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Author: Ue Kiao
Publisher:
ISBN:
Category :
Languages : en
Pages : 163
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Book Description
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.
Author: Ue Kiao
Publisher:
ISBN:
Category :
Languages : en
Pages : 163
Get Book Here
Book Description
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.
Author: David Gries
Publisher: Springer Science & Business Media
ISBN: 1475738374
Category : Computers
Languages : en
Pages : 517
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Book Description
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.
Author: Sanjeev Arora
Publisher: Cambridge University Press
ISBN: 0521424267
Category : Computers
Languages : en
Pages : 609
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Book Description
New and classical results in computational complexity, including interactive proofs, PCP, derandomization, and quantum computation. Ideal for graduate students.
Author: Chris Okasaki
Publisher: Cambridge University Press
ISBN: 9780521663502
Category : Computers
Languages : en
Pages : 236
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Book Description
This book describes data structures and data structure design techniques for functional languages.
Author: Peter David Miller
Publisher: American Mathematical Soc.
ISBN: 0821840789
Category : Mathematics
Languages : en
Pages : 488
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Book Description
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.
Author: Anne Benoit
Publisher: CRC Press
ISBN: 1439898138
Category : Computers
Languages : en
Pages : 380
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Book Description
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.
Author: Peter M. Kuhn
Publisher: Springer Science & Business Media
ISBN: 1475744749
Category : Computers
Languages : en
Pages : 242
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Book Description
MPEG-4 is the multimedia standard for combining interactivity, natural and synthetic digital video, audio and computer-graphics. Typical applications are: internet, video conferencing, mobile videophones, multimedia cooperative work, teleteaching and games. With MPEG-4 the next step from block-based video (ISO/IEC MPEG-1, MPEG-2, CCITT H.261, ITU-T H.263) to arbitrarily-shaped visual objects is taken. This significant step demands a new methodology for system analysis and design to meet the considerably higher flexibility of MPEG-4. Motion estimation is a central part of MPEG-1/2/4 and H.261/H.263 video compression standards and has attracted much attention in research and industry, for the following reasons: it is computationally the most demanding algorithm of a video encoder (about 60-80% of the total computation time), it has a high impact on the visual quality of a video encoder, and it is not standardized, thus being open to competition. Algorithms, Complexity Analysis, and VLSI Architectures for MPEG-4 Motion Estimation covers in detail every single step in the design of a MPEG-1/2/4 or H.261/H.263 compliant video encoder: Fast motion estimation algorithms Complexity analysis tools Detailed complexity analysis of a software implementation of MPEG-4 video Complexity and visual quality analysis of fast motion estimation algorithms within MPEG-4 Design space on motion estimation VLSI architectures Detailed VLSI design examples of (1) a high throughput and (2) a low-power MPEG-4 motion estimator. Algorithms, Complexity Analysis and VLSI Architectures for MPEG-4 Motion Estimation is an important introduction to numerous algorithmic, architectural and system design aspects of the multimedia standard MPEG-4. As such, all researchers, students and practitioners working in image processing, video coding or system and VLSI design will find this book of interest.
Author: Thomas H Cormen
Publisher: MIT Press
ISBN: 9780262032933
Category : Computers
Languages : en
Pages : 1216
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Book Description
An extensively revised edition of a mathematically rigorous yet accessible introduction to algorithms.
Author: Benjamin Doerr
Publisher: Springer Nature
ISBN: 3030294145
Category : Computers
Languages : en
Pages : 506
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Book Description
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.
Author: Magnus Lie Hetland
Publisher: Apress
ISBN: 1430232382
Category : Computers
Languages : en
Pages : 325
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Book Description
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.
