EECS
lec15-complexity

# lec15-complexity - EECS 203 Winter 2007 Discrete...

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EECS 203, Winter 2007 Discrete Mathematics Lecture 15 Complexity of algorithms February 22 Reading: Rosen [3.3] February 22 Complexity of algorithms, Page 1

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15.1 Complexity measures How to measure the running time of an algorithm? Examples: linear search, Bubble sort, insertion sort, merge February 22 Complexity of algorithms, Page 2
15.2 Recursive algorithms Examples: binary search, merge sort.

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Unformatted text preview: Complexity of algorithms, Page 3 15.3 Complexity classes P: the class of decision problems having a polynomial time algorithm. NP: the class of decision problems whose positive instance can be veriﬁed in polynomial time. Example of an NP problem: Clique. NP-complete problems: in NP and hardest in NP. Is P=NP? February 22 Complexity of algorithms, Page 4...
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• Winter '07
• YaoyunShi
• Algorithms, Big O notation, Computational complexity theory

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