Concrete mathematics : a foundation for computer science

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564 ANSWERS TO EXERCISES 8.56 If m is even, the frisbees always stay an odd distance apart and the game lasts forever. If m = i:l. + 1, the relevant generating functions are (The coefficient [z”] Ak is the probability that the distance between frisbees is 2k after n throws.) Taking a clue from the similar equations in exercise 49, we set z = 1 /cos’ 8 and Al := X sin28, where X is to be determined. It follows by induction (not using the equation for Al) that Ak = X sin2kO. Therefore we want to choose X such that ( 3 1-p X sin;!10 = 1 +& X sin(21- 218. 4cos28 > It turns out that X = 2 cos’ O/sin 8 cos(21+ 1 )O, hence cos e G, = - cos me ’ The denominator vanishes when 8 is an odd multiple of n/(2m); thus 1 -qkz is a root of the denominator for 1 6 k 6 1, and the stated product representation must hold. To find the mean and variance we can write Trigonometry wins again. is there a G, = (1 - $2 + L.04 - . . )/(I - $2@ + &m4@4 - . . . ) connection with pitching pennies = 1 + i(m2 - 1)02 + &(5m4 -6m2+ 1)04 +... = 1 +~(m2-l)(tanB)2+~(5m4-14m2+9)(tan8)4+~~~ = 1 + G:,(l)(tan8)2 + iGK(1)(tan8)4 +... , because tan28 = Z- 1 and tan8 =O+ i03 +.... So we have Mean = i(m2-1) andVar(G,) = im2(m2-1). (Note that thisimplies theidentities m2 - 1 ~ = 2 (m-1 l/2 & i = 'mjf'2(l/sin "",r,,')")'; lm Ii/2 m2(m2 - 1) - cot (2k- 1)~ (2k- 1)n 2 6 = u 2m I sin 2m > ’ k=l The third cumulant of this distribution is &m2(m2 - l)(4m2 - 1); but the pattern of nice cumulant factorizations stops there. There’s a much simpler k=l along the angles of the m-gon?
A ANSWERS TO EXERCISES 565 way to derive the mean: We have G, + Al +. + Ar = z(Ar +. . . + AL) + 1, hence when z = 1 we have Gk = Al +. + Al. Since G, = 1 when z = 1, an easy induction shows that Ak = 4k.) 8.57 We have A:A 3 2’ ’ and B:B < 2l ’ + 2l 3 and B:A 3 2’ 2, hence 13:B - B:A 3 A:A - A:B is possible only if A:B > 21p3. This means that 52 = ~3, ~1 = ~4, ~2 = ‘~5, . , rr 3 = rr. But then A:A zz 2’ ’ + 2’ 4 + ..I A:B z 2’ 3 + 2’ 6 +. , B:A z 2’ ’ + 2’ 5 +. . . , and B:B z 2’ -’ + 2’ 4 + . . . ; hence B:B - B:A is less than A:A - A:B after all. (Sharper results have been obtained by Guibas and Odlyzko [138], who show that Bill’s chances are always maximized with one of the two patterns H-r1 . . . rl I or Trl rl , .) 8.58 According to r(8.82), we want B:B - B:A > A:A - A:B. One solution is A = TTHH, B = HHH. 8.59 (a) Two cases arise depending on whether hk # h, or hk = h,: m - l m-2+w+z k-1 m-l+2 nmk G(w,z) = ---( > ( l > 1 rn-cwzJk lwZ~m.:;S k-lZ.z +- m ( (b) We can either argue algebraically, taking partial derivatives of G (w, z) with respect to w and z and setting w = z = 1; or we can argue combinatorially: Whatever the values of hl, . . . , h, -1, the expected value of P(hl , . , h, 1, h,; n) is the same (averaged over h,), because the hash sequence (hr , . . . , h, 1) determines a sequence of list sizes (nl , n2,. . , n,) such that the stated expected value is ((nr+l) + (nz+l) + ... + (n,+l))/m = (n - 1 + m)/m. Therefore the random variable EP( hl , . . . , h,,; n) is independent of (hl , . , h, I), hence independent of P( hr , . . , h,; k). 8.60 If 1 6 k < 1 :$ n, the previous exercise shows that the coefficient of sksr in the variance of the average is zero. Therefore we need only consider the coefficient of si, which is t 1Sh1 ,...I h,,Sm -’ Pih,,...,h,;k)2 mn -( t l
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CONCRETE MATHEMATICS Dedicated to L
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CONCRETE MATHEMATICS Ronald L. Grah
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“A odience, level, and treatment
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‘I a concrete life preserver thro
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I’m unaccustomed to this face. De
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n [ n-l 1 n {I m Prestressed concre
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CONTENTS xiii 5.3 Tricks of the Tra
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2 RECURRENT PROBLEMS It’s not imm
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4 RECURRENT PROBLEMS Of course the
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6 RECURRENT PROBLEMS through any of
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8 RECURRENT PROBLEMS From these sma
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10 RECURRENT PROBLEMS But what abou
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12 RECURRENT PROBLEMS that is, in t
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14 RECURRENT PROBLEMS by separating
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16 RECURRENT PROBLEMS For example,
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18 RECURRENT PROBLEMS Homework exer
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20 RECURRENT PROBLEMS 21 Suppose th
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22 SUMS The three-dots notation has
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24 SUMS A slightly modified form of
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26 SUMS where A(n), B(n), and C(n)
