Download or read book Time Complexity Analysis written by Ue Kiao and published by . This book was released on 2021-08-29 with total page 163 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book "Time Complexity Analysis" introduces you to the basics of Time Complexity notations, meaning of the Complexity values and How to analyze various Algorithmic problems. This book includes Time and Space Complexity cheat sheets at the end as a bonus resource. We have tackled several significant problems and demonstrated the approach to analyze them and arrived at the Time and Space Complexity of the problems and Algorithms. This is a MUST-READ book for all Computer Science students and Programmers. Do not miss this opportunity. You will get a better idea to judge which approach will work better and will be able to make better judgements in your development work. See the "Table of content" to get the list of exciting topics you will learn about. Some of the key points you will understand: Random Access Memory does not take O(1) time. It is complicated and in general, has a Time Complexity of O(√N). Multiplication takes O(N^2) time, but the most optimal Algorithm (developed in 2019) takes O(N logN) time which is believed to be the theoretical limit. As per Time Complexity, finding the largest element and the i-th largest element takes the same order of time. It is recommended that you go through this book twice. First time, you may skip the minute details that you may not understand at first go and get the overview. In the second reading, you will get all the ideas, and this will strengthen your insights. In 1950s, Computing was not a Science. It was a collective effort by several Computer Scientists such as Robert Tarjan and Philippe Flajolet who analyzed several computational problems to demonstrate that Computation Problems are equally complicated as Physics and Mathematics Problems. The ideas captured in this book include some of these analyses which glorified Computer Science and made it a Scientific field. Book: Time Complexity Analysis Authors: Aditya Chatterjee; Ue Kiao, PhD. Contributors (7): Vansh Pratap Singh, Shreya Shah, Vikram Shishupalsingh Bais, Mallika Dey, Siddhant Rao, Shweta Bhardwaj, K. Sai Drishya. Table of content: 1. Introduction to Time and Space Complexity (+ different notations) 2. How to calculate Time Complexity? 3. Meaning of different Time Complexity 4. Brief Background on NP and P 5. Does O(1) time exist?: Cost of accessing Memory 6. Time Complexity of Basic Arithmetic Operations 6.1. Bitwise operations 6.2. Addition 6.3. Subtraction 6.4. Multiplication 6.5. Division 7. Analysis of Array 8. Analysis of Dynamic Array 9. Find largest element 10. Find Second largest element 11. Find i-th largest element 12. Time Complexity Bound for comparison-based sorting 12.1. Analysis of Selection Sort 12.2. Analysis of Insertion Sort 12.3. Analysis of Bubble Sort 12.4. Analysis of Quick Sort 13. Bound for non-comparison-based sorting 13.1. Analysis of Counting Sort 13.2. Analysis of Bucket Sort 14. Analysis of Linked List 15. Analysis of Hash functions 16. Analysis of Binary Search 17. Time and Space Complexity Cheat Sheets There is no other book that cover these topics. Many students have several misconceptions which are resolved with the book. Read this book and level up.
Download or read book Computational Complexity written by Sanjeev Arora and published by Cambridge University Press. This book was released on 2009-04-20 with total page 609 pages. Available in PDF, EPUB and Kindle. Book excerpt: New and classical results in computational complexity, including interactive proofs, PCP, derandomization, and quantum computation. Ideal for graduate students.
Download or read book A Logical Approach to Discrete Math written by David Gries and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 517 pages. Available in PDF, EPUB and Kindle. Book excerpt: Here, the authors strive to change the way logic and discrete math are taught in computer science and mathematics: while many books treat logic simply as another topic of study, this one is unique in its willingness to go one step further. The book traets logic as a basic tool which may be applied in essentially every other area.
Download or read book Data Structures Algorithms in Swift Fourth Edition written by raywenderlich Tutorial Team and published by . This book was released on 2021-09-15 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn Data Structures & Algorithms in Swift!Data structures and algorithms form the basis of computer programming and are the starting point for anyone looking to become a software engineer. Choosing the proper data structure and algorithm involves understanding the many details and trade-offs of using them, which can be time-consuming to learn - and confusing.This is where this book, Data Structures & Algorithms in Swift, comes to the rescue! In this book, you'll learn the nuts and bolts of how fundamental data structures and algorithms work by using easy-to-follow tutorials loaded with illustrations; you'll also learn by working in Swift playground code.Who This Book Is ForThis book is for developers who know the basics of Swift syntax and want a better theoretical understanding of what data structures and algorithms are to build more complex programs or ace a whiteboard interview.Topics Covered in Data Structures & Algorithms in Swift*Basic data structures and algorithms, including stacks, queues and linked lists. *How protocols can be used to generalize algorithms. *How to leverage the algorithms of the Swift standard library with your own data structures. *Trees, tries and graphs. *Building algorithms on top of other primitives. *A complete spectrum of sorting algorithms from simple to advanced. *How to think about algorithmic complexity. *Finding shortest paths, traversals, subgraphs and much more.After reading this book, you'll have a solid foundation on data structures and algorithms and be ready to solve more complex problems in your apps elegantly.
