1 / 23

Discrete Mathematics

Discrete Mathematics. Chapter 4 Induction and Recursion. 4.1 Mathematical Induction( 数学归纳法 ). Note : Mathematical induction can be used only to prove results obtained in some other way. It is not a tool for discovering formulae or theorems. (p.265)

darryl
Télécharger la présentation

Discrete Mathematics

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Discrete Mathematics Chapter 4 Induction and Recursion

  2. 4.1 Mathematical Induction(数学归纳法) Note : Mathematical induction can be used only to prove results obtained in some other way. It is not a tool for discovering formulae or theorems. (p.265) P(n) : a propositional function (e.g. n ≦ 2n) A proof by mathematical induction(MI) that P(n) is true for every nZ+ consists of two steps : 1. Basis step : The proposition P(1) is shown to be true.(若 n 从 0 开始则证 P(0)为真) 2. Inductive step : the implication P(k) → P(k+1) is shown to be true for every kZ+

  3. Example 2. Use MI to prove that the sum of the first n odd positive integers is n2. Note. 不用MI就可以得证: Pf : Let P(n) denote the proposition that Basis step :P(1) is true , since 1=12 Inductive step : Suppose that P(k) is true for a positive integer k, i.e., 1+3+5+…+(2k-1)=k2 Note that 1+3+5+…+(2k-1)+(2k+1) = k2+2k+1= (k+1)2 ∴ P(k+1) is true By induction, P(n) is true for all nZ+

  4. Example 5. Use MI to prove the inequality n < 2n for all nZ+ pf : Let P(n) be the proposition “ n < 2n”. Basis step :P(1) is true since 1 < 21. Inductive step : Assume that P(k) is true for a positive integer k, i.e., k < 2k. Consider P(k+1) : k + 1 < 2k+ 1  2k+ 2k =2k + 1 ∴ P(k+1) is true. By MI, P(n) is true for all nZ+.

  5. Example 7. The harmonic numbersHk, k =1,2,3,…, are defined by . Use MI to show that whenever n is a nonnegative integer. Pf : Let P(n) be the proposition that “ ”. Basis step :P(0) is true, since . Inductive step : Assume that P(k) is true for some k, i.e., Consider P(k+1) :

  6. ∴P(k+1) is true. By MI, P(n) is true for all nZ+. Exercise : 7, 13

  7. 4.2 Strong Induction(强数学归纳法) • Basis step 相同 • Inductive step : Assume all the statements P(1), P(2), …, P(k) are true. Show that P(k+1) is also true.

  8. Example 2. Show that if nZ and n >1, then n can be written as the product of primes. Pf : Let P(n) be the proposition that n can be written as the product of primes. Basis :P(2) is true, since 2 is a prime number Inductive : Assume P(2), P(3), …, P(k) are true. Consider P(k + 1) : Case 1 : k + 1 is prime  P(k+1) is true Case 2 : k + 1 is composite, i.e., k + 1 = ab where 2 ab< k+1 By the induction hypothesis, both a and b can be written as the product of primes. P(k+1) is true. By Strong MI, P(k) is true if kZ and k >1. Note: 此题无法仅用 MI 证

  9. Example 4. Prove that every amount of postage of 12 cents or more can be formed using just 4-cent and 5-cent stamps. Pf : Let P(n) be the statement that the postage of n cents can formed using just 4-cent and 5-cent stamps. Basis :P(12) is true, since 12 = 4  3; P(13) is true, since 13 = 4  2 + 5  1; P(14) is true, since 14 = 4  1 + 5  2; P(15) is true, since 15 = 5  3; Inductive : Assume P(12), P(13), …, P(k) are true. Consider P(k+1) : Suppose k-3= 4  m + 5  n. Then k+1= 4  (m+1) + 5  n. P(k+1) is true. By Strong MI, P(n) is true if nZ and n 12. (k-3  12) Exercise : 7

  10. 4.3 Recursive Definitions. Def. The process of defining an object in terms of itself is called recursion(递归). e.g. We specify the terms of a sequence using (1) an explicit formula: an=2n, n=0,1,2,… (2) a recursive form: a0=1, an+1=2an , n=0,1,2,… Example 1. Suppose that f is defined recursively by f(0)=3 , f(n+1)=2f(n)+3 Find f(1), f(2), f(3), f(4).