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28 SUMS Let’s apply these ideas t
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30 SUMS 2.3 MANIPULATION OF SUMS No
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32 SUMS Typically we use rule (2.20
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34 SUMS because the derivative of a
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36 SUMS instead of summing over all
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38 SUMS The second sum here is zero
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40 SUMS The normal way to evaluate
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42 SUMS First, as usual, we look at
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44 SUMS order to get an equation fo
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46 SUMS One way to use this fact is
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48 SUMS definition where the factor
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50 SUMS Let’s try to recap this;
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52 SUMS we need an appropriate defi
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54 SUMS This formula indicates why
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56 SUMS u(x) = x and Av(x) = 2’;
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58 SUMS The definition in the previ
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60 SUMS In fact, our definition of
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62 SUMS tCj,kiEF a. J, k < A for al
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64 SUMS 18 Let 9%~ and Jz be the re
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66 SUMS 34 35 36 Prove that if the
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68 INTEGER FUNCTIONS below the line
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70 INTEGER FUNCTIONS same inequalit
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72 INTEGER FUNCTIONS An important s
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74 INTEGER FUNCTIONS By the way, th
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76 INTEGER FUNCTIONS (Previously K
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78 INTEGER FUNCTIONS This derivatio
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80 INTEGER FUNCTIONS We’ve got mo
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82 INTEGER FUNCTIONS division, and
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84 INTEGER FUNCTIONS more than one
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86 INTEGER FUNCTIONS 3.5 FLOOR/CEIL
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88 INTEGER FUNCTIONS For this purpo
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90 INTEGER FUNCTIONS it comes out i
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92 INTEGER FUNCTIONS To summarize,
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94 INTEGER FUNCTIONS Also, as we gu
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96 INTEGER FUNCTIONS Basics 10 Show
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98 INTEGER FUNCTIONS 31 Prove or di
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100 INTEGER FUNCTIONS 43 Find an in
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4 Number Theory INTEGERS ARE CENTRA
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104 NUMBER THEORY The left side can
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106 NUMBER THEORY product of primes
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108 NUMBER THEORY only finitely man
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110 NUMBER THEORY But 2P - 1 isn’
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112 NUMBER THEORY arrangements in a
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114 NUMBER THEORY The binary repres
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116 NUMBER THEORY A fraction m/n is
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118 NUMBER THEORY A mediant fractio
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120 NUMBER THEORY This representati
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122 NUMBER THEORY This means that w
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124 NUMBER THEORY Since x mod m dif
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126 NUMBER THEORY than to say that
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128 NUMBER THEORY require division,
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130 NUMBER THEORY Now we must show
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132 NUMBER THEORY And it’s possib
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134 NUMBER THEORY For example, (~(1
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136 NUMBER THEORY Conversely, if f(
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138 NUMBER THEORY (We must add 1 to
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140 NUMBER THEORY The problem of co
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142 NUMBER THEORY n is odd, n4 and