Download or read book Applied Asymptotic Analysis written by Peter David Miller and published by American Mathematical Soc.. This book was released on 2006 with total page 488 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a survey of asymptotic methods set in the current applied research context of wave propagation. It stresses rigorous analysis in addition to formal manipulations. Asymptotic expansions developed in the text are justified rigorously, and students are shown how to obtain solid error estimates for asymptotic formulae. The book relates examples and exercises to subjects of current research interest, such as the problem of locating the zeros of Taylor polynomials of entirenonvanishing functions and the problem of counting integer lattice points in subsets of the plane with various geometrical properties of the boundary. The book is intended for a beginning graduate course on asymptotic analysis in applied mathematics and is aimed at students of pure and appliedmathematics as well as science and engineering. The basic prerequisite is a background in differential equations, linear algebra, advanced calculus, and complex variables at the level of introductory undergraduate courses on these subjects. The book is ideally suited to the needs of a graduate student who, on the one hand, wants to learn basic applied mathematics, and on the other, wants to understand what is needed to make the various arguments rigorous. Down here in the Village, this is knownas the Courant point of view!! --Percy Deift, Courant Institute, New York Peter D. Miller is an associate professor of mathematics at the University of Michigan at Ann Arbor. He earned a Ph.D. in Applied Mathematics from the University of Arizona and has held positions at the Australian NationalUniversity (Canberra) and Monash University (Melbourne). His current research interests lie in singular limits for integrable systems.
Download or read book A Guide to Algorithm Design written by Anne Benoit and published by CRC Press. This book was released on 2013-08-27 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presenting a complementary perspective to standard books on algorithms, A Guide to Algorithm Design: Paradigms, Methods, and Complexity Analysis provides a roadmap for readers to determine the difficulty of an algorithmic problem by finding an optimal solution or proving complexity results. It gives a practical treatment of algorithmic complexity and guides readers in solving algorithmic problems. Divided into three parts, the book offers a comprehensive set of problems with solutions as well as in-depth case studies that demonstrate how to assess the complexity of a new problem. Part I helps readers understand the main design principles and design efficient algorithms. Part II covers polynomial reductions from NP-complete problems and approaches that go beyond NP-completeness. Part III supplies readers with tools and techniques to evaluate problem complexity, including how to determine which instances are polynomial and which are NP-hard. Drawing on the authors’ classroom-tested material, this text takes readers step by step through the concepts and methods for analyzing algorithmic complexity. Through many problems and detailed examples, readers can investigate polynomial-time algorithms and NP-completeness and beyond.
Download or read book The Concrete Tetrahedron written by Manuel Kauers and published by Springer Science & Business Media. This book was released on 2011-01-15 with total page 209 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book treats four mathematical concepts which play a fundamental role in many different areas of mathematics: symbolic sums, recurrence (difference) equations, generating functions, and asymptotic estimates. Their key features, in isolation or in combination, their mastery by paper and pencil or by computer programs, and their applications to problems in pure mathematics or to "real world problems" (e.g. the analysis of algorithms) are studied. The book is intended as an algorithmic supplement to the bestselling "Concrete Mathematics" by Graham, Knuth and Patashnik.
Download or read book Beyond the Worst Case Analysis of Algorithms written by Tim Roughgarden and published by Cambridge University Press. This book was released on 2021-01-14 with total page 705 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduces exciting new methods for assessing algorithms for problems ranging from clustering to linear programming to neural networks.
Download or read book Purely Functional Data Structures written by Chris Okasaki and published by Cambridge University Press. This book was released on 1999-06-13 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes data structures and data structure design techniques for functional languages.
Download or read book Python Algorithms written by Magnus Lie Hetland and published by Apress. This book was released on 2011-02-27 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: Python Algorithms explains the Python approach to algorithm analysis and design. Written by Magnus Lie Hetland, author of Beginning Python, this book is sharply focused on classical algorithms, but it also gives a solid understanding of fundamental algorithmic problem-solving techniques. The book deals with some of the most important and challenging areas of programming and computer science, but in a highly pedagogic and readable manner. The book covers both algorithmic theory and programming practice, demonstrating how theory is reflected in real Python programs. Well-known algorithms and data structures that are built into the Python language are explained, and the user is shown how to implement and evaluate others himself.
