UNIX: The Complete Reference, Second Edition by Kenneth, H. Rosenet al. ,jntu e-book free download

E-Book Details:

Title:	UNIX: The Complete Reference, Second Edition by Kenneth, H. Rosenet al.
Publisher:	McGraw-Hill Osborne
Author:	Kenneth, H. Rosenet al.
Edition:	Second Edition
EditionNumber:	2
ISBN:	0072263369
EAN:	9780072263367
No. of Pages:	912

Table of Contents:

The Definitive UNIX Resource--Fully Updated Get cutting-edge coverage of the newest releases of UNIX--including Solaris 10, all Linux distributions, HP-UX, AIX, and FreeBSD--from this thoroughly revised, one-stop resource for users at all experience levels. Written by UNIX experts with many years of experience starting with Bell Laboratories, UNIX: The Complete Reference, Second Edition provides step-by-step instructions on how to use UNIX and take advantage of its powerful tools and utilities.

                         Get up-and-running on UNIX quickly, use the command shell and desktop, and access the Internet and e-mail. You'll also learn to administer systems and networks, develop applications, and secure your UNIX environment. Up-to-date chapters on UNIX desktops, Samba, Python, Java Apache, and UNIX Web development are included.* Install, configure, and maintain UNIX on your PC or workstation* Work with files, directories, commands, and the UNIX shell* Create and modify text files using powerful text editors* Use UNIX desktops, including GNOME, CDE, and KDE, as an end user or system administrator* Use and manage e-mail, TCP/IP networking, and Internet services* Protect and maintain the security of your UNIX system and network* Share devices, printers, and files between Windows and UNIX systems* Use powerful UNIX tools, including awk, sed, and grep* Develop your own shell, Python, and Perl scripts, and Java, C, and C programs under UNIX*

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Probability by Charles M. Grinstead, jntu ebook free download

E-Book Details:

Title:	Introduction to Probability by Charles M. Grinstead & J. Laurie Snell
Publisher:	American Mathematical Society 1997
Author:	Charles M. Grinstead & J. Laurie Snell
Edition:	second Revised Edition
Edition Number:	2
ISBN:	0821807498
EAN:	9780821807491
No. of Pages:	520

Description:

This is a textbook designed for an introductory probability course at the university level for sophomores, juniors, and seniors in mathematics, physical and social sciences, engineering, and computer science. It presents a thorough treatment of ideas and techniques necessary for a firm understanding of the subject.

Table of Contents:

1 Discrete Probability Distributions 1

1.1 Simulation of Discrete Probabilities . . . . . . . . . . . . . . . . . . . 1

1.2 Discrete Probability Distributions . . . . . . . . . . . . . . . . . . . . 18

2 Continuous Probability Densities 41

2.1 Simulation of Continuous Probabilities . . . . . . . . . . . . . . . . . 41

2.2 Continuous Density Functions . . . . . . . . . . . . . . . . . . . . . . 55

3 Combinatorics 75

3.1 Permutations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75

3.2 Combinations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92

3.3 Card Shuffling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120

4 Conditional Probability 133

4.1 Discrete Conditional Probability . . . . . . . . . . . . . . . . . . . . 133

4.2 Continuous Conditional Probability . . . . . . . . . . . . . . . . . . . 162

4.3 Paradoxes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 175

5 Distributions and Densities 183

5.1 Important Distributions . . . . . . . . . . . . . . . . . . . . . . . . . 183

5.2 Important Densities . . . . . . . . . . . . . . . . . . . . . . . . . . . 205

6 Expected Value and Variance 225

6.1 Expected Value . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 225

6.2 Variance of Discrete Random Variables . . . . . . . . . . . . . . . . . 257

6.3 Continuous Random Variables . . . . . . . . . . . . . . . . . . . . . . 268

7 Sums of Random Variables 285

7.1 Sums of Discrete Random Variables . . . . . . . . . . . . . . . . . . 285

7.2 Sums of Continuous Random Variables . . . . . . . . . . . . . . . . . 291

8 Law of Large Numbers 305

8.1 Discrete Random Variables . . . . . . . . . . . . . . . . . . . . . . . 305

8.2 Continuous Random Variables . . . . . . . . . . . . . . . . . . . . . . 316

9 Central Limit Theorem 325

9.1 Bernoulli Trials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 325

9.2 Discrete Independent Trials . . . . . . . . . . . . . . . . . . . . . . . 340

9.3 Continuous Independent Trials . . . . . . . . . . . . . . . . . . . . . 356

10 Generating Functions 365

10.1 Discrete Distributions . . . . . . . . . . . . . . . . . . . . . . . . . . 365

10.2 Branching Processes . . . . . . . . . . . . . . . . . . . . . . . . . . . 376

10.3 Continuous Densities . . . . . . . . . . . . . . . . . . . . . . . . . . . 393

11 Markov Chains 405

11.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 405

11.2 Absorbing Markov Chains . . . . . . . . . . . . . . . . . . . . . . . . 416

11.3 Ergodic Markov Chains . . . . . . . . . . . . . . . . . . . . . . . . . 433

11.4 Fundamental Limit Theorem . . . . . . . . . . . . . . . . . . . . . . 447

11.5 Mean First Passage Time . . . . . . . . . . . . . . . . . . . . . . . . 452

12 Random Walks 471

12.1 Random Walks in Euclidean Space . . . . . . . . . . . . . . . . . . . 471

12.2 Gambler’s Ruin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 486

12.3 Arc Sine Laws . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 493

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DS [ Principles of Data Structures Using C and C++ ] by Vinu V. Das, jntu e-book free download

E-Book Details:

Title:	Principles of Data Structures Using C and C++ by Vinu V Das
Publisher:	New Age Publications 2008
Author:	Vinu V Das
Edition:	1st Edition
EditionNumber:	1
ISBN:	8122418589
EAN:	9780075032309
No. of Pages:	374

Table of Contents:

About the Book Principles of DATA STRUCTURES using C and C++ covers all the fundamental topics to give a better understanding about the subject. The study of data structures is essential to every one who comes across with computer science. This book is written in accordance with the revised syllabus for B.Tech./B.E. (both Computer Science and Electronics branches) and MCA. students of Kerala University, MG University, Calicut University, CUSAT Cochin (deemed) University. NIT Calicut (deemed) University, Anna University, UP Technical University, Amritha Viswa (deemed) Vidyapeeth, Karunya (deemed) University and Rajasthan Vidyapeeth (deemed) University. Moreover, this book covers almost all the topics of the other Indian and International Universities where this subject is there in their undergraduate and graduate programs. All effort is made to discuss the topics in the simplest possible way without loosing its qualities.Table of ContentsProgramming Methodologies Memory Management The Stack The Queue Linked List Sorting Techniques Searching and Hashing The Trees GraphsAbout the BookProf. Vinu V. Das received his MTech, BTech and BS degree (all in Computer Science) from Dr. MGR University, India: JRN Rajasthan Vidyapeeth University India, and AIUM & T, USA respectively and also holds MLM (Labour Management) degree from Madurai Kamaraj University, India. He is also a holder RHCE (Red Hat Certified Engineer) and Diploma in CMM (Capability Maturity Model) for software. At present, he is actively participating in different research works related to Analysis and Design of Network Secrity related Protocols and Algorithms. He is member of IEEE, ISTE, IETE and IAENG. Other than this book, he is the author of two books, ``Principles of Data Structures Using C and C++``, ``Compiler Design Using FLEX and YACC``, and having number of papers to his credit, which has been published in International Conferences/Journals including IEEE, ACM, IET and Springer etc.Currently he is Researcher and Assistant Professor with the Department of Computer Science and Engineering, SAINTGITS College of Engineering, Kottayam, Kerala, India. His research interests include Network Security, Algorithms, Cryptography, Compilers, Requirement Engineering, and Structuring of Image Processing Algorithms. Contents: Programming Methodologies Memory Management The Stack The Queue Linked List Sorting Techniques Searching and Hashing The Trees Graphs

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Data Structures and Algorithm Analysis [ ds ] in C, by Mark A. Weiss jntu e-book free download

E-Book Details:

Title:	Data Structures and Algorithm Analysis in C,  by Mark A. Weiss
Publisher:	Addison-Wesley
Author:	Mark A. Weiss
Edition:	Paperback 3rd Edition
Edition Number:	3
ISBN:	0201498405
EAN:	9780201498400
No. of Pages:	600

Description:

Mark Allen Weiss' successful book provides a modern approach to algorithms and data structures using the C programming language. The book's conceptual presentation focuses on ADTs and the analysis of algorithms for efficiency, with a particular concentration on performance and running time. The second edition contains a new chapter that examines advanced data structures such as red black trees, top down splay trees, treaps, k-d trees, and pairing heaps among others. All code examples now conform to ANSI C and coverage of the formal proofs underpinning several key data structures has been strengthened.