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144 NUMBER THEORY But the inner sum
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146 NUMBER THEORY 22 The number 111
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148 NUMBER THEORY 40 If the radix p
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150 NUMBER THEORY 57 Let S(m,n) be
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152 NUMBER THEORY 73 If the 0(n) +
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154 BINOMIAL COEFFICIENTS For examp
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156 BINOMIAL COEFFICIENTS And now t
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158 BINOMIAL COEFFICIENTS property
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160 BINOMIAL COEFFICIENTS (3, then
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162 BINOMIAL COEFFICIENTS Binomial
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164 BINOMIAL COEFFICIENTS Table 164
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166 BINOMIAL COEFFICIENTS not rows.
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168 BINOMIAL COEFFICIENTS Equation
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170 BINOMIAL COEFFICIENTS that m =
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172 BINOMIAL COEFFICIENTS ifweuse (
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176 BINOMIAL COEFFICIENTS sum on th
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178 BINOMIAL COEFFICIENTS some data
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180 BINOMIAL COEFFICIENTS Problem 4
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182 BINOMIAL COEFFICIENTS We’re l
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184 BINOMIAL COEFFICIENTS We can’
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186 BINOMIAL COEFFICIENTS 5.3 TRICK
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188 BINOMIAL COEFFICIENTS if we app
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190 BINOMIAL COEFFICIENTS The Newto
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192 BINOMIAL COEFFICIENTS One examp
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194 BINOMIAL COEFFICIENTS We can de
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196 BINOMIAL COEFFICIENTS This obse
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198 BINOMIAL COEFFICIENTS Generatin
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200 BINOMIAL COEFFICIENTS can be pu
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204 BINOMIAL COEFFICIENTS This hold
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206 BINOMIAL COEFFICIENTS It’s ou
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208 BINOMIAL COEFFICIENTS into this
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210 BINOMIAL COEFFICIENTS integer.
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212 BINOMIAL COEFFICIENTS into to b
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214 BINOMIAL COEFFICIENTS Now sin(
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216 BINOMIAL COEFFICIENTS But look
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218 BINOMIAL COEFFICIENTS It’s al
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220 BINOMIAL COEFFICIENTS A similar
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222 BINOMIAL COEFFICIENTS One use o
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224 BINOMIAL COEFFICIENTS Therefore
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226 BINOMIAL COEFFICIENTS Now f(-b)
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228 BINOMIAL COEFFICIENTS negative
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230 BINOMIAL COEFFICIENTS valid for
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232 BINOMIAL COEFFICIENTS 18 Find a
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234 BINOMIAL COEFFICIENTS 37 Show t
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236 BINOMIAL COEFFICIENTS 57 Use Go
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238 BINOMIAL COEFFICIENTS 72 Prove
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240 BINOMIAL COEFFICIENTS 86 Let al
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242 BINOMIAL COEFFICIENTS Research
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244 SPECIAL NUMBERS Table 244 Stirl
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246 SPECIAL NUMBERS There are eleve
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248 SPECIAL NUMBERS cycle arrangeme
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250 SPECIAL NUMBERS Table 250 Basic
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252 SPECIAL NUMBERS We can remember
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254 SPECIAL NUMBERS Table 254 Euler
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{'l 'I L\‘, 0 1 / 2 256 SPECIAL N
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258 SPECIAL NUMBERS Table 258 Stirl
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260 SPECIAL NUMBERS ’ ’ ’ (Th
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262 SPECIAL NUMBERS we found that a
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264 SPECIAL NUMBERS Rearranging, we
