算法导论第三版第五章答案英

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《计算机算法基础》第三版,课后习题答案

③当物品按w
i的非降次序输入时，重复②的讨论。
解：
①按照p
i/w
i的非增序可得
(p
5/w
5，p
1/w
1，p
6/w
6，p
3/w
3，p
7/w
7，p
2/w
2，p
4/w
4)= (6,5,9/2,3,3,5/3,1)
W的次序为(1,2,4,5,1,3,7),解为(1,1,1,1,1,2/3,0)
所以最优解为：
k=I
k+2k，考察原树的外部路径长度为E
k+1= E
k-（h-1）+2h，内部路径长度为I
k+1=I
k+（h-1），所以E
k+1= I
k+2k+h+1= I
k+1+2k+2= I
k+1+2(k+1)，综合①②③知命题成立。
4.10过程MERGESORT的最坏情况时间是O(nlogn)，它的最好情况时间是什么？能说归并分类的时间是Θ(nlogn)吗？
i的非增次序考虑这些物品，只要正被考虑的物品能装进的就将其装入背包。证明这种策略不一定能得到最优解。
证明：
当按照p
i/w
i的非增次序考虑物品存放背包时，如果所装入的物品恰能装满背包时，易证为最优解，否则未必是最优解。
可举例如下：
设n=3，M=6，（p
1,p
2,p
3）=(3,4,8)，（w
1,w
2,w
=(A
11+A
22)(B
11+B
22)+A
11(B
12+B

算法导论习题答案 (5)

c(j) = min {c(i − 1) + linecost(i, j)} .
Three-hole punch your paper on submissions. You will often be called upon to “give an algorithm” to solve a certain problem. Your write-up should take the form of a short essay. A topic paragraph should summarize the problem you are solving and what your results are. The body of the essay should provide the following:
(a) Argue that this problem exhibits optimal substructure.
Solution: First, notice that linecost(i, j) is deﬁned to be � if the words i through j do not ﬁt on a line to guarantee that no lines in the optimal solution overﬂow. (This relies on the assumption that the length of each word is not more than M .) Second, notice that linecost(i, j) is deﬁned to be 0 when j = n, where n is the total number of words; only the actual last line has zero cost, not the recursive last lines of subprob lems, which, since they are not the last line overall, have the same cost formula as any other line.

算法导论第五章概率分析和随机算法

Proof We start by considering the particular permutation in which each element A[i] receives the ith smallest priority. We shall show that this permutation occurs with probability exactly 1/n!. For i = 1, 2, ..., n, let Xi be the event that element A[i] receives the ith smallest priority. Then we wish to compute the probability that for all i, event Xi occurs, which is Pr {X1 ∩ X2 ∩ X3 ∩ ··· ∩ Xn-1 ∩ Xn}. Using Exercise C.2-6, this probability is equal to Pr {X1} · Pr{X2 | X1} · Pr{X3 | X2 ∩ X1} · Pr{X4 | X3 ∩ X2 ∩ X1} Pr{Xi | Xi-1 ∩ Xi-2 ∩ ··· ∩ X1} Pr{Xn | Xn-1 ∩ ··· ∩ X1}. We have that Pr {X1} = 1/n because it is the probability that one priority chosen randomly out of a set of n is the smallest. Next, we observe that Pr {X2 | X1} = 1/(n - 1) because given that element A[1] has the smallest priority, each of the remaining n - 1 elements has an equal chance of having the second smallest priority. In general, for i = 2, 3, ..., n, we have that Pr {Xi | Xi-1 ∩ Xi-2 ∩ ··· ∩ X1} = 1/(n - i + 1), since, given that elements A[1] through A[i - 1] have the i - 1 smallest priorities (in order), each of the remaining n - (i - 1) elements has an equal chance of having the ith smallest priority. Thus, we have

