Design and Analysis of Algorithms"All aspects pertaining to algorithm design and algorithm analysis have been discussed over the chapters in this book-- Design and Analysis of Algorithms"--Resource description page. |
Contents
Chapter | 3 |
Introduction | 4 |
Introduction | 5 |
Problem Solving with a Computer | 16 |
Structured Programming | 48 |
4 | 58 |
5 | 75 |
6 | 82 |
Efficiency of Algorithms | 370 |
Efficiency of Algorithms | 371 |
Examples of Complexity Calculation | 404 |
TimeSpace TradeOff | 434 |
TimeSpace TradeOff | 435 |
Tractable and NonTractable Problems | 462 |
Some NP and NPComplete Problems | 504 |
Some NP and NPComplete Problems | 505 |
Computation Models and Design by Refinement | 89 |
3 | 106 |
Summary | 116 |
Proof RulesBasics | 120 |
Chapter 6 | 122 |
Design by Proof Rules | 152 |
Design by Proof Rules | 153 |
Chapter 8 | 173 |
3 | 179 |
Design using Recursion | 180 |
जैजै | 221 |
4 | 229 |
Abstract Algorithms 2Greedy Methods | 236 |
Abstract Algorithms 2Greedy Methods | 237 |
Abstract Algorithms 3Dynamic Programming | 268 |
76 | 304 |
Abstract Algorithms 4Backtracking | 310 |
Natural AlgorithmsGA SA ANN TS | 340 |
Randomized and Approximate Algorithms | 524 |
Randomized and Approximate Algorithms | 525 |
Formal Specifications1 Model Oriented | 558 |
Formal Specifications1 Model Oriented | 559 |
Formal Specifications2 Algebraic | 588 |
Appendix A Essential Mathematical Background | 611 |
Sets | 620 |
Formal Languages | 626 |
Random Variables | 634 |
Appendix B Some Useful Mathematical Formulae | 642 |
Overview of Essential Data Structures | 667 |
Solutions of Recurrence Relations | 701 |
Appendix E Additional Exercises with Solutions | 720 |
| 794 | |
| 803 | |
| 804 | |
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Common terms and phrases
analysis array artificial neural networks backtracking Binomial heap called complexity condition consider construct cost data structure defined denote discussed divisor dynamic programming edges efficiency elements example execution expression Fibonacci Fibonacci heap given graph greedy heap implementation input integer iterative Key Terms Kruskal's algorithm loop invariant matrix memory mergesort method minimum minimum spanning tree multiplications neural networks neurons NIL NIL node notation Note NP-Complete NP-hard O(n² operations optimal solution optimal substructure output parameters partition permutations polynomial post-condition power2 pre-condition prime numbers problem program segment programming language proof rule QuickSort random numbers randomized algorithm recursive algorithm recursive function result satisfied sequence shortest path solve sort space spanning tree specification statement steps strategy structured programming sub-problems termination Terms in Chapter true upper bound variables vertex vertices