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266 SPECIAL NUMBERS Thus we have th
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268 SPECIAL NUMBERS (We have used t
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270 SPECIAL NUMBERS Bernoulli numbe
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272 SPECIAL NUMBERS trigonometric f
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274 SPECIAL NUMBERS Recurrence (6.9
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276 SPECIAL NUMBERS Gnethingwecando
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278 SPECIAL NUMBERS cases are: a0 =
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280 SPECIAL NUMBERS The process of
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282 SPECIAL NUMBERS Fk < n < Fk+l;
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284 SPECIAL NUMBERS We have now boi
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286 SPECIAL NUMBERS Before we stop
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288 SPECIAL NUMBERS The continuant
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290 SPECIAL NUMBERS in four steps:
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292 SPECIAL NUMBERS Thus we can con
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294 SPECIAL NUMBERS numbers are 1,
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296 SPECIAL NUMBERS 6 An explorer h
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298 SPECIAL NUMBERS 24 Prove that t
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300 SPECIAL NUMBERS 44 Prove the co
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302 SPECIAL NUMBERS 61 Prove the id
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304 SPECIAL NUMBERS 80 Show that co
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7 Generating Functions THE MOST POW
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308 GENERATING FUNCTIONS are added
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310 GENERATING FUNCTIONS (The last
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312 GENERATING FUNCTIONS Now we hav
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314 GENERATING FUNCTIONS The first
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316 GENERATING FUNCTIONS determine
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318 GENERATING FUNCTIONS operation
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320 GENERATING FUNCTIONS Table 320
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322 GENERATING FUNCTIONS middle of
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324 GENERATING FUNCTIONS Fortunatel
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326 GENERATING FUNCTIONS Once we’
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328 GENERATING FUNCTIONS Step 1 is
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330 GENERATING FUNCTIONS nice prope
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332 GENERATING FUNCTIONS Finally, s
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334 GENERATING FUNCTIONS Step 3 was
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336 GENERATING FUNCTIONS This is a
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338 GENERATING FUNCTIONS Table 337
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340 GENERATING FUNCTIONS F(z)' = i
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342 GENERATING FUNCTIONS We can app
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344 GENERATING FUNCTIONS Step 3 is
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346 GENERATING FUNCTIONS Raney’s
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348 GENERATING FUNCTIONS Notice tha
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350 GENERATING FUNCTIONS Chapter 5
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352 GENERATING FUNCTIONS Now let’
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354 GENERATING FUNCTIONS function f
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356 GENERATING FUNCTIONS 7.7 DIRICH
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358 GENERATING FUNCTIONS 5 Find a g
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360 GENERATING FUNCTIONS 20 A power
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362 GENERATING FUNCTIONS 29 What is
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364 GENERATING FUNCTIONS 43 The New
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366 GENERATING FUNCTIONS 53 The seq
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368 DISCRETE PROBABILITY total of 6
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370 DISCRETE PROBABILITY about R if
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372 DISCRETE PROBABILITY The mean o
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374 DISCRETE PROBABILITY more sprea
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376 DISCRETE PROBABILITY hence VS =
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378 DISCRETE PROBABILITY And we can
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380 DISCRETE PROBABILITY variance b
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382 DISCRETE PROBABILITY (1 +z+...