算法导论第三版第七章答案英

Exercise 7.2-4
Let’s say that by “almost sorted” we mean that A[i] is at most c positions from its correct place in the sorted array, for some constant c. For INSERTIONSORT, we run the inner-while loop at most c times before we ﬁnd where to insert A[j] for any particular iteration of the outer for loop. Thus the running time time is O(cn) = O(n), since c is ﬁxed in advance. Now suppose we run QUICKSORT. The split of PARTITION will be at best n − c to c, which leads to O(n2) running time.
Chapter 7
Michelle Bodnar, Andrew Lohr
April 12, 2016
Exercise 7.1-1
13 19 9 5 12 8 7 4 21 2 6 11 13 19 9 5 12 8 7 4 21 2 6 11 13 19 9 5 12 8 7 4 21 2 6 11 9 19 13 5 12 8 7 4 21 2 6 11 9 5 13 19 12 8 7 4 21 2 6 11 9 5 13 19 12 8 7 4 21 2 6 11 9 5 8 19 12 13 7 4 21 2 6 11 9 5 8 7 12 13 19 4 21 2 6 11 9 5 8 7 4 13 19 12 21 2 6 11 9 5 8 7 4 13 19 12 21 2 6 11 9 5 8 7 4 2 19 12 21 13 6 11 9 5 8 7 4 2 6 12 21 13 19 11 9 5 8 7 4 2 6 11 21 13 19 12 Exercise 7.1-2

算法导论作业5答案概要

6 Problem 5-2. Join operation on red-black trees Handout 22: Problem Set 5 The join operation takes two dynamic� sets �� and �� and an element � such that for any �� and �� , we have key �� key �� key �� . It returns a set �� . In this problem, we investigate how to implement the join operation on red-black trees. (a Given a red-black tree � , we store its black-height as the ﬁeld bh ��. Argue that this ﬁeld can be maintained by RB-I NSERT and RB-D ELETE (as given in the textbook, on pages 280 and 288 respectively without requiring extra storage in the nodes of the tree and without increasing the asymptotic running times. Show that while descending through � , we can determine the black-height of each node we visit in �� time per node visited. Solution: Starting at the root, we can proceed to a leaf, couting the number of black nodes on the path. This does not require any extra storage in the nodes of the tree and will take �� time. Since RB-I NSERT and RB-D ELETE also run in�� time, the asymptotic running time is not increased. While descending through � , we decrement bh �� by � 1 everytime we encounter a blacknode. The black-height of a node, � , is then bh �� minus the number of black nodes encountered (excluding node � itself. This decrement can be done in �� time per node visited. We wish to implement the operation RB-J OIN �� , which may destroy �� and �� and returns a red-black tree �� . Let � be the total number of nodes in �� and �� . (b Assume that bh �� bh �� . Describe an �� -time algorithm that ﬁnds a black � node �� in � with the largest key from among those nodes whose black-height is bh � . Solution: Since �� is a binary search tree, the largest element at any level is on the rightmost path. So, we decend down the rightmost path, calculating bh at each node (as described �� in the previous part, until we reach the black node whose black-height is bh � , which is what we want. Thus the running time is at most the height of the tree, i.e. �� . (Calculating the black-height takes �� per node, as shown in the previous part. �� (c Let �� be the subtree rooted at � . Describe how �� can replace �� in �� time without destroying the binary-search-tree property. Solution:Handout 22: Problem Set 5 Insert � into where � was in �� . Form �� by letting �� be the left subtree� of � , and �� be the right subtree of � . Given that this join operation is such that � key �� key�� key �� where �� and �� , the binary search tree property is maintained and this operation takes �� time. Consider the following red-black properties: 7 � every node is either red or black � every leaf is black nodes (d What color should we make � so that the above red-black properties are maintained? Solution: We should make � red. Since �� already has black-height = bh �� , � must be red to �� = bh ��maintain the same black-height, bh �� Consider the following red-black properties: �for each node, all paths from the node to descendant leaves contain the same number of black � the root is black � if a node is red, then both its children are black (e Describe how the above two properties can be enforced in �� time. Solution:Use RB-I NSERT-F IXUP on the new tree, to perform the recoloring and rotations nec-essary to enforce these two properties. We know that RB-I NSERT-F IXUP runs in�� time, thus we conclude that the enforcement can be done in�� time. (f Argue that the running time of RB-J OIN is�� . Solution: RB-J OIN is implemented by using all the previous parts: The black-height can be calculated and maintained in �� time. The required black node, � , can be found in �� time. Then, the join is done in��time, and ﬁnally, after assigning � the right color, the red-black tree properties can be enforced in �� time. So the total runing time is ��。

