rec01 - 6.006 Intro to Algorithms Recitation 01 February 2...

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Unformatted text preview: 6.006 Intro to Algorithms Recitation 01 February 2, 2011 Asymptotic analysis Asymptotic analysis or “big O” notation is a way of describing the growth of the runtime of an algorithm without without having to worry about different computers, compilers, or implementa- tions. For functions f ( n ) , g ( n ) , O ( g ( n )) is a class of functions such that f ( n ) ∈ O ( g ( n )) if there exist M,x such that | f ( n ) | ≤ M · | g ( n ) | for all x > x . Similarly, f ( n ) ∈ Ω( g ( n )) if there exist M,x such that | f ( n ) | ≥ M · | g ( n ) | for all x > x . If f ( n ) ∈ O ( g ( n )) and f ( n ) ∈ Ω( g ( n )) , then we write f ( n ) ∈ Θ( g ( n )) . x = ( x 2 ) M = ,x = (1) x = ( log x ) M = ,x = (2) x 3 = (2 x ) M = ,x = (3) 6.006 Intro to Algorithms Recitation 01 February 2, 2011 Python This class uses Python 2.6. Do not use Python 3. If you’re not familiar with Python, there are numerous resources available on the Internet: • Python tutorial: http://docs.python.org/tutorial/http://docs....
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This note was uploaded on 11/11/2011 for the course MATH 180 taught by Professor Byrns during the Spring '11 term at Montgomery College.

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rec01 - 6.006 Intro to Algorithms Recitation 01 February 2...

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