Fundamentals of Computer Algorithms (Record no. 40137)

MARC details
000 -LEADER
fixed length control field 09230nam a22001697a 4500
003 - CONTROL NUMBER IDENTIFIER
control field OSt
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9788173716126
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Horowitz, Ellis
245 ## - TITLE STATEMENT
Title Fundamentals of Computer Algorithms
250 ## - EDITION STATEMENT
Edition statement 2nd
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc New Delhi
Name of publisher, distributor, etc University Press
Date of publication, distribution, etc 2007
300 ## - PHYSICAL DESCRIPTION
Extent 773p.
500 ## - GENERAL NOTE
General note 1 INTRODUCTION<br/>1.1 WHAT IS AN ALGORITHM?<br/>1.2 ALGORITHM SPECIFICATION<br/> 1.2.1 Pseudocode Conventions<br/> 1.2.2 Recursive Algorithms<br/>1.3 PERFORMANCE ANALYSIS<br/> 1.3.1 Space Complexity<br/> 1.3.2 Time Complexity<br/> 1.3.3 Amortized Complexity<br/> 1.3.4 Asymptotic Notation (Ο, Ω, Θ)<br/> 1.3.5 Practical Complexities<br/> 1.3.6 Performance Measurement<br/>1.4 RANDOMIZED ALGORITHMS<br/> 1.4.1 Basics of Probability Theory<br/> 1.4.2 Randomized Algorithms: An Informal Description<br/> 1.4.3 Identifying the Repeated Element<br/> 1.4.4 Primality Testing<br/> 1.4.5 Advantages and Disadvantages<br/>1.5 REFERENCES AND READINGS<br/> <br/>2 ELEMENTARY DATA STRUCTURES<br/>2.1 STACKS AND QUEUES<br/>2.2 TREES<br/> 2.2.1 Terminology<br/> 2.2.2 Binary Trees<br/>2.3 DICTIONARIES<br/> 2.3.1 Binary Search Trees<br/>2.4 PRIORITY QUEUES<br/> 2.4.1 Heaps<br/> 2.4.2 Heap Sort<br/>2.5 SETS AND DISJOINT SET UNION<br/> 2.5.1 Introduction<br/> 2.5.2 Union and Find Operations<br/>2.6 GRAPHS<br/> 2.6.1 Introduction<br/> 2.6.2 Definitions<br/> 2.6.3 Graph Representations<br/>2.7 REFERENCES AND READINGS<br/> <br/>3. DIVIDE AND CONQUER<br/>3.1 GENERAL METHOD<br/>3.2 DEFECTIVE CHESSBOARD<br/>3.3 BINARY SEARCH<br/>3.4 FINDING THE MAXIMUM AND MINIMUM<br/>3.5 MERGE SORT<br/>3.6 QUICK SORT<br/> 3.6.1 Performance Measurement<br/> 3.6.2 Randomized Sorting Algorithms<br/>3.7 SELECTION<br/> 3.6.2 Evaluating Postfix Expressions<br/>3.7 Multiple Stacks and Queues<br/>3.7 Additional Exercises<br/> 3.7.1 A Worst-Case Optimal Algorithm<br/> 3.7.2 Implementation of Select2<br/>3.8 STRASSEN´S MATRIX MULTIPLICATION<br/>3.9 CONVEX HULL<br/> 3.9.1 Some Geometric Primitives<br/> 3.9.2 The QuickHullAlgorithm<br/> 3.9.3 Graham´s Scan<br/> 3.9.4 An Ο (n log n) Divide-and-Conquer Algorithm<br/>3.10 REFERENCES AND READINGS<br/>3.11 ADDITIONAL EXERCISES<br/> <br/>4 THE GREEDY METHOD<br/>4.1 THE GENERAL METHOD<br/>4.2 CONTAINER LOADING<br/>4.3 KNAPSACK PROBLEM<br/>4.4 TREE VERTEX SPLITTING<br/>4.5 JOB SEQUENCING WITH DEADLINES<br/>4.6 MINIMUM-COST SPANNING TREES<br/> 4.6.1 Prim´s Algorithm<br/> 4.6.2 Kruskal´s Algorithm<br/> 4.6.3 An Optimal Randomized Algorithm (∗)<br/>4.7 OPTIMAL STORAGE ON TAPES<br/>4.8 OPTIMAL MERGE PATTERNS<br/>4.9 SINGLE-SOURCE SHORTEST PATHS<br/>4.10 