17. (ando-Zhan) is set to $ A, B \ In M_n $ semi-definite, $ \ Sen {\ cdot} $ is an undo norm, then $ \ Bex \ Sen {(a + B) ^ r} \ Leq \ Sen {A ^ r + B ^ r }, \ Quad (0
Proof: (1 ). verify when $0
(2 ). when $ r \ geq 1 $, make $ g (t) = t ^ r = f ^ {-1} (t) $, $ F (t) = t ^ \ frac {1} {r} $, then by (1), $ \ Bex S (F [G (A) + g (B)]) \ prec_w S (F [G (A)] + F [G (A)]) = S (A + B ). \ EEx $ by $ G $ non-negative incremental convex function, theorem 3.21, and ing theorem similar to Theorem 1.3
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15. (fan-Hoffman) set $ A, H \ In M_n $, where $ h $ is the Hermite matrix, then $ \ Bex \ Sen {A-\ re a} \ Leq \ Sen {A-H} \ EEx $ is set to any Unio constant norm.
Proof: (1 ). first, it is proved that $ \ Bex \ Sen {\ cdot} \ mbox {is an undo norm }, X \ In M_n \ Ra \ Sen {x }=\ Sen {x ^ *}. \ EEx $ in fact, $ x $ has the same singular value as $ x ^ * $, while $ \ Bex S (x) \ prec S (x ^ *) \ prec S (X ). \ EEx $ the fan-dominated principl
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1. (fan-Hoffman ). set $ A \ In M_n $, note $ \ re a = (a + A ^ *)/2 $. then $ \ Bex \ lm_j (\ re a) \ Leq s_j (A), \ quad j = 1, \ cdots, N. \ EEx $
Proof: For $ x \ In \ BBC ^ N $, $ \ beex \ Bea x ^ * (\ re a) suitable for $ \ Sen {x} = 1 $) X = x ^ * \ frac {A + A ^ *} {2} X \ =\ frac {1} {2} (x ^ * AX + x ^ * A ^ * X) \\=\ Re (x ^ * Ax) \ quad \ sex {z \ In \ BBC \ rA Z ^ * = \ bar z} \ \ Leq | x ^ * ax |\\ = | \ SEF {ax, x} | \\ \ Leq \ S
1. $ A \ in M_n $ is called an orthogonal projection matrix. If $ A $ is A Hermite matrix and its idempotence is: $ \ bex A ^ * = A ^ 2. \ eex $ Proof: If $ A, B \ in M_n $ is an orthogonal projection matrix, then $ \ sen {A-B} _ \ infty \ leq 1 $.Proof: By $ A ^ * = A $ Zhi $ A $, you can perform the right-to-right corner. the feature value of $ A ^ 2 = A $ Zhi $ A $ is $0 $ or $1 $. therefore, $ Makes $ \ bex A = U ^ * \ diag (I _r, 0) U, \ quad r = \ rank (). \ eex $, $ \ beex \ bea x ^ * Ax
Label: style io color ar sp for on bs line3. (Bhatia-Davis) if $ A, B \ in M_n $ is A matrix, then $ \ bex \ rd (\ sigma (A), \ sigma (B )) \ leq \ sen {A-B} _ \ infty. \ eex $Proof: [see R. Bhatia, C. Davis, A bound for the spectral variation of a unitary operator, Linear and Multilinear Algebra, 15 (1984),-76.][Zhan Xiang matrix theory exercise reference] exercise 5.3
8. set $ k \ Leq m \ Leq N $. what kind of matrix $ A \ in M _ {m, n} $ each diagonal line exactly contains $ K $ zero elements?
Answer: Theorem 2.5 (k \ "onig ), each diagonal line of $ A $ contains $ K $ zero elements $ \ LRA $ A $ has a zero submatrix of $ r \ times S $, $ R + S = N + k $; $ A $ a diagonal line contains $ k + 1 $ zero elements $ \ LRA $ any $ r \ times S $ level submatrix of $ A $ non-zero, $ R + S = N + k + 1 $. therefore, each diagonal line of $ A $ contains $ K $ zero
Label: Style Color SP on BS size nbsp C element3. Set $ a, B \ In M_n $, $ A $ positive definite, $ B $ semi-positive, and the logarithm element is positive, then $ A \ circ B $ positive.Proof: By Schur theorem, $ A \ circ B $ is semi-definite, and its feature value $ \ geq 0 $. to prove that $ A \ circ B $ is positive, only $ \ det (A \ circ B)> 0 $ ($ \ rA $ any feature value $> 0 $) must be proved ). this can be directly caused by the Oppenheim inequality $ \ Bex \ det (A \ circ B) \ geq \ de
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9. Note $ \ DPS {M = \ sex {n \ atop K }}$. Composite Matrix ing $ c_k (\ cdot): M_n \ To m_m $ is it a single shot? Is it a full shot?
A: When $ k = 1 $, $ c_k (a) $ is each element of $ A $. therefore, $ c_k $ is a single shot or full shot. when $ k \ geq 2 $, generally, $ c_k $ is not a single shot, for example, $ \ Bex \ sex {\ BA {CCCC} 1 0 \ cdots 0 \ 0 \ cdots 0 \ vdots \ ddots \ vdots \ 0 0 \ cdots 0 \ EA }, \ quad \ sex {\ BA {CC
14. if ing $ F: M_n \ To M_n $ sorts the elements of each matrix in $ M_n $ in a fixed mode, $ F $ is called a replacement operator. what kind of replacement operator does not change the feature value of the Matrix? Keep the rank unchanged?