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384 DISCRETE PROBABILITY ~1 and ~2
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386 DISCRETE PROBABILITY where Ug i
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388 DISCRETE PROBABILITY Repeating
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390 DISCRETE PROBABILITY There’s
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392 DISCRETE PROBABILITY But the co
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394 DISCRETE PROBABILITY In the spe
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396 DISCRETE PROBABILITY Here 1 is
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398 DISCRETE PROBABILITY For exampl
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400 DISCRETE PROBABILITY Thus the m
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402 DISCRETE PROBABILITY Let sj be
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404 DISCRETE PROBABILITY Therefore
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406 DISCRETE PROBABILITY The mean v
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408 DISCRETE PROBABILITY Complicate
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410 DISCRETE PROBABILITY all k and
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412 DISCRETE PROBABILITY to be a pg
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414 DISCRETE PROBABILITY 10 What’
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416 DISCRETE PROBABILITY 28 What is
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418 DISCRETE PROBABILITY 38 What is
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420 DISCRETE PROBABIL1T.Y a Once he
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422 DISCRETE PROBABILITY 50 Conside
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424 DISCRETE PROBABILITY 58 Are the
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426 ASYMPTOTICS The word asymptotic
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428 ASYMPTOTIC3 How about the funct
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430 ASYMPTOTICS N. G. de Bruijn beg
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432 ASYMPTOTICS subtle consideratio
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434 ASYMPTOTICS inefficient “beca
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436 ASYMPTOTICS 9.3 0 MANIPULATION
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138 ASYMPTOTICS Table 438 Asymptoti
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440 ASYMPTOTICS Notice how the 0 te
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442 ASYMPTOTICS Problem 3: The nth
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444 ASYMPTOTICS Problem 4: A sum fr
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446 ASYMPTOTICS Problem 5: An infin
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448 ASYMPTOTICS We might as well do
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450 ASYMPTOTIC3 a rough estimate an
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452 ASYMPTOTICS This last estimate
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454 ASYMPTOTICS Here’s another ex
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456 ASYMPTOTICS On the left is a ty
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458 ASYMPTOTICS (The Bernoulli poly
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460 ASYMPTOTICS The graph of B,(x)
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462 ASYMPTOTICS 9.6 FINAL SUM:MATIO
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464 ASYMPTOTICS The integral JT B4(
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466 ASYMPTOTIC3 where 0 < a,,,, < 1
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468 ASYMPTOTICS In Chapter 5, equat
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470 ASYMPTOTICS For example, we hav
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472 ASYMPTOTICS The final task seem
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474 ASYMPTOTICS This is our approxi
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476 ASYMPTOTIC23 9 Prove (9.22) rig
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478 ASYMPTOTICS 39 Evaluate xOsk
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480 ASYMPTOTICS a What is the asymp
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482 ASYMPTOTIC3 Research problems 6
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484 ANSWERS TO EXERCISES Venn [294]
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486 ANSWERS TO EXERCISES move the b
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488 ANSWERS TO EXERCISES 2.2 This i
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490 ANSWERS TO EXERCISES 2.24 Summi
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492 ANSWERS TO EXERCISES 2.36 (a) B
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494 ANSWERS TO EXERCISES 3.21 If 10
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496 ANSWERS TO EXERCISES the circle
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498 ANSWERS TO EXERCISES 3.40 Let L
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500 ANSWERS TO EXERCISES 3.50 H. S.