算法导论课程作业答案

算法导论课程作业答案Introduction to AlgorithmsMassachusetts Institute of Technology 6.046J/18.410J Singapore-MIT Alliance SMA5503 Professors Erik Demaine,Lee Wee Sun,and Charles E.Leiserson Handout10Diagnostic Test SolutionsProblem1Consider the following pseudocode:R OUTINE(n)1if n=12then return13else return n+R OUTINE(n?1)(a)Give a one-sentence description of what R OUTINE(n)does.(Remember,don’t guess.) Solution:The routine gives the sum from1to n.(b)Give a precondition for the routine to work correctly.Solution:The value n must be greater than0;otherwise,the routine loops forever.(c)Give a one-sentence description of a faster implementation of the same routine. Solution:Return the value n(n+1)/2.Problem2Give a short(1–2-sentence)description of each of the following data structures:(a)FIFO queueSolution:A dynamic set where the element removed is always the one that has been in the set for the longest time.(b)Priority queueSolution:A dynamic set where each element has anassociated priority value.The element removed is the element with the highest(or lowest)priority.(c)Hash tableSolution:A dynamic set where the location of an element is computed using a function of the ele ment’s key.Problem3UsingΘ-notation,describe the worst-case running time of the best algorithm that you know for each of the following:(a)Finding an element in a sorted array.Solution:Θ(log n)(b)Finding an element in a sorted linked-list.Solution:Θ(n)(c)Inserting an element in a sorted array,once the position is found.Solution:Θ(n)(d)Inserting an element in a sorted linked-list,once the position is found.Solution:Θ(1)Problem4Describe an algorithm that locates the?rst occurrence of the largest element in a?nite list of integers,where the integers are not necessarily distinct.What is the worst-case running time of your algorithm?Solution:Idea is as follows:go through list,keeping track of the largest element found so far and its index.Update whenever necessary.Running time isΘ(n).Problem5How does the height h of a balanced binary search tree relate to the number of nodes n in the tree? Solution:h=O(lg n) Problem 6Does an undirected graph with 5vertices,each of degree 3,exist?If so,draw such a graph.If not,explain why no such graph exists.Solution:No such graph exists by the Handshaking Lemma.Every edge adds 2to the sum of the degrees.Consequently,the sum of the degrees must be even.Problem 7It is known that if a solution to Problem A exists,then a solution to Problem B exists also.(a)Professor Goldbach has just produced a 1,000-page proof that Problem A is unsolvable.If his proof turns out to be valid,can we conclude that Problem B is also unsolvable?Answer yes or no (or don’t know).Solution:No(b)Professor Wiles has just produced a 10,000-page proof that Problem B is unsolvable.If the proof turns out to be valid,can we conclude that problem A is unsolvable as well?Answer yes or no (or don’t know).Solution:YesProblem 8Consider the