Proving a[n] = Θ(lg n): A Case Study

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SUMMARY

The discussion centers on proving that the sequence {a[n]} defined by the recurrence relation a[n] = a[n/m] + d, where m divides n, satisfies the asymptotic notation a[n] = Θ(lg n). The participants establish that a[n] is O(lg n) by demonstrating that a[n/2] + d serves as an upper bound. The challenge lies in proving that a[n] is also Ω(lg n), which requires identifying a sequence {x_i} such that a[x_i] grows logarithmically. The conversation highlights the importance of addressing cases where n is odd and clarifies the recurrence relation as a_n = a_{\lfloor n/2 \rfloor} + d.

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  • Understanding of asymptotic notation (Θ, O, Ω)
  • Familiarity with recurrence relations in algorithm analysis
  • Knowledge of logarithmic growth rates
  • Basic principles of number theory regarding divisibility
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  • Learn about logarithmic functions and their properties
  • Explore examples of sequences defined by recurrence relations
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a[n] = Θ(lg n)!?

Suppose {a[n]} is an increasing sequence and whenever m divides n, then

a[n] = a[n/m] + d

where m is a positive integer and d is a real number. Show that a[n] = Θ(lg n).

a[n/m] + d ≤ a[n/2] + d, and with this I can show that a[n] = O(lg n). All I need to do is show that a[n] = Ω(lg n). This is where I'm stuck. Any hints?
 
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To show that something is in omega(log x), it suffices to find some sequence {x_i} such that a[x_i] grows like log x.

By the way, I'm disconcerted with your reasoning that it is in O(log x); what if n is odd? I suppose you're just abbreviating the complete proof you have.
 
Hurkyl said:
By the way, I'm disconcerted with your reasoning that it is in O(log x); what if n is odd? I suppose you're just abbreviating the complete proof you have.
Sorry. What I meant was

[tex]a_n = a_{\lfloor n/2 \rfloor} + d[/tex]

My head is a total blank. I can't think of anything.
 

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