From definition of Big O
f(n) = O(g(n))
if f(n) <= g(n)
a)
b)
c)
d)
The answers for the following questions are given as handwritten notes.
1. For each of the following, prove using the definition of O): (a) 7n + log(n)...
Prove this using the definition R7: log(n*) is O(log n) for any fixed x > 0
Let f(n) = 5n^2. Prove that f(n) = O(n^3). Let f(n) = 7n^2. Prove that f(n) = Ω(n). Let f(n) = 3n. Prove that f(n) =ꙍ (√n). Let f(n) = 3n+2. Prove that f(n) = Θ (n). Let k > 0 and c > 0 be any positive constants. Prove that (n + k)c = O(nc). Prove that lg(n!) = O(n lg n). Let g(n) = log10(n). Prove that g(n) = Θ(lg n). (hint: ???? ? = ???? ?)???? ?...
Prove each of the following using the definition of Big-Oh. a)(?+1)5is O(?5) b)2?+1is O(2?) c)If ?(?)is a polynomial in ?, then ????(?)is ?(log?)
(10) Prove ONLY ONE of the following statements using the principle of mathematical induction 7n n(n+3) (11) Give a recurrence definition of the following sequence: an 2n +1, n 1,2,3,..
Prove (using the definition of O) or disprove (via counter-example): If f(n) = O(n)), and g(n) = O(n2), then f(n) + g(n) = O(n5). Prove (using the definition of O) or disprove (via counter-example): If f(n) = O(n), and g(n) = O(n2), then fin)/g(n) = O(n).
Please explain big O. I don't get it Prove the following, using either the definition of Big-O or a limit argument. (a) log_2 (n) elementof O(n/log_2(n)) (b) 2^n elementof O(n!) (c) log_2(n^2) + log_2 (100n^10) elementof O(log_2 (n)) (d) n^1/2 elementof O(n^2/3) (e) log(3n) elementof O(log(2n)) (f) 2^n elementof O(3^n/n^2)
1. Prove that log2(n) is O(n) 2. Prove that log(n!) is O(n log(n))
1. a) Let f(n) = 6n2 - 100n + 44 and g(n) = 0.5n3 . Prove that f(n) = O(g(n)) using the definition of Big-O notation. (You need to find constants c and n0). b) Let f(n) = 3n2 + n and g(n) = 2n2 . Use the definition of big-O notation to prove that f(n) = O(g(n)) (you need to find constants c and n0) and g(n) = O(f(n)) (you need to find constants c and n0). Conclude that...
Which of the following could be false? A. n2/(log(n)) = O(n2). B. (log n)1000 = O(n1//1000). C. 1/n = O(1/(log(n))). D. 2(log(n))^2 = O(n2). E. None of the above.
1. For each of the following pairs of functions, prove that f(n)-O(g(n)), and / or that g(n) O(f(n)), or explain why one or the other is not true. (a) 2"+1 vs 2 (b) 22n vs 2" VS (c) 4" vs 22n (d) 2" vs 4" (e) loga n vs log, n - where a and b are constants greater than 1. Show that you understand why this restriction on a and b was given. f) log(0(1) n) vs log n....