e-books in Algorithms & Data Structures category
by Larry LIU Xinyu - Github , 2016
'Elementary Algorithms' is a free book about elementary algorithms and data structures. This book doesn't only focus on an imperative (or procedural) approach, but also includes purely functional algorithms and data structures.
by James Aspnes - Yale University , 2015
Topics include programming in C; data structures (arrays, stacks, queues, lists, trees, heaps, graphs); sorting and searching; storage allocation and management; data abstraction; programming style; testing and debugging; writing efficient programs.
by Chris Okasaki - Carnegie Mellon University , 1996
This book describes data structures from the point of view of functional languages. The author includes both classical data structures, such as red-black trees, and a host of new data structures developed exclusively for functional languages.
by Jurg Nievergelt, Klaus Hinrichs - Prentice Hall , 2011
Contents: Programming environments for motion, graphics, and geometry; Programming concepts - beyond notation; Objects, algorithms, programs; Complexity of problems and algorithms; Data structures; Interaction between algorithms and data structures.
by K. Mehlhorn, St. Näher - Cambridge University Press , 1999
The book treats the architecture, the implementation, and the use of the LEDA system. LEDA is a library of efficient data types and algorithms and a platform for combinatorial and geometric computing, written in C++ and freely available worldwide.
- Wikipedia , 2011
A data structure is a particular way of storing and organizing data in a computer so that it can be used efficiently. Contents of the book: Sequences; Dictionaries; Sets; Priority queues; Successors and neighbors; Integer and string searching.
by Solomon I. Khmelnik - MiC , 2013
This book describes various processors, designed for affine transformations of many-dimensional figures -- planar and spatial. Designed for students, engineers and developers, who intend to use the computer arithmetic of geometrical figures.
by K. Raghava Rao - Smashwords , 2013
This book provides a complete information to the modern study of computer algorithms. It presents many concepts in a considerable depth, so that it can be understand by all levels of readers. Each and every concept is explained by suitable examples.
by Pat Morin - AU Press , 2013
Offered as an introduction to the field of data structures and algorithms, the book covers the implementation and analysis of data structures for sequences (lists), queues, priority queues, unordered dictionaries, ordered dictionaries, and graphs.
by Brad Miller, David Ranum - Franklin, Beedle & Associates , 2011
This textbook is designed as a text for a first course on data structures and algorithms, taught as the second course in the computer science curriculum. We cover abstract data types and data structures, writing algorithms, and solving problems.
by Robert Sedgewick, Kevin Wayne - Addison-Wesley Professional , 2011
This textbook surveys the most important algorithms and data structures in use today. Applications to science, engineering, and industry are a key feature of the text. We motivate each algorithm by examining its impact on specific applications.
by Clifford A. Shaffer - Dover Publications , 2012
A comprehensive treatment focusing on the creation of efficient data structures and algorithms, explaining how to select the data structure best suited to specific problems. It uses Java programming language and is suitable for second-year courses.
by Clifford A. Shaffer - Dover Publications , 2012
A comprehensive treatment focusing on efficient data structures and algorithms, this text explains how to select or design the data structure best suited to specific problems. It uses C++ programming language and is suitable for second-year courses.
by Wolfgang Merkle - ESSLLI , 2001
The first part of the course gives an introduction to randomized algorithms and to standard techniques for their derandomization. The second part presents applications of the probabilistic method to the construction of logical models.
by Nashat Mansour - InTech , 2011
This book demonstrates the applicability of search algorithms for the purpose of developing solutions to problems that arise in a variety of domains. It is targeted to a wide group of readers: researchers, graduate students, and practitioners.
by K. Mehlhorn, P. Sanders - Springer , 2008
This book is a concise introduction addressed to students and professionals familiar with programming and basic mathematical language. Individual chapters cover arrays and linked lists, hash tables and associative arrays, sorting and selection, etc.
by Jeffrey Scott Vitter - Now Publishers , 2008
The book describes several useful paradigms for the design and implementation of efficient EM algorithms and data structures. The problem domains considered include sorting, permuting, FFT, scientific computing, computational geometry, graphs, etc.
by Guy Blelloch - The MIT Press , 1990
Vector Models for Data-Parallel Computing describes a model of parallelism that extends and formalizes the Data-Parallel model on which the Connection Machine and other supercomputers are based. It presents many algorithms based on the model.
by D. P. Williamson, D. B. Shmoys - Cambridge University Press , 2010
This book shows how to design approximation algorithms: efficient algorithms that find provably near-optimal solutions. It is organized around techniques for designing approximation algorithms, including greedy and local search algorithms.
by Donald E. Knuth - Addison-Wesley Professional , 2006
This work on the analysis of algorithms has long been recognized as the definitive description of classical computer science, arguably the most influential work ever written on computer programming. Volume 4 covers Combinatorial Algorithms.
by Clifford A. Shaffer - Virginia Tech , 2010
A comprehensive treatment of fundamental data structures and algorithm analysis with a focus on how to create efficient data structures and algorithms. Aims to help the reader gain an understanding of how to select or design the best data structure.
by Sean Luke , 2009
This is an open set of lecture notes on metaheuristics algorithms, intended for undergraduate students, practitioners, programmers, and other non-experts. It was developed as a series of lecture notes for an undergraduate course.
by Andrew Tridgell - samba.org , 1999
This thesis presents efficient algorithms for parallel sorting and remote data update. The sorting algorithms approach the problem by concentrating first on efficient but incorrect algorithms followed by a cleanup phase that completes the sort.