  11. Example 2. Give an inductive (recursive) definition of the factorial function F(n) = n!. Sol : initial value : F(0) = 1 recursive form : F(n+1) = (n+1)! = n!  (n+1) = F(n)  (n+1) Def1, Example 5. The Fibonacci numbersf0, f1, f2…,are defined by : f0= 0 , f1 = 1 , fn = fn-1 + fn-2 , for n = 2,3,4,… what is f4 ? Sol : f4 = f3 + f2 = (f2 + f1) + (f1 + f0) = f2 + 2 = (f1 + f0) + 2 = 3

  12. Example 6. Show that fn > a n-2 , where Pf:( By Strong MI ) Let P(n) be the statement fn>a n-2 . Basis: f3 = 2 > a so that P(3) and P(4) are true. Inductive: Assume that P(3), P(4), …, P(n) are true. We must show that P(n+1) is true. fn+1 = fn + fn-1 > a n-2 + a n-3 = a n-3(a +1) ∵ a +1= a2 ∴ fn+1 > a n-3  a2 = a n-1 We get that P(n+1) is true. By Strong MI , P(n) is true for all n  3

  13. ※Recursively defined sets. Example 7. Let S be defined recursively by 3S x+yS if xS and yS. Show that S is the of positive integers divisible by 3 (i.e., S = { 3, 6, 9, 12, 15, 18, … } Pf: Let A be the set of all positive integers divisible by 3. We need to prove that A=S. (i) A  S : (By MI) Let P(n) be the statement that 3nS … (ii) S  A : (利用S的定义) (1) 3  A , (2) if xA,yA, then 3|x and 3|y.  3|(x+y)  x+yA ∴S A S = A

  14. Definition 2. The set of strings over an alphabet is denoted by *. The empty string is denoted by l, l , and wx* whenever w* and x.eg.  = { a, b, c } * = { l, a , b , c , aa , ab , ac , ba , bb , bc, …abcabccba, …} Example 9. Give a recursive definition of l(w), the length of the string w* Sol : initial value : l(l)=0 recursive def : l(wx)=l(w)+1 if w*, x. lb la lc

  15. 0l1 n个 n个 Exercise 3, 7, 13, 48, 49 Exercise 39. When does a string belong to the set A of bit strings defined recursively by lA 0x1A if xA. Sol : A={l, 01 , 0011, 000111, …} ∴当bit string a = 000…011…1时 aA

  16. Ackermann’s function A(m, n) = 2n if m = 0 0 if m  1 and n = 0 2 if m  1 and n = 1 A(m-1, A(m, n-1)) if m  1 and n  2 Exercise 49 Show that A(m,2)=4 whenever m  1 Pf : A(m,2) = A(m-1, A(m,1)) = A(m-1,2) whenever m  1. A(m,2) = A(m-1,2) = A(m-2,2) = … = A(0,2) = 4.

  17. 4.4 Recursive algorithms. ※ Sometimes we can reduce the solution to a problem with a particular set of input to the solution of the same problem with smaller input values. eg. gcd(a,b) = gcd(b mod a, a) (when a < b) Def 1. An algorithm is called recursiveif it solves a problem by reducing it to an instance of the same problem with smaller input.

  18. Algorithm 2. Procedurepower( a : nonzero real number, n : nonnegative integer ) ifn = 0 thenpower(a, n):=1 elsepower(a, n):= a*power(a, n-1). Example 2. Give a recursive algorithm for computing an, where aR \ {0}, nN. Sol : recursive definition of an : initial value : a0=1 recursive def : an = a  an-1.

  19. 从ai,ai+1,…aj中找 x Example 4. Find gcd(a,b) with 0a<b Algorithm 4. proceduregcd(a,b : nonnegative integers with a<b) ifa=0 thengcd(a,b) := b elsegcd(a,b) := gcd(b mod a, a). Sol : Example 5. Search x in a1, a2,…,an by Linear Search Sol : Alg. 5 proceduresearch (i, j, x: integers) if ai = xthenlocation := i elseif i = jthenlocation := 0 elsesearch(i+1, j, x) call search(1, n, x)

  20. 表示左半边ai, ai+1, …, am-1 至少还有一个元素 Example 6. Search x from a1,a2,…,an by binary search (recursive version). search x from ai, ai+1, …, aj Sol : Alg. 5 procedurebinary_search (x , i , j: integers) m := (i+j) / 2 ifx = amthenlocation := m else if (x < am and i < m) then binary_search(x, i, m-1) else if (x > am and j > m) then binary_search(x, m+1, j) elselocation := 0 call binary_search(x, 1, n)

  21. Example 1. Give the value of n!, nZ+ Sol : Note : n! = n (n-1)! Alg. 1 (Recursive Procedure) procedurefactorial (n: positive integer) ifn = 1 thenfactorial (n) := 1 elsefactorial (n) := nfactorial (n-1) Alg. (Iterative Procedure) procedureiterative_factorial (n : positive integer) x := 1 for i := 1 ton x := i  x { x = n! }

  22. ※ iterative alg. 的计算次数通常比 recursive alg.少 ※ Find Fibonacci numbers (Note : f0=0, f1=1, fn=fn-1+fn-2 for n2) Alg. 7 (Recursive Fibonacci) procedureFibonacci (n : nonnegative integer) if n = 0 thenFibonacci (0) := 0 elseifn = 1 then Fibonacci (1) := 1 else Fibonacci (n) := Fibonacci (n-1)+Fibonacci (n-2)

  23. Alg.8 (Iterative Fibonacci) procedureiterative_fibonacci (n: nonnegative integer) if n = 0 theny := 0 // y = f0 else begin x := 0 y := 1 // y = f1 fori := 1 ton-1 begin z := x + y x := y y := z end end {y is fn} Exercise : 11, 35

More Related