MATRIX A element of R^n*n Theorem...
Prove Theorem 4.2.21. The Singular Value
Decomposition. PROVE THAT IF MATRIX A element of R^n*n
Theorem 4.2.21. Let A e Rnxn. Then ||A| Definition 4.2.2. On R" we will use the standard inner product (7.7) = .2.2015 j=1 | 7 ||2=1 Theorem 4.2.20. Let A € R"X". Then ||A||2 = 01. Proof: Let AE Rnxn and let Let A=USVT be an SVD of A. We have || A||2 = max || 17 || 2 = max, ||UEV17 || 2 =...
Please do exercise 129: Exercise 128: Define r:N + N by r(n) = next(next(n)). Let f:N...
Please do exercise 129:
Exercise 128: Define r:N + N by r(n) = next(next(n)). Let f:N → N be the unique function that satisfies f(0) = 2 and f(next(n)) =r(f(n)) for all n E N. 102 1. Prove that f(3) = 8. 2. Prove that 2 <f(n) for all n E N. Exercise 129: Define r and f as in Exercise 128. Assume that x + y. Define r' = {(x,y),(y,x)}. Let g:N + {x,y} be the unique function that...
2 is the question
Question 4 [35 marks in total] An n xn matrix A is called a stochastic matriz if it satisfies two conditions: (i) all entries of A are non-negative; and (ii) the sum of entries in each column is one. If the (i, j) entry of A is denoted by aij for i,j e {1, 2, ..., n}, then A is a stochastic matrix when aij > 0 for all i and j and in dij =...
Material:
8.3.2 Consider the matrix (1 2 3 A-2 3 1 (8.3.28) (i) Use (8.3.27) to find the dominant eigenvalue of A. (ii) Check to see that u-(1 , I , î ), is a positive eigenvector of A. Use 11 and Theorem 8.6 to find the dominant eigenvalue of A and confirm that this is exactly what was obtained in part 0) obtained in part (i) or(ii ii) Compute all the eigenvalues of A directly and confirm the result...
A1. Let (A, B, C, D) be a SISO system in which A is a (n x n) complex matrix and B a (n x 1) column vector, let -1 V = {£ajA*B: aj e C; j= 0, ...,n- (i) Show that V is a complex vector space. (ii) Show that V has dimension one, if and only if B is an eigenvector of A AX for X E V. Show that S defines a linear map from S: V...
Review 4: question 1 Let A be an n x n matrix. Which of the below is not true? A. A scalar 2 is an eigenvalue of A if and only if (A - 11) is not invertible. B. A non-zero vector x is an eigenvector corresponding to an eigenvalue if and only if x is a solution of the matrix equation (A-11)x= 0. C. To find all eigenvalues of A, we solve the characteristic equation det(A-2) = 0. D)....
Question 4 [35 marks in totalj An n x n matrix A is called a stochastic matrix if it! satisfies two conditions: (i) all entries of A are non-negative; and (ii) the sum of entries in each column is one. If the (,) entry of A is denoted by any for ij € {1, 2,...,n}, then A is a stochastic matrix when alij 20 for all i and j and I j = 1 for all j. These matrices are...
3. Let I be a left ideal of R and let (: R) reRRCI (a) : R) is an ideal of R. If l is regular, then (: R) is the largest ideal of R that is contained in 1 (b) If I is a regular maximal left ideal of Rand AR/I, then (A(R). Therefore J(R) na:R), where /runs over all the regular maximal left ideals of R. Theorem 1.4. Let B be a subset of a left module A...
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...
Prove Theorem 4.2.21. The Singular Value
Decomposition. PROVE THAT IF MATRIX A element of R^n*n
Theorem 4.2.21. Let A e Rnxn. Then ||A| Definition 4.2.2. On R" we will use the standard inner product (7.7) = .2.2015 j=1 | 7 ||2=1 Theorem 4.2.20. Let A € R"X". Then ||A||2 = 01. Proof: Let AE Rnxn and let Let A=USVT be an SVD of A. We have || A||2 = max || 17 || 2 = max, ||UEV17 || 2 =...
Please do exercise 129:
Exercise 128: Define r:N + N by r(n) = next(next(n)). Let f:N → N be the unique function that satisfies f(0) = 2 and f(next(n)) =r(f(n)) for all n E N. 102 1. Prove that f(3) = 8. 2. Prove that 2 <f(n) for all n E N. Exercise 129: Define r and f as in Exercise 128. Assume that x + y. Define r' = {(x,y),(y,x)}. Let g:N + {x,y} be the unique function that...
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