following statement:If 5points are placed anywhere on or inside a unit square,then there must exist two that are no more than √2/2units apart.Here are two attempts to prove this statement.Proof (a):Place 4of the points on the vertices of the square;that way they are maximally sepa-rated from one another.The 5th point must then lie within √2/2units of one of the other points,since the furthest from the corners it can be is the center,which is exactly √2/2units fromeach of the four corners.Proof (b):Partition the square into 4squares,each with a side of 1/2unit.If any two points areon or inside one of these smaller squares,the distance between these two points will be at most √2/2units.Since there are 5points and only 4squares,at least two points must fall on or inside one of the smaller squares,giving a set of points that are no more than √2/2apart.Which of the proofs are correct:(a),(b),both,or neither (or don’t know)?Solution:(b)onlyProblem9Give an inductive proof of the following statement:For every natural number n>3,we have n!>2n.Solution:Base case:True for n=4.Inductive step:Assume n!>2n.Then,multiplying both sides by(n+1),we get(n+1)n!> (n+1)2n>2?2n=2n+1.Problem10We want to line up6out of10children.Which of the following expresses the number of possible line-ups?(Circle the right answer.)(a)10!/6!(b)10!/4!(c) 106(d) 104 ·6!(e)None of the above(f)Don’t knowSolution:(b),(d)are both correctProblem11A deck of52cards is shuf?ed thoroughly.What is the probability that the4aces are all next to each other?(Circle theright answer.)(a)4!49!/52!(b)1/52!(c)4!/52!(d)4!48!/52!(e)None of the above(f)Don’t knowSolution:(a)Problem12The weather forecaster says that the probability of rain on Saturday is25%and that the probability of rain on Sunday is25%.Consider the following statement:The probability of rain during the weekend is50%.Which of the following best describes the validity of this statement?(a)If the two events(rain on Sat/rain on Sun)are independent,then we can add up the twoprobabilities,and the statement is true.Without independence,we can’t tell.(b)True,whether the two events are independent or not.(c)If the events are independent,the statement is false,because the the probability of no rainduring the weekend is9/16.If they are not independent,we can’t tell.(d)False,no matter what.(e)None of the above.(f)Don’t know.Solution:(c)Problem13A player throws darts at a target.On each trial,independentlyof the other trials,he hits the bull’s-eye with probability1/4.How many times should he throw so that his probability is75%of hitting the bull’s-eye at least once?(a)3(b)4(c)5(d)75%can’t be achieved.(e)Don’t know.Solution:(c),assuming that we want the probability to be≥0.75,not necessarily exactly0.75.Problem14Let X be an indicator random variable.Which of the following statements are true?(Circle all that apply.)(a)Pr{X=0}=Pr{X=1}=1/2(b)Pr{X=1}=E[X](c)E[X]=E[X2](d)E[X]=(E[X])2Solution:(b)and(c)only。