Download or read book Algorithms and Complexity written by Herbert S. Wilf and published by A K PETERS. This book was released on 2020-09-30 with total page 219 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is an introductory textbook on the design and analysis of algorithms. The author uses a careful selection of a few topics to illustrate the tools for algorithm analysis. Recursive algorithms are illustrated by Quicksort, FFT, fast matrix multiplications, and others. Algorithms associated with the network flow problem are fundamental in many areas of graph connectivity, matching theory, etc. Algorithms in number theory are discussed with some applications to public key encryption. This second edition will differ from the present edition mainly in that solutions to most of the exercises will be included.
Download or read book Average Case Analysis of Algorithms on Sequences written by Wojciech Szpankowski and published by John Wiley & Sons. This book was released on 2011-10-14 with total page 580 pages. Available in PDF, EPUB and Kindle. Book excerpt: A timely book on a topic that has witnessed a surge of interest over the last decade, owing in part to several novel applications, most notably in data compression and computational molecular biology. It describes methods employed in average case analysis of algorithms, combining both analytical and probabilistic tools in a single volume. * Tools are illustrated through problems on words with applications to molecular biology, data compression, security, and pattern matching. * Includes chapters on algorithms and data structures on words, probabilistic and analytical models, inclusion-exclusion principles, first and second moment methods, subadditive ergodic theorem and large deviations, elements of information theory, generating functions, complex asymptotic methods, Mellin transform and its applications, and analytic poissonization and depoissonization. * Written by an established researcher with a strong international reputation in the field.
Download or read book Introduction To Algorithms written by Thomas H Cormen and published by MIT Press. This book was released on 2001 with total page 1216 pages. Available in PDF, EPUB and Kindle. Book excerpt: An extensively revised edition of a mathematically rigorous yet accessible introduction to algorithms.
Download or read book Theory of Evolutionary Computation written by Benjamin Doerr and published by Springer Nature. This book was released on 2019-11-20 with total page 527 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited book reports on recent developments in the theory of evolutionary computation, or more generally the domain of randomized search heuristics. It starts with two chapters on mathematical methods that are often used in the analysis of randomized search heuristics, followed by three chapters on how to measure the complexity of a search heuristic: black-box complexity, a counterpart of classical complexity theory in black-box optimization; parameterized complexity, aimed at a more fine-grained view of the difficulty of problems; and the fixed-budget perspective, which answers the question of how good a solution will be after investing a certain computational budget. The book then describes theoretical results on three important questions in evolutionary computation: how to profit from changing the parameters during the run of an algorithm; how evolutionary algorithms cope with dynamically changing or stochastic environments; and how population diversity influences performance. Finally, the book looks at three algorithm classes that have only recently become the focus of theoretical work: estimation-of-distribution algorithms; artificial immune systems; and genetic programming. Throughout the book the contributing authors try to develop an understanding for how these methods work, and why they are so successful in many applications. The book will be useful for students and researchers in theoretical computer science and evolutionary computing.
Download or read book Computer Aided Verification written by Armin Biere and published by Springer. This book was released on 2014-06-28 with total page 904 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 26th International Conference on Computer Aided Verification, CAV 2014, held as part of the Vienna Summer of Logic, VSL 2014, in Vienna, Austria, in July 2014. The 46 regular papers and 11 short papers presented in this volume were carefully reviewed and selected from a total of 175 regular and 54 short paper submissions. The contributions are organized in topical sections named: software verification; automata; model checking and testing; biology and hybrid systems; games and synthesis; concurrency; SMT and theorem proving; bounds and termination; and abstraction.
Download or read book Computational Complexity written by and published by . This book was released on 1998 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Computational Complexity and Feasibility of Data Processing and Interval Computations written by V. Kreinovich and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 460 pages. Available in PDF, EPUB and Kindle. Book excerpt: Targeted audience • Specialists in numerical computations, especially in numerical optimiza tion, who are interested in designing algorithms with automatie result ver ification, and who would therefore be interested in knowing how general their algorithms caIi in principle be. • Mathematicians and computer scientists who are interested in the theory 0/ computing and computational complexity, especially computational com plexity of numerical computations. • Students in applied mathematics and computer science who are interested in computational complexity of different numerical methods and in learning general techniques for estimating this computational complexity. The book is written with all explanations and definitions added, so that it can be used as a graduate level textbook. What this book .is about Data processing. In many real-life situations, we are interested in the value of a physical quantity y that is diflicult (or even impossible) to measure directly. For example, it is impossible to directly measure the amount of oil in an oil field or a distance to a star. Since we cannot measure such quantities directly, we measure them indirectly, by measuring some other quantities Xi and using the known relation between y and Xi'S to reconstruct y. The algorithm that transforms the results Xi of measuring Xi into an estimate fj for y is called data processing.