REFERENCES AND READINGS<br/>4.11 ADDITIONAL EXERCISES<br/> <br/>5 DYNAMIC PROGRAMMING<br/>5.1 THE GENERAL METHOD<br/>5.2 MULTISTAGE GRAPHS<br/>5.3 ALL-PAIRS SHORTEST PATHS<br/>5.4 SINGLE-SOURCE SHORTEST PATHS: GENERAL WEIGHTS<br/>5.5 OPTIMAL BINARY SEARCH TREES (∗)<br/>5.6 STRING EDITING<br/>5.7 0/1 KNAPSACK<br/>5.8 RELIABILITY DESIGN<br/>5.9 THE TRAVELING SALESPERSON PROBLEM<br/>5.10 FLOW SHOP SCHEDULING<br/>5.11 REFERENCES AND READINGS<br/>5.12 ADDITIONAL EXERCISES<br/> <br/>6 BASIC TRAVERSAL AND SEARCH TECHNIQUES<br/>6.1 TECHNIQUES FOR BINARY TREES<br/>6.2 TECHNIQUES FOR GRAPHS<br/> 6.2.1 Breadth First Search and Traversal<br/> 6.2.2 Depth First Search and Traversal<br/>6.3 CONNECTED COMPONENTS AND SPANNING TREES<br/>6.4 BICONNECTED COMPONENTS AND DFS<br/>6.5 REFERENCES AND READINGS CONTENTS<br/> <br/>7 BACKTRACKING<br/>7.1 THE GENERAL METHOD<br/>7.2 THE 8-QUEENS PROBLEM<br/>7.3 SUM OF SUBSETS<br/>7.4 GRAPH COLORING<br/>7.5 HAMILTONIAN CYCLES<br/>7.6 KNAPSACK PROBLEM<br/>7.7 REFERENCES AND READINGS<br/>7.8 ADDITIONAL EXERCISES<br/> <br/>8 BRANCH AND BOUND<br/>8.1 THE METHOD<br/> 8.1.1 Least Cost (LC) Search<br/> 8.1.2 The 15-puzzle: An Example<br/> 8.1.3 Control Abstractions for LC-Search<br/> 8.1.4 Bounding<br/> 8.1.5 FIFO Branch-and-Bound<br/> 8.1.6 LC Branch-and-Bound<br/>8.2 0/1 KNAPSACK PROBLEM<br/> 8.2.1 LC Branch-and-Bound Solution<br/> 8.2.2 FIFO Branch-and-Bound Solution<br/>8.3 TRAVELING SALESPERSON (∗)<br/>8.4 EFFICIENCY CONSIDERATIONS<br/>8.5 REFERENCES AND READINGS<br/> <br/>9 ALGEBRAIC PROBLEMS<br/>9.1 THE GENERAL METHOD<br/>9.2 EVALUATION AND INTERPOLATION<br/>9.3 THE FAST FOURIER TRANSFORM<br/> 9.3.1 An In-place Version of the FFT<br/> 9.3.2 Some Remaining Points<br/>9.4 MODULAR ARITHMETIC<br/>9.5 EVEN FASTER EVALUATION AND INTERPOLATION<br/>9.6 REFERENCES AND READINGS<br/> <br/>10 LOWER BOUND THEORY<br/>10.1 COMPARISON TREES<br/> 10.1.1 Ordered Searching<br/> 10.1.2 Sorting<br/> 10.1.3 Selection<br/>10.2 ORACLES AND ADVERSARY ARGUMENTS<br/> 10.2.1 Merging<br/> 10.2.2 Largest and Second Largest<br/> 10.2.3 State Space Method<br/> 10.2.4 Selection<br/>10.3 LOWER BOUNDS THROUGH REDUCTIONS<br/> 10.3.1 Finding the Convex Hull<br/> 10.3.2 Disjoint Sets Problem<br/> 10.3.3 On-line Median Finding<br/> 10.3.4 Multiplying Triangular Matrices<br/> 10.3.5 Inverting a Lower Triangular Matrix<br/> 10.3.6 Computing the Transitive Closure<br/>10.4 TECHNIQUES FOR ALGEBRAIC PROBLEMS (∗)<br/>10.5 REFERENCES AND READINGS<br/> <br/>11 NP-HARD AND NP-COMPLETE PROBLEMS<br/>11.1 BASIC CONCEPTS<br/> 11.1.1 Nondeterministic Algorithms<br/> 11.1.2 The Classes NP-hard and NP-complete<br/>11.2 COOK´S THEOREM (∗)<br/>11.3 NP-HARD GRAPH PROBLEMS<br/> 11.3.1 Clique Decision Problem (CDP)<br/> 11.3.2 Node Cover Decision Problem (NCDP)<br/> 11.3.3 Chromatic Number Decision Problem (CNDP)<br/> 11.3.4 Directed Hamiltonian Cycle (DHC) (∗)<br/> 11.3.5 Traveling Salesperson Decision Problem (TSP)<br/> 