编译原理第三版课后习题答案解析

目录P36-6 (2)P36-7 (2)P36-8 (2)P36-9 (3)P36-10 (3)P36-11 (3)P64–7 (4)P64–8 (5)P64–12 (5)P64–14 (7)P81–1 (8)P81–2 (9)P81–3 (12)P133–1 (12)P133–2 (12)P133–3 (14)P134–5 (15)P164–5 (19)P164–7 (19)P217–1 (19)P217–3 (20)P218–4 (20)P218–5 (21)P218–6 (22)P218–7 (22)P219–12 (22)P270–9 (24)P36-6(1)L G ()1是0~9组成的数字串(2)最左推导:N ND NDD NDDD DDDD DDD DD D N ND DD D N ND NDD DDD DD D ⇒⇒⇒⇒⇒⇒⇒⇒⇒⇒⇒⇒⇒⇒⇒⇒⇒⇒0010120127334556568最右推导:N ND N ND N ND N D N ND N D N ND N ND N D ⇒⇒⇒⇒⇒⇒⇒⇒⇒⇒⇒⇒⇒⇒⇒⇒⇒⇒77272712712701274434886868568P36-7G(S)O N O D N S O AO A AD N→→→→→1357924680|||||||||||P36-8文法：E T E T E T TF T F T F F E i→+-→→|||*|/()| 最左推导:E E T T TF T i T i T F i F F i i F i i i E T T F F F i F i E i E T i T T i F T i i T i i F i i i ⇒+⇒+⇒+⇒+⇒+⇒+⇒+⇒+⇒⇒⇒⇒⇒⇒+⇒+⇒+⇒+⇒+⇒+********()*()*()*()*()*()*()最右推导:E E T E TF E T i E F i E i i T i i F i i i i i E T F T F F F E F E T F E F F E i F T i F F i F i i i i i ⇒+⇒+⇒+⇒+⇒+⇒+⇒+⇒+⇒⇒⇒⇒⇒+⇒+⇒+⇒+⇒+⇒+⇒+**********()*()*()*()*()*()*()*()语法树：/********************************EE FTE +T F F T +iiiEEFTE-T F F T -iiiE EFT+T F FTiii*i+i+ii-i-ii+i*i*****************/P36-9句子iiiei 有两个语法树：S iSeS iSei iiSei iiiei S iS iiSeS iiSei iiiei ⇒⇒⇒⇒⇒⇒⇒⇒P36-10/**************)(|)(|S T TTS S →→***************/P36-11/*************** L1:ε||cC C ab aAb A AC S →→→ L2:bcbBc B aA A AB S ||→→→εL3:εε||aBb B aAb A AB S →→→ L4:AB B A A B A S |01|10|→→→ε ***************/第三章习题参考答案P64–7(1)101101(|)*1 ε ε 1 0 11 确定化：0 1 {X} φ {1,2,3} φ φ φ {1,2,3} {2,3} {2,3,4} {2,3} {2,3} {2,3,4} {2,3,4} {2,3,5} {2,3,4} {2,3,5} {2,3} {2,3,4,Y} {2,3,4,Y}{2,3,5}{2,3,4,}1 00 0 1 1 00 1 0 1 1 1 最小化：X 1 2 3 4 Y5 X Y60 12 35 4{,,,,,},{}{,,,,,}{,,}{,,,,,}{,,,}{,,,,},{},{}{,,,,}{,,}{,,,},{},{},{}{,,,}{,012345601234513501234512460123456012341350123456012310100==== 3012312401234560110112233234012345610101}{,,,}{,,}{,},{,}{},{},{}{,}{}{,}{,}{,}{}{,}{}{},{},{,},{},{},{}===== 010 0 1 00 1 0 1 1 1P64–8(1)01)0|1(*(2))5|0(|)5|0()9|8|7|6|5|4|3|2|1|0)(9|8|7|6|5|4|3|2|1(*(3)******)110|0(01|)110|0(10P64–12(a)aa,b a确定化：a b {0} {0,1} {1} {0,1} {0,1} {1} {1}{0}φ5 01 2 4 3 01φφ φ给状态编号：a b 0 1 2 1 1 2 2 0 3 333aaa b b bba最小化：{,},{,}{,}{}{,}{}{,}{,}{,}{}{,},{},{}012301101223032330123a ba b ====a ab bab (b)b b aa b aa bb aa a已经确定化了,进行最小化0 1 2 3 01 2 02 3 14 5最小化：{{,}, {,,,}}012345011012423451305234523452410243535353524012435011012424{,}{}{,}{,}{,,,}{,,,}{,,,}{,,,}{,}{,}{,}{,}{,}{,}{,}{,}{{,},{,},{,}}{,}{}{,}{,}{,}a b a b a b a b a b a =============={,}{,}{,}{,}{,}{,}{,}10243535353524 b a