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502 ANSWERS TO EXERCISES 4.22 (b,
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504 ANSWERS TO EXERCISES 4.40 Let f
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506 ANSWERS TO EXERCISES 4.50 (a) I
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508 ANSWERS TO EXERCISES and (k- 1)
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510 ANSWERS TO EXERCISES In both ca
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512 ANSWERS TO EXERCISES 5.7 Yes, b
Page 528 and 529: 514 ANSWERS TO EXERCISES because al
Page 530 and 531: 516 ANSWERS TO EXERCISES 5.44 Cance
Page 532 and 533: 518 ANSWERS TO EXERCISES and this i
Page 534 and 535: 520 ANSWERS TO EXERCISES The infini
Page 536 and 537: 522 ANSWERS TO EXERCISES 5.82 Let ~
Page 538 and 539: 524 ANSWERS TO EXERCISES Since ~06j
Page 540 and 541: 526 ANSWERS TO EXERCISJES 5.94 This
Page 542 and 543: 528 ANSWERS TO EXERCISES 6.21 The h
Page 544 and 545: 530 ANSWERS TO EXERCISIES 6.40 If 6
Page 546 and 547: 532 ANSWERS TO EXERCISES solutions
Page 548 and 549: 534 ANSWERS TO EXERCISES 6.62 (a) A
Page 550 and 551: 536 ANSWERS TO EXERCISES 6.74 If p(
Page 552 and 553: 538 ANSWERS TO EXERCISIES One of th
Page 554 and 555: 540 ANSWERS TO EXERCISES 6.85 The p
Page 556 and 557: 542 ANSWERS TO EXERCISES Hence gzn+
Page 558 and 559: 544 ANSWERS TO EXERCISES 7.24 ntk,+
Page 560 and 561: 546 ANSWERS TO EXERCISES 7.40 The e
Page 562 and 563: 548 ANSWERS TO EXERCISES 1 + a. Hen
Page 564 and 565: 550 ANSWERS TO EXERCISES applied to
Page 566 and 567: 552 ANSWERS TO EXERCISES 8.13 (Solu
Page 568 and 569: 554 ANSWERS TO EXERCISES 8.24 (a) A
Page 570 and 571: 556 ANSWERS TO EXERCISES 8.32 By sy
Page 572 and 573: 558 ANSWERS TO EXERCISES 8.37 The n
Page 574 and 575: 560 ANSWERS TO EXERCISES probabilit
Page 576 and 577: 562 ANSWERS TO EXERCISES And since
Page 580 and 581: 566 ANSWERS TO EXERCISES We can now
Page 582 and 583: 568 ANSWERS TO EXERCISES 9.19 Hlo =
Page 584 and 585: 570 ANSWERS TO EXERCIS:ES 9.30 Let
Page 586 and 587: 572 ANSWERS TO EXERCISES 9.42 The h
Page 588 and 589: 574 ANSWERS TO EXERCISIES length of
Page 590 and 591: 576 ANSWERS TO EXERCISES 9.58 Let 0
Page 592 and 593: B Bibliography HERE ARE THE WORKS c
Page 594 and 595: 580 BIBLIOGRAPHY 24' 25 26 27 28 29
Page 596 and 597: 582 BIBLIOGRAPHY 51 52 53 54 55 56
Page 598 and 599: 584 BIBLIOGRAPHY 78 79 80 81 82 83
Page 600 and 601: 586 BIBLIOGRAPHY 100 R. A. Fisher,
Page 602 and 603: 588 BIBLIOGRAPHY 128 Ronald L. Grah
Page 604 and 605: 590 BIBLIOGRAPHY 160 K. Inkeri, “
Page 606 and 607: 592 BIBLIOGRAPHY 188 E.E. Kummer,
Page 608 and 609: 594 BIBLIOGRAPHY 214 Z.A. Melzak, C
Page 610 and 611: 596 BIBLIOGRAPHY 243 George N. Rane
Page 612 and 613: 598 BIBLIOGRAPHY 271 A. D. Solov’
Page 614 and 615: 600 BIBLIOGRAPHY 299 Louis Weisner,
Page 616 and 617: 602 CREDITS FOR EXERCISES 1.1 1.2 1
Page 618 and 619: 604 CREDITS FOR EXERCISES 6.46 6.47
Page 620 and 621: Index WHEN AN INDEX ENTRY refers to
Page 622 and 623: 608 INDEX Bois-Reymond, Paul David
Page 624 and 625: 610 INDEX Degenerate hypergeometric
Page 626 and 627: 612 INDEX Feder, Tom&s, 604. Feigen
Page 628 and 629:
614 INDEX Hall, Marshall, Jr., 588.
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616 INDEX Lincoln, Abraham, 387. Li
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618 INDEX Patashnik, Oren, iii, iv,
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620 INDEX Running time, 411-412. Ru
Page 636 and 637:
622 INDEX Sylvester, James Joseph,
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List of Tables Sums and differences
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Concrete mathematics : a foundation for computer science

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