Author Bios:

Mark Allen Weiss is a Professor in the School of Computer Science at Florida International University. He received his Ph.D. in Computer Science from Princeton University where he studied under Robert Sedgewick. Dr.Weiss has received FIU's Excellence in Research Award, as well as the Teaching Incentive Program Award, which was established by the Florida Legislature to recognize teaching excellence. Mark Allen Weiss is on the Advanced Placement Computer Science Development Committee. He is the successful author of Algorithms, Data Structures, and Problem Solving with C++ and the series Data Structures and Algorithm Analysis in Pascal, Ada, C, and C++, with Addison-Wesley.

Backcover Copy:

In this second edition of his best-selling book, Data Structures and Algorithm Analysis in C, Mark Allen Weiss, continues to refine and enhance his innovative approach to algorithms and data structures. Using a C implementation, he highlights conceptual topics, focusing on ADTs and the analysis of algorithms for efficiency as well as performance and running time. Dr. Weiss also distinguishes Data Structures and Algorithm Analysis in C with the extensive use of figures and examples showing the successive stages of an algorithm, his engaging writing style, and a logical organization of topics.

Features:

• Includes a chapter on algorithm and design techniques that covers greedy algorithms, divide and conquer algorithms, dynamic programming, randomized algorithms, and backtracking
• Presents current topics and newer data structures such as Fibonacci heaps, skew heaps, binomial queues, skip lists, and splay trees
• Contains a chapter on amortized analysis that examines the advanced data structures presented earlier in the book
• Provides a new chapter on advanced data structures and their implementation covering red black trees, top down splay trees, treaps, k-d trees, pairing heaps, and more
• Incorporates new results on the average case analysis of heapsort

Table of Contents:

1. Introduction. 

·         What’s the Book About?

·         Mathematics Review.

·         Exponents.

·         Logarithms.

·         Series.

·         Modular Arithmetic.

·         The P word.

·         A Brief Introduction to Recursion.

2. Algorithm Analysis. 

·         Mathematical Background.

·         Model.

·         What to Analyze.

·         Running Time Calculations.

·         A Simple Example.

·         General Rules.

·         Solutions for the Maximum Subsequence Sum Problem.

·         Logarithms in the Running Time.

·         Checking Your Analysis.

·         A Grain of Salt.

3. Lists, Stacks, and Queues. 

·         Abstract Data Types (ADTs).

·         The List ADT.

·         Simple Array Implementation of Lists.

·         Linked Lists.

·         Programming Details.

·         Common Errors.

·         Doubly Linked Lists.

·         Circularly Linked Lists.

·         Examples.

·         Cursor Implementation of Linked Lists.

·         The Stack ADT.

·         Stack Model.

·         Implementation of Stacks.

·         Applications.

·         The Queue ADT.

·         Queue Model.

·         Array Implementation of Queues.

·         Applications of Queues.

4. Trees. 

·         Preliminaries.

·         Implementation of Trees.

·         Tree Traversals with an Application.

·         Binary Trees.

·         Implementation.

·         Expression Trees.

·         The Search Tree ADT—Binary Search Trees.

·         MakeEmpty.

·         Find.

·         FindMin and FindMax.

·         Insert.

·         Delete.

·         Average-Case Analysis.

·         AVL Trees.

·         Single Rotation.

·         Double Rotation.

·         Splay Trees.

·         A Simple Idea (That Does Not Work).

·         Splaying.

·         Tree Traversals (Revisited).

·         B-Trees.

5. Hashing. 

·         General Idea.

·         Hash Function.

·         Separate Chaining.

·         Open Addressing.

·         Linear Probing.

·         Quadratic Probing.

·         Double Hashing.

·         Rehashing.

·         Extendible Hashing.