bb b aa baP64–14(1) 01 0 (2):(|)*0100 1 ε ε确定化：0 1 {X,1,Y}{1,Y}{2}1 2 01YX YX 2 1{1,Y} {1,Y} {2} {2} {1,Y} φ φφ φ 给状态编号：0 1 0 1 2 1 1 2 2 1 3 3330 1 01 1 10 最小化：{,},{,}{,}{}{,}{}{,}{,}{,}{}{,},{},{}0123011012231323301230101====1 1 1 0第四章P81–1(1) 按照T,S 的顺序消除左递归ε|,)(||^)(T S T TS T T a S S G '→''→→' 递归子程序： procedure S; beginif sym='a' or sym='^' then abvance else if sym='('0 2 13 01 3then begin advance;T;if sym=')' then advance; else error; end else error end;procedure T; begin S;'T end;procedure 'T ; beginif sym=',' then begin advance; S;'T end end; 其中:sym:是输入串指针IP 所指的符号 advance:是把IP 调至下一个输入符号 error:是出错诊察程序 (2)FIRST(S)={a,^,(} FIRST(T)={a,^,(} FIRST('T )={,,ε} FOLLOW(S)={),,,#} FOLLOW(T)={)} FOLLOW('T )={)} 预测分析表a^() , # S S a →S →^S T →()TT ST →' T ST →' T ST →''T'→T ε '→'T ST ,是LL(1)文法P81–2文法：|^||)(|*||b a E P F F F P F T T T F T E E E T E →'→''→→''→+→''→εεε(1)FIRST(E)={(,a,b,^} FIRST(E')={+,ε} FIRST(T)={(,a,b,^} FIRST(T')={(,a,b,^,ε} FIRST(F)={(,a,b,^} FIRST(F')={*,ε} FIRST(P)={(,a,b,^} FOLLOW(E)={#,)} FOLLOW(E')={#,)} FOLLOW(T)={+,),#} FOLLOW(T')={+,),#}FOLLOW(F)={(,a,b,^,+,),#} FOLLOW(F')={(,a,b,^,+,),#} FOLLOW(P)={*,(,a,b,^,+,),#} (2)考虑下列产生式:'→+'→'→'→E E T T F F P E a b ||*|()|^||εεεFIRST(+E)∩FIRST(ε)={+}∩{ε}=φ FIRST(+E)∩FOLLOW(E')={+}∩{#,)}=φ FIRST(T)∩FIRST(ε)={(,a,b,^}∩{ε}=φ FIRST(T)∩FOLLOW(T')={(,a,b,^}∩{+,),#}=φ FIRST(*F')∩FIRST(ε)={*}∩{ε}=φFIRST(*F')∩FOLLOW(F')={*}∩{(,a,b,^,+,),#}=φ FIRST((E))∩FIRST(a) ∩FIRST(b) ∩FIRST(^)=φ 所以,该文法式LL(1)文法. (3)+ * ()ab^#EE TE →' E TE →' E TE →' E TE →'E' '→+E E'→E ε '→E εTT F T →' T F T →' T F T →' T F T →'T''→T ε'→T T '→T ε '→T T '→T T '→T T '→T εFF P F →'F P F →' F P F →' F P F →'F' '→F ε '→'F F * '→F ε '→F ε '→F ε '→F ε '→F ε '→F εPP E →() P a → P b → P →^(4)procedure E; beginif sym='(' or sym='a' or sym='b' or sym='^' then begin T; E' end else error endprocedure E'; beginif sym='+'then begin advance; E endelse if sym<>')' and sym<>'#' then error endprocedure T; beginif sym='(' or sym='a' or sym='b' or sym='^' then begin F; T' end else error endprocedure T'; beginif sym='(' or sym='a' or sym='b' or sym='^' then Telse if sym='*' then error endprocedure F; beginif sym='(' or sym='a' or sym='b' or sym='^' then begin P; F' end else error endprocedure F'; beginif sym='*'then begin advance; F' end endprocedure P; beginif sym='a' or sym='b' or sym='^' then advanceelse if sym='(' thenbeginadvance; E;if sym=')' then advance else error endelse errorend;P81–3/***************(1) 是，满足三个条件。