11.3.6 AND/OR Graph Decision Problem (AOG)<br/>11.4 NP-HARD SCHEDULING PROBLEMS<br/> 11.4.1 Scheduling Identical Processors<br/> 11.4.2 Flow Shop Scheduling<br/> 11.4.3 Job Shop Scheduling<br/>11.5 NP-HARD CODE GENERATION PROBLEMS<br/> 11.5.1 Code Generation with Common Subexpressions<br/> 11.5.2 Implementing Parallel Assignment Instructions<br/>11.6 SOME SIMPLIFIED NP-HARD PROBLEMS<br/>11.7 REFERENCES AND READINGS<br/>11.8 ADDITIONAL EXERCISES<br/> <br/>12 APPROXIMATION ALGORITHMS<br/>12.1 INTRODUCTION.<br/>12.2 ABSOLUTE APPROXIMATIONS.<br/> 12.2.1 Planar Graph Coloring<br/> 12.2.2 Maximum Programs Stored Problem<br/> 12.2.3 NP-hard Absolute Approximations<br/>12.3 ∊-APPROXIMATIONS<br/> 12.3.1 Scheduling Independent Tasks<br/> 12.3.2 Bin Packing<br/> 12.3.3 NP-hard ∊-approximation Problems<br/>12.4 POLYNOMIAL TIME APPROXIMATION SCHEMES<br/> 12.4.1 Scheduling Independent Tasks<br/> 12.4.2 0/1 Knapsack<br/>12.5 FULLY POLYNOMIAL TIME APPROXIMATION SCHEMES<br/> 12.5.1 Rounding<br/> 12.5.2 Interval Partitioning<br/> 12.5.3 Separation<br/>12.6 PROBABILISTICALLY GOOD ALGORITHMS (∗)<br/>12.7 REFERENCES AND READINGS<br/>12.8 ADDITIONAL EXERCISES<br/> <br/>13 PRAM ALGORITHMS<br/>13.1 INTRODUCTION<br/>13.2 COMPUTATIONAL MODEL<br/>13.3 FUNDAMENTAL TECHNIQUES AND ALGORITHMS<br/> 13.3.1 Prefix Computation<br/> 13.3.2 List Ranking<br/>13.4 SELECTION<br/> 13.4.1 Maximal Selection with n2 Processors<br/> 13.4.2 Finding the Maximum Using n Processors<br/> 13.4.3 Maximal Selection Among Integers<br/> 13.4.4 General Selection Using n2 Processors<br/> 13.4.5 A Work-Optimal Randomized Algorithm (∗)<br/>13.5 MERGING<br/> 13.5.1 A Logarithmic Time Algorithm<br/> 13.5.2 Odd-Even Merge<br/> 13.5.3 A Work-Optimal Algorithm<br/> 13.5.4 An O (log log m)-Time Algorithm<br/>13.6 SORTING<br/> 13.6.1 Odd-Even Merge Sort<br/> 13.6.2 An Alternative Randomized Algorithm<br/> 13.6.3 Preparata´s Algorithm<br/> 13.6.4 Reischuk´s Randomized Algorithm (∗)<br/>13.7 GRAPH PROBLEMS<br/> 13.7.1 An Alternative Algorithm for Transitive Closure<br/> 13.7.2 All-Pairs Shortest Paths<br/>13.8 COMPUTING THE CONVEX HULL<br/>13.9 LOWER BOUNDS<br/> 13.9.1 A lower bound on average-case sorting<br/> 13.9.2 Finding the maximum<br/>13.10REFERENCES AND READINGS<br/>13.11ADDITIONAL EXERCISES<br/> <br/>14 MESH ALGORITHMS<br/>14.1 COMPUTATIONAL MODEL<br/>14.2 PACKET ROUTING<br/> 14.2.1 Packet Routing on a Linear Array<br/> 14.2.2 A Greedy Algorithm for PPR on a Mesh<br/> 14.2.3 A Randomized Algorithm with Small Queues<br/>14.3 FUNDAMENTAL ALGORITHMS<br/> 14.3.1 Broadcasting<br/> 14.3.2 Prefix Computation<br/> 14.3.3 Data Concentration<br/> 14.3.4 Sparse Enumeration Sort<br/>14.4 SELECTION<br/> 14.4.1 A Randomized Algorithm for n = p (∗)<br/> 14.4.2 Randomized Selection for n > p (∗)<br/> 14.4.3 A Deterministic Algorithm For n > p<br/>14.5 MERGING<br/> 14.5.1 Rank Merge on a Linear Array<br/> 14.5.2 Odd-Even Merge on a Linear Array<br/> 14.5.3 Odd-Even