3.1.1 Bounding Summations

Knowledge Base > Algorithm > Recurrence


We first introduce a few methods for bounding the summations that describe the running times of algorithm. The following subsections are the most frequently used techniques.

Mathematical Induction

The most basic way to prove a series equation is to use mathematical induction.

Method 3.1.1
Assume you have a series:

 n
∑  f (k) = g(n)
k=1
You first need to prove the equation holds for the base case, that is, f(k = 1) = g(1). Next, we assume the equation ’is’ correct, and call that Inductive Hypothesis. The last goal is to prove if it holds for (n + 1) case.

For example,

 n
∑  k = 1⋅n ⋅(n+ 1)(from equation 1.7.0.14)
k=1    2
Proof>
(Base)
∑1        1
   k = 1 = 2 ⋅1⋅2 = 1
k=1
(Inductive Hypothesis), Assume
∑n     1
   k = -⋅n ⋅(n+ 1)
k=1    2
Need to prove
n∑+1
    k = 1 ⋅(n+ 1)⋅(n +2)
k=1    2
Sol>
n∑+1       ∑n
   k  =      k+ (n+ 1)
k=1       k=1
      =   1 ⋅n ⋅(n+ 1)+ (n +1)
          2
      =   n⋅(n-+-1)+-2⋅(n+-1)
                   2
      =   n2 +-3-⋅n+-2
               2
      =   1 ⋅(n + 1)⋅(n + 2)
          2
Thus, proved.

Bounding the Terms

Method 3.1.2
A quick upper bound on a series can be obtained by bounding each term of the series with the largest term. That is,

∑n        ∑n
   ak  ≤     aMAX
k=1    =  kn=1⋅a
              MAX
Conversely, a quick lower bound can be evaluated by bounding each term with the smallest term. That is,
∑n        ∑n
   ak  ≥      aMIN
k=1       k=1
       =  n ⋅aMIN

Splitting Summations

Method 3.1.3
Another technique to get a bound is to express the series as the sum of two or more series by partitioning the range of the index and then to bound each of the resulting series[1]. That is,

n         k0- 1     n
∑  ak  =  ∑   ak + ∑  ak
k=1        k=1     k=k0

Approximation by Integrals

Method 3.1.4
When a function f(k) is a monotonically increasing function, the summation of f(k) can be approximated by integrals,

∫ n           n        ∫ n+1
     f(x )dx ≤ ∑   f(k ) ≤     f(k)dx           (3.1.1.1)
 m-1         k=m        m
When f(k) is a monotonically decreasing function, the summation of f(k) can be bounded by integrals,
∫                      ∫
  n+1         ∑n         n
 m   f(x)dx ≤    f(k) ≤ m -1f(k)dx           (3.1.1.2)
             k=m

For example, the integral approximation gives a tight bound for the nth harmonic number (monotonically decreasing),

          ∫
∑n 1-       k+1dx-
   k  ≥    1    x
k=1
      =   ln (n + 1)
      =   Ω(ln n)
∑n 1         ∑n 1
   k- =   1+    k-
k=1       ∫  k=2
      ≤     ndx-
           1  x
      =   ln n
      =   O(lnn)
∑n
   1- =   Θ(lnn)                   (3.1.1.3)
k=1k