lec14&amp;15

# lec14&amp;15 - Discrete Computation Structures CSE 2353...

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Discrete Computation Structures CSE 2353 Bhanu Kapoor, PhD Department of Computer Science & Engineering Southern Methodist University, Dallas, TX [email protected] , 214-336-4973 October 15 and 20, 2009 Embrey 129, SMU, Dallas, Texas Lectures 14 and 15 1

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Lecture 12 & 13 Agenda Bi i l C ffi i t Binomial Coefficients Recurrence 2
Binomial Coefficients ALGORITHM 7.3: Determine C ( n , r ) using dynamic programming programming. Input: n , r , n > 0, r > 0, r n Output: C ( n , r ) 1 function combDynamicProg (n r) 1. (n,r) 2. begin 3. for i := 0 to n do 4. for j := 0 to min(i,r) do 5. if j = 0 or j = i then 6. C[i,j] := 1; 7. else 8. C[i,j] := C[i-1, j-1] + C[i-1, j]; 9. return C[n, r]; 10. end 3

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Sequences and Recurrence Relations 4
Sequences and Recurrence Relations 5

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Sequences and Recurrence Relations 6
Sequences and Recurrence Relations 7

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Sequences and Recurrence Relations 8
Sequences and Recurrence Relations 9

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Linear Homogenous Recurrence Relations 11

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Linear Homogenous Recurrence Relations 12
Linear Homogenous Recurrence Relations 13

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Linear Homogenous Recurrence Relations 14
Linear Homogenous Recurrence Relations 15

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Linear Homogenous Recurrence Relations 16
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Design and Analysis of Algorithms Analysis: predict the cost of an algorithm in terms of resources and performance Design: design algorithms which minimize the cost Hard Problems: for some problems no efficient algorithms exist => NP-Complete problems, Equally important to know that you are dealing with such a problem. 19

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Why algorithms are important? Total system performance depends upon both hardware and software Hardware with high clock rates Pipelining Superscalar architecture Very high speed networking Poor choice of algorithm can bring the highest f i hi t it k performing machine to its knees Problem sizes that we are dealing with is also increasing Complexity of solution needed is also increasing 20
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