Merge on a Mesh<br/>14.6 SORTING<br/> 14.6.1 Sorting on a Linear Array<br/> 14.6.2 Sorting on a Mesh<br/>14.7 GRAPH PROBLEMS<br/> 14.7.1 An n × n Mesh Algorithm for Transitive Closure<br/> 14.7.2 All-Pairs Shortest Paths<br/>14.8 COMPUTING THE CONVEX HULL<br/>14.9 REFERENCES AND READINGS<br/>14.10 ADDITIONAL EXERCISES<br/> <br/>15 HYPERCUBE ALGORITHMS<br/>15.1 COMPUTATIONAL MODEL<br/> 15.1.1 The Hypercube<br/> 15.1.2 The Butterfly Network<br/> 15.1.3 Embedding of Other Networks<br/>15.2 PPR ROUTING<br/> 15.2.1 A Greedy Algorithm<br/> 15.2.2 A Randomized Algorithm<br/>15.3 FUNDAMENTAL ALGORITHMS<br/> 15.3.1 Broadcasting<br/> 15.3.2 Prefix Computation<br/> 15.3.3 Data Concentration<br/> 15.3.4 Sparse Enumeration Sort<br/>15.4 SELECTION<br/> 1.5.4.1 A Randomized Algorithm for n = p (∗)<br/> 15.4.2 Randomized Selection for n > p (∗)<br/> 15.4.3 A Deterministic Algorithm for n > p<br/>15.5 MERGING<br/> 15.5.1 Odd-Even Merge<br/> 15.5.2 Bitonic Merge<br/>15.6 SORTING<br/> 15.6.1 Odd-Even Merge Sort<br/> 15.6.2 Bitonic Sort<br/>15.7 GRAPH PROBLEMS<br/>15.8 COMPUTING THE CONVEX HULL<br/>15.9 REFERENCES AND READINGS<br/>15.10 ADDITIONAL EXERCISES
856 ## - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://books.google.co.in/books?id=qzoqLM8899MC&printsec=frontcover&dq=fundamentals+of+computer+algorithms&hl=en&sa=X&ved=0ahUKEwjvksv--bLgAhUGFHIKHR8HCJIQ6AEIKDAA#v=onepage&q=fundamentals%20of%20computer%20algorithms&f=false">https://books.google.co.in/books?id=qzoqLM8899MC&printsec=frontcover&dq=fundamentals+of+computer+algorithms&hl=en&sa=X&ved=0ahUKEwjvksv--bLgAhUGFHIKHR8HCJIQ6AEIKDAA#v=onepage&q=fundamentals%20of%20computer%20algorithms&f=false</a>
901 ## - LOCAL DATA ELEMENT A, LDA (RLIN)
Acc. No. 27937
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Koha item type Books
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Collection code Home library Current library Shelving location Date acquired Source of acquisition Cost, normal purchase price Inventory number Total Checkouts Full call number Barcode Date last seen Uniform Resource Identifier Price effective from Koha item type Date last borrowed
    Dewey Decimal Classification   Not For Loan Reference Amity Central Library Amity Central Library AIIT 24/07/2018 SBA 995.00 SBA / 12220 19/06/2018   005.1 HOR-F 27937 08/03/2021 https://epgp.inflibnet.ac.in/view_f.php?category=1064 24/07/2018 Reference Book  
    Dewey Decimal Classification       Amity Central Library Amity Central Library ASET M.Tech CSE 24/07/2018 SBA 995.00 SBA / 12220 19/06/2018 8 005.1 HOR-F 27938 21/05/2024 https://epgp.inflibnet.ac.in/view_f.php?category=1064 24/07/2018 Books 13/05/2024
    Dewey Decimal Classification       Amity Central Library Amity Central Library ASET M.Tech CSE 24/07/2018 SBA 995.00 SBA / 12220 19/06/2018 7 005.1 HOR-F 27939 11/09/2024 https://epgp.inflibnet.ac.in/view_f.php?category=1064 24/07/2018 Books 28/08/2024
Web Counter

Powered by Koha