算法导论第三版第九章答案英

2Hale Waihona Puke is less than roughly 4n/14 of the elements. So, we are never calling it recursively on more than 10n/14 elements. So, T (n) ≤ T (n/7) + T (10n/14) + O(n). So, we can show by substitution this is linear. Suppose T (n) < cn for n < k , then, for m ≥ k , T (m) ≤ T (m/7) + T (10m/14) + O(m) ≤ cm(1/7 + 10/14) + O(m). So, as long as we have that the constant hidden in the big-Oh notation is less than c/7, we have the desired result. Suppose now that we use groups of size 3 instead. So, For similar reasons, we have that the recurrence we are able to get is T (n) = T ( n/3 ) + T (4n/6) + O(n) ≥ T (n/3) + T (2n/3) + O(n). So, we will show it is ≥ cn lg(n). T (m) ≥ c(m/3) lg(m/3) + c(2m/3) lg(2m/3) + O(m) ≥ cm lg(m) + O(m). So, we have that it grows more quickly than linear. Exercise 9.3-2 We know that the number of elements greater than or equal to x and the number of elements less than or equal to x is at least 3n/10 − 6. Then for n ≥ 140 we have 3n/10 − 6 = Exercise 9.3-3 We can modify quicksort to run in worst case n lg(n) time by choosing our pivot element to be the exact median by using quick select. Then, we are guaranteed that our pivot will be good, and the time taken to ﬁnd the median is on the same order of the rest of the partitioning. Exercise 9.3-4 Create a graph with n vertices and draw a directed edge from vertex i to vertex j if the ith and j th elements of the array are compared in the algorithm and we discover that A[i] ≥ A[j ]. Observe that A[i] is one of the i − 1 smaller elements if there exists a path from x to i in the graph, and A[i] is one of the n − i larger elements if there exists a path from i to x in the graph. Every vertex i must either lie on a path to or from x because otherwise the algorithm can’t distinguish between i ≤ x and i ≥ x. Moreover, if a vertex i lies on both a path to x and a path from x then it must be such that x ≤ A[i] ≤ x, so x = A[i]. In this case, we can break ties arbitrarily. Exercise 9.3-5 To use it, just ﬁnd the median, partition the array based on that median. If i is less than half the length of the original array, recurse on the ﬁrst half, if i is half the length of the array, return the element coming from the median ﬁnding 3 n n + − 6 ≥ n/4 + 140/20 − 6 = n/4 + 1 ≥ n/4 . 4 20

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for all eternity do a = BiasedRandom b = BiasedRandom if a > b then return 1 end if if a < b then return 0 end if end for
Chapter 5
Michelle Bodnar, Andrew Lohr April 12, 2016
Exercise 5.1-1 We may of been presented the candidates in increasing order of goodness. This would mean that we can apply transitivity to determine our preference between any two candidates Exercise 5.1-2
Algorithm 1 RANDOM(a,b) 1: n = lg(b − a + 1) 2: Initialize an array A of length n 3: while true do 4: for i = 1 to n do 5: A[i] = RAN DOM (0, 1) 6: end for 7: if A holds the binary representation of one of the numbers in a through b then 8: return number represented by A 9: end if 10: end while Each iteration of the while loop takes n time to run. The probability that the while loop stops on a given iteration is (b − a + 1)/2n . Thus the expected running time is the expected number of times run times n. This is given by: n
loop. This program will expect to go through the loop a number of times equal to:
∞
j (1 − 2p(p − 1))j (2p(p − 1)) =
j =0
1 − 2p(p − 1) 2p(p − 1)(1 − 2p(p − 1)) = (2p(p − 1))2 2p(p − 1)
i≥1
i 1−
b−a+1 2n
i −1
b−a&2n
2n b−a+1
2
=n
2n = O(lg(b−a)). b−a+1
Exercise 5.1-3 Clearly since a and b are IID, the probability this algorithm returns one is equal to the probability it returns 0. Also, since there is a constant positive probability (2p(p − 1)) that the algorithm returns on each iteration of the for
Note that the formula used for the sum of jαj can be obtained by diﬀerentiawting both sides of the geometric sum formula for αj with respect to α Exercise 5.2-1 You will hire exactly one time if the best candidate is presented ﬁrst. There are (n − 1)! orderings with the best candidate ﬁrst, so, it is with probability (n−1)! 1 = n that you only hire once. You will hire exactly n times if the candin! dates are presented in increasing order. This ﬁxes the ordering to a single one, 1 and so this will occur with probability n !. Exercise 5.2-2 Since the ﬁrst candidate is always hired, we need to compute the probability that that exactly one additional candidate is hired. Since we view the candidate ranking as reading an random permutation, this is equivalent to the probability that a random permutation is a decreasing sequence followed by an increase, followed by another decreasing sequence. Such a permutation can be thought of as a partition of [n] into 2 parts. One of size k and the other of size n − k , where 1 ≤ k ≤ n − 1. For each such partition, we obtain a permutation with a single increase by ordering the numbers each partition in decreasing order, then concatenating these sequences. The only thing that can go wrong is if the numbers n through n − k + 1 are in the ﬁrst partition. Thus there are n k −1 permutations which correspond to hiring the second and ﬁnal person on step k + 1. Summing, we see that the probability you hire exactly twice is