by Luc Devroye - Birkhauser , 1986
In these lecture notes, we attempt to explain the connection between the expected time of various bucket algorithms and the distribution of the data. The results are illustrated on standard searching, sorting and selection problems.
by Richard P. Brent, Paul Zimmermann - LORIA , 2009
This book collects in the same document all state-of-the-art algorithms in multiple precision arithmetic (integers, integers modulo n, floating-point numbers). The book will be useful for graduate students in computer science and mathematics.
by John Morris , 1998
The text focuses on data structures and algorithms for manipulating them. Data structures for storing information in tables, lists, trees, queues and stacks are covered. Some basic graph and discrete transform algorithms are also discussed.
by Silvano Martello, Paolo Toth - John Wiley & Sons , 1990
The book on exact and approximate algorithms for a number of important problems in the field of integer linear programming, which the authors refer to as 'knapsack'. Includes knapsack problems such as binary, bounded, unbounded or binary multiple.
by Wojciech Szpankowski - Wiley-Interscience , 2001
A book on a topic that has witnessed a surge of interest over the last decade, owing in part to several novel applications in data compression and computational molecular biology. It describes methods employed in average case analysis of algorithms.
by Niklaus Wirth - Prentice Hall , 1985
The book treats practically important algorithms and data structures. It starts with a chapter on data structure, then it treats sorting algorithms, concentrates on several examples of recursion, and deals with dynamic data structures.
by Anil K. Jain, Richard C. Dubes - Prentice Hall , 1988
The book is useful for scientists who gather data and seek tools for analyzing and interpreting data. It will be a reference for scientists in a variety of disciplines and can serve as a textbook for a graduate course in exploratory data analysis.
by Wassim Jaziri - InTech , 2008
Tabu search is a mathematical optimization method. The goal of the book is to report original researches on algorithms and applications of Tabu Search to real-world problems as well as recent improvements and extensions on its concepts and algorithms.
by Ian Craw, John Pulham - University of Aberdeen , 1999
This course studies computer algorithms, their construction, validation and effectiveness. A number of topics will be covered: a general introduction to the subject, the problem of sorting data sets into order, the theory of formal grammars, etc.
by Witold Bednorz - InTech , 2008
Each chapter comprises a separate study on some optimization problem giving both an introductory look into the theory the problem comes from and some new developments invented by authors. Usually some elementary knowledge is assumed.
by Granville Barnett, Luca Del Tongo - DotNetSlackers , 2008
The book provides implementations of common and uncommon algorithms in pseudocode which is language independent and provides for easy porting to most programming languages. We assume that the reader is familiar with the object oriented concepts.
by J. E. Cremona - Cambridge University Press , 1992
The author describes the construction of modular elliptic curves giving an algorithm for their computation. Then algorithms for the arithmetic of elliptic curves are presented. Finally, the results of the implementations of the algorithms are given.
by Jeff Erickson - University of Illinois at Urbana-Champaign , 2009
These are lecture notes, homework questions, and exam questions from algorithms courses the author taught at the University of Illinois. It is assumed that the reader has mastered the material covered in the first 2 years of a typical CS curriculum.
by Macneil Shonle, Matthew Wilson, Martin Krischik - Wikibooks , 2006
An accessible introduction into the design and analysis of efficient algorithms. It explains only the most basic techniques, and gives intuition for and an introduction to the rigorous mathematical methods needed to describe and analyze them.
by Jianer Chen , 1996
The author concentrates on four themes in computational geometry: the construction of convex hulls, proximity problems, searching problems and intersection problems. Solving manufacturing problems requires application of fast-algorithm techniques.
by Leonard Soicher, Franco Vivaldi , 2004
This text is a course in mathematical algorithms, intended for second year mathematics students. It introduces the algorithms for computing with integers, polynomials and vector spaces. The course requires no computing experience.
by Steven M. LaValle - Cambridge University Press , 2006
Written for computer scientists and engineers with interests in artificial intelligence, robotics, or control theory, this book tightly integrates a vast body of literature from several fields into a coherent source for reference in applications.
by Ian Parberry, William Gasarch - Prentice Hall , 2002
A collection of problems on the design, analysis, and verification of algorithms for practicing programmers who wish to hone and expand their skills, as a supplementary text for students, and as a self-study text for graduate students.
by David M. Mount - University of Maryland , 2003
The focus is on how to design good algorithms, and how to analyze their efficiency. The text covers some preliminary material, optimization algorithms, graph algorithms, minimum spanning trees, shortest paths, network flows and computational geometry.
by Herbert Edelsbrunner - Duke University , 2008
The main topics to be covered in this course are: Design Techniques; Searching; Prioritizing; Graph Algorithms; Topological Algorithms; Geometric Algorithms; NP-completeness. The emphasis will be on algorithm design and on algorithm analysis.
by Marko Petkovsek, Herbert S. Wilf, Doron Zeilberger - AK Peters, Ltd. , 1996
The book shows how some computer algorithms can simplify complex summations and if there is no such simplification they will prove this to be the case. The authors present the underlying mathematical theory, and the principle theorems and proofs.
by Albert Nijenhuis, Herbert S. Wilf - Academic Press Inc , 1978
This is a collection of mathematical algorithms with many new and interesting examples in this second edition. The authors tried to place in the reader's hands a kit of building blocks with which the reader can construct more elaborate structures.
by Herbert S. Wilf - AK Peters, Ltd. , 1994
An introductory textbook on the design and analysis of algorithms. Recursive algorithms are illustrated by Quicksort, FFT, and fast matrix multiplications. Algorithms in number theory are discussed with some applications to public key encryption.