Answer: The replacement operator $ F $ keeps the feature value of the matrix unchanged. If only the replacement matrix $ p $ exists, $ \ Bex F (a) = pap ^ t, \ quad \ forall \ A \ In M_n; \ EEx $ or $ \ Bex F (a) = PA ^ TP ^ t, \ quad \ forall \ A \ In M
2. (oldenburgere) set $ A \ In M_n $, $ \ rock (a) $ to indicate the spectral radius of $ A $, that is, the creator of the modulus of the feature value of $ A $. proof: $ \ Bex \ vlm {k} a ^ K = 0 \ LRA \ rock (a)
Proof: $ \ rA $: Based on Jordan standard theory, there is a reversible array $ p $, make $ \ Bex P ^ {-1} AP =\sex {\ BA {CCC} \ lm_1 * \\\\ ddots \\\ \ lm_n \ EA }, \ EEx $ and $ \ Bex P ^ {-1} a ^ Kp = \ sex {\ BA {CCC} \ lm_1 ^ K * \ ddots \\ \ lm_n ^ k \ EA }. \ EEx $ thus,
10. set $ A and B $ to the same-order semi-Definite Matrix, $0 \ Leq s \ Leq 1 $. proof: $ \ Bex \ Sen {A ^ Sb ^ s} _ \ infty \ Leq \ Sen {AB} _ \ infty ^ s. \ EEx $
Proof:
(1 ). first, it is proved that the spectral norm of $ A $ is the maximum singular value of $ A $. in fact, $ \ beex \ Bea \ Sen {A} _ \ infty ^ 2 =\ Max _ {\ Sen {x} _ 2 = 1} \ Sen {ax} _ 2 ^ 2 \ =\ Max _ {\ Sen {x} _ 2 = 1} x ^ * a ^ * ax \ =\ Max _ {\ Sen {x }_ 2 = 1} x ^ * VV ^ * a ^ * u ^ * uavv ^ * x \ =\ Max
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8. it is proved that each semi-positive definite matrix has a unique square root of the semi-positive definite number. That is, if $ A \ geq 0 $, there is a unique $ B \ geq 0 $ that satisfies $ B ^ 2 = A $.
Proof: $ A \ geq 0 $ indicates the existence of U $, so that $ \ Bex U ^ * Au = \ diag (\ lm_1, \ cdots, \ lm_n ), \ quad \ lm_ I \ geq 0. \ EEx $ \ Bex B = U \ diag (\ SQRT {\ lm_1}, \ cdots, \ SQRT {\ lm_n}) U ^ *, \ EEx $ B \ geq 0 $, an
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5. Without the Weierstrass theorem, we can directly prove that the function operation (3.6) of the Hermite matrix has nothing to do with the specific spectral decomposition.
Proof: $ h $ also has a spectral decomposition $ \ Bex H = V \ diag (\ lm_1, \ cdots, \ lm_n) V ^ *, \ EEx $ \ Bex w \ diag (\ lm_1, \ cdots, \ lm_n) = \ diag (\ lm_1, \ cdots, \ lm_n) W, \ quad W = V ^ * U. \ EEx $ therefore, $ \ Bex W = \ diag (W_1, \ cdots, w_s ), \ EEx $
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1. Set $ A \ In M_n $. Prove that if $ AA ^ * = a ^ 2 $, $ A ^ * = A $.
Proof: By Schur ry triangle theorem, $ U $ exists, making $ \ Bex a = u ^ * Bu, \ EEx $ where $ B = (B _ {IJ}) $ is the upper triangle array. so $ \ Bex U ^ * BB ^ * u = AA ^ * = a ^ 2 = u ^ * B ^ 2u \ rA BB ^ * = B ^ 2. \ EEx $ compare the diagonal yuan between two ends $ \ Bex | B _ {II} | ^ 2 + \ cdots + | B _ {In} | ^ 2 = B _{ II} ^ 2, \ Quad 1 \ Leq I \ Leq n. \ EEx $ whi
PHP exercises (2): php exercises. PHP exercise (2), php exercise program 6. question: If a person has 100,000 yuan in cash and needs to pay a fee every time he passes through an intersection, the rule is that when his cash is greater than 50,000, he needs PHP exercises every time (2). php exercises
Program 6.Question:Assume that a person has 100,000 yuan in cash and must pay 50,000 yuan each time after the
Exercise 4-7 OriginalExercise 4.7. Let* is similar to let, except that the bindings of the A let variables be performed sequentially from left to right, and E Ach binding is made in a environment in which all of the preceding bindings are visible. For example (let* ( (x 3 ) (y (+ x 2 ) ) Span class= "Hljs-list" > (z ( x y 5 ) ) ) (* x z) ) Returns 39. Explain How a let* expression can is rewritten as a set of nested let expressions,
Exercise 4-8 OriginalExercise 4.8. "Named let" are a variant of let that have the formvar>bindings>body>)The and is just as in ordinary let, except that is bound within to a procedure whose body is and whose parameters are the variables in the . Thus, one can repeatedly execute the by invoking the procedure named . For example, the iterative Fibonacci procedure (section 1.2.2) can be rewritten using named let as follows: (Define (fib N) ( LetFib-it
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