6. Priority Queues (Heaps). 

·         Model.

·         Simple Implementations.

·         Binary Heaps.

·         Structure Property.

·         Heap Order Property.

·         Basic Heap Operations.

·         Other Heap Operations.

·         Applications of Priority Queues.

·         The Selection Problem.

·         Event Simulation.

·         d-Heaps.

·         Leftist Heaps.

·         Leftist Heap Property.

·         Leftist Heap Operations.

·         Skew Heaps.

·         Binomial Queues.

·         Binomial Queue Structure.

·         Binomial Queue Operations.

·         Implementations of Binomial Queues.
7. Sorting. 

·         Preliminaries.

·         Insertion Sort.

·         The Algorithm.

·         Analysis of Insertion Sort.

·         A Lower Bound for Simple Sorting Algorithms.

·         Shellsort.

·         Analysis of Insertion Sort.

·         Heapsort.

·         Analysis of Heapsort.

·         Mergesort.

·         Analysis of Mergesort.

·         Quicksort.

·         Picking the Pivot.

·         Partitioning Strategy.

·         Small Arrays.

·         Actual Quicksort Routines.

·         Analysis of Quicksort.

·         A Linear-Expected-Time Algorithm for Selection.

·         Sorting Large Structures.

·         A General Lower Bound for Sorting.

·         Decision Trees.

·         Bucket Sort.

·         External Sorting.

·         Why We Need New Algorithms.

·         Model for External Sorting.

·         The Simple Algorithm.

·         Multiway Merge.

·         Polyphase Merge.

·         Replacement Selection.

8. The Disjoint Set ADT. 

·         Equivalence Relations.

·         The Dynamic Equivalence Problem.

·         Basic Data Structure.

·         Smart Union Algorithms.

·         Path Compression.

·         Worst Case for Union-by-Rank and Path Compression.

·         Analysis of the Union/Find Algorithm.

·         An Application.

9. Graph Algorithms. 

·         Definitions.

·         Representation of Graphs.

·         Topological Sort.

·         Shortest-Path Algorithms.

·         Unweighted Shortest Paths.

·         Dijkstra’s Algorithm.

·         Graphs with Negative Edge Costs.

·         Acyclic Graphs.

·         All-Pairs Shortest Path.

·         Network Flow Problems.

·         A Simple Maximum-Flow Algorithm.

·         Minimum Spanning Tree.

·         Prim’s Algorithm.

·         Kruskal’s Algorithm.

·         Applications of Depth-First Search.

·         Undirected Graphs.

·         Biconnectivity.

·         Euler Circuits.

·         Directed Graphs.

·         Finding Strong Components.

·         Introduction to the NP-Completeness.

·         Easy vs. Hard.

·         The Class NP.

·         NP-Complete Problems.
10. Algorithm Design Techniques. 

·         Greedy Algorithms.

·         A Simple Scheduling Problem.

·         Huffman Codes.

·         Approximate Bin Packing.

·         Divide and Conquer.

·         Running Time of Divide and Conquer Algorithms.

·         Closest-Points Problem.

·         The Selection Problem.

·         Theoretical Improvements for Arithmetic Problems.

·         Dynamic Programming.

·         Using a Table Instead of Recursion.

·         Ordering Matrix Multiplications.

·         Optimal Binary Search Tree.

·         All-Pairs Shortest Path.

·         Randomized Algorithms.

·         Random Number Generators.

·         Skip Lists.

·         Primality Testing.

·         Backtracking Algorithms.

·         The Turnpike Reconstruction Problem.

·         Games.
11. Amortized Analysis. 

·         An Unrelated Puzzle.

·         Binomial Queues.

·         Skew Heaps.

·         Fibonacci Heaps.

·         Cutting Nodes in Leftist Heaps.

·         Lazy Merging for Binomial Queues.

·         The Fibonacci Heap Operations.

·         Proof of the Time Bound.

·         Splay Trees.
12. Advanced Data Structures and Implementation. 

·         Top-Down Splay Trees.

·         Red Black Trees.

·         Bottom-Up Insertion.

·         Top-Down Red Black Trees.

·         Top-Down Deletion.

·         Deterministic Skip Lists.

·         AA-Trees.

·         Treaps.

·         k-d Trees.

·         Pairing Heaps.

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