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Complexity And Time
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Book Synopsis Complexity and the Arrow of Time by : Charles H. Lineweaver
Download or read book Complexity and the Arrow of Time written by Charles H. Lineweaver and published by Cambridge University Press. This book was released on 2013-08-08 with total page 371 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written by a wide range of experts, this work presents cosmological, biological and philosophical perspectives on complexity in our universe.
Book Synopsis Computational Complexity by : Sanjeev Arora
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.
Book Synopsis Complexity of Seismic Time Series by : Tamaz Chelidze
Download or read book Complexity of Seismic Time Series written by Tamaz Chelidze and published by Elsevier. This book was released on 2018-05-21 with total page 548 pages. Available in PDF, EPUB and Kindle. Book excerpt: Complexity of Seismic Time Series: Measurement and Application applies the tools of nonlinear dynamics to seismic analysis, allowing for the revelation of new details in micro-seismicity, new perspectives in seismic noise, and new tools for prediction of seismic events. The book summarizes both advances and applications in the field, thus meeting the needs of both fundamental and practical seismology. Merging the needs of the classical field and the very modern terms of complexity science, this book covers theory and its application to advanced nonlinear time series tools to investigate Earth's vibrations, making it a valuable tool for seismologists, hazard managers and engineers. - Covers the topic of Earth's vibrations involving many different aspects of theoretical and observational seismology - Identifies applications of advanced nonlinear time series tools for the characterization of these Earth's signals - Merges the needs of geophysics with the applications of complexity theory - Describes different methodologies to analyze problems, not only in the context of geosciences, but also those associated with different complex systems across disciplines
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 Data Science written by Ivo D. Dinov and published by Walter de Gruyter GmbH & Co KG. This book was released on 2021-12-06 with total page 489 pages. Available in PDF, EPUB and Kindle. Book excerpt: The amount of new information is constantly increasing, faster than our ability to fully interpret and utilize it to improve human experiences. Addressing this asymmetry requires novel and revolutionary scientific methods and effective human and artificial intelligence interfaces. By lifting the concept of time from a positive real number to a 2D complex time (kime), this book uncovers a connection between artificial intelligence (AI), data science, and quantum mechanics. It proposes a new mathematical foundation for data science based on raising the 4D spacetime to a higher dimension where longitudinal data (e.g., time-series) are represented as manifolds (e.g., kime-surfaces). This new framework enables the development of innovative data science analytical methods for model-based and model-free scientific inference, derived computed phenotyping, and statistical forecasting. The book provides a transdisciplinary bridge and a pragmatic mechanism to translate quantum mechanical principles, such as particles and wavefunctions, into data science concepts, such as datum and inference-functions. It includes many open mathematical problems that still need to be solved, technological challenges that need to be tackled, and computational statistics algorithms that have to be fully developed and validated. Spacekime analytics provide mechanisms to effectively handle, process, and interpret large, heterogeneous, and continuously-tracked digital information from multiple sources. The authors propose computational methods, probability model-based techniques, and analytical strategies to estimate, approximate, or simulate the complex time phases (kime directions). This allows transforming time-varying data, such as time-series observations, into higher-dimensional manifolds representing complex-valued and kime-indexed surfaces (kime-surfaces). The book includes many illustrations of model-based and model-free spacekime analytic techniques applied to economic forecasting, identification of functional brain activation, and high-dimensional cohort phenotyping. Specific case-study examples include unsupervised clustering using the Michigan Consumer Sentiment Index (MCSI), model-based inference using functional magnetic resonance imaging (fMRI) data, and model-free inference using the UK Biobank data archive. The material includes mathematical, inferential, computational, and philosophical topics such as Heisenberg uncertainty principle and alternative approaches to large sample theory, where a few spacetime observations can be amplified by a series of derived, estimated, or simulated kime-phases. The authors extend Newton-Leibniz calculus of integration and differentiation to the spacekime manifold and discuss possible solutions to some of the "problems of time". The coverage also includes 5D spacekime formulations of classical 4D spacetime mathematical equations describing natural laws of physics, as well as, statistical articulation of spacekime analytics in a Bayesian inference framework. The steady increase of the volume and complexity of observed and recorded digital information drives the urgent need to develop novel data analytical strategies. Spacekime analytics represents one new data-analytic approach, which provides a mechanism to understand compound phenomena that are observed as multiplex longitudinal processes and computationally tracked by proxy measures. This book may be of interest to academic scholars, graduate students, postdoctoral fellows, artificial intelligence and machine learning engineers, biostatisticians, econometricians, and data analysts. Some of the material may also resonate with philosophers, futurists, astrophysicists, space industry technicians, biomedical researchers, health practitioners, and the general public.
Book Synopsis Data Structures & Algorithms in Swift (Fourth Edition) by : raywenderlich Tutorial Team
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.
Book Synopsis Learn Data Structures and Algorithms with Golang by : Bhagvan Kommadi
Download or read book Learn Data Structures and Algorithms with Golang written by Bhagvan Kommadi and published by Packt Publishing Ltd. This book was released on 2019-03-30 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore Golang's data structures and algorithms to design, implement, and analyze code in the professional setting Key FeaturesLearn the basics of data structures and algorithms and implement them efficientlyUse data structures such as arrays, stacks, trees, lists and graphs in real-world scenariosCompare the complexity of different algorithms and data structures for improved code performanceBook Description Golang is one of the fastest growing programming languages in the software industry. Its speed, simplicity, and reliability make it the perfect choice for building robust applications. This brings the need to have a solid foundation in data structures and algorithms with Go so as to build scalable applications. Complete with hands-on tutorials, this book will guide you in using the best data structures and algorithms for problem solving. The book begins with an introduction to Go data structures and algorithms. You'll learn how to store data using linked lists, arrays, stacks, and queues. Moving ahead, you'll discover how to implement sorting and searching algorithms, followed by binary search trees. This book will also help you improve the performance of your applications by stringing data types and implementing hash structures in algorithm design. Finally, you'll be able to apply traditional data structures to solve real-world problems. By the end of the book, you'll have become adept at implementing classic data structures and algorithms in Go, propelling you to become a confident Go programmer. What you will learnImprove application performance using the most suitable data structure and algorithmExplore the wide range of classic algorithms such as recursion and hashing algorithmsWork with algorithms such as garbage collection for efficient memory management Analyze the cost and benefit trade-off to identify algorithms and data structures for problem solvingExplore techniques for writing pseudocode algorithm and ace whiteboard coding in interviewsDiscover the pitfalls in selecting data structures and algorithms by predicting their speed and efficiencyWho this book is for This book is for developers who want to understand how to select the best data structures and algorithms that will help solve coding problems. Basic Go programming experience will be an added advantage.
Book Synopsis Time Complexity Analysis by : Ue Kiao
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.
Book Synopsis Descriptive Complexity by : Neil Immerman
Download or read book Descriptive Complexity written by Neil Immerman and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: By virtue of the close relationship between logic and relational databases, it turns out that complexity has important applications to databases such as analyzing the parallel time needed to compute a query, and the analysis of nondeterministic classes. This book is a relatively self-contained introduction to the subject, which includes the necessary background material, as well as numerous examples and exercises.
Book Synopsis Data Structures & Algorithms in Kotlin (Second Edition) by : raywenderlich Tutorial Team
Download or read book Data Structures & Algorithms in Kotlin (Second Edition) written by raywenderlich Tutorial Team and published by . This book was released on 2021-06-30 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn Data Structures & Algorithms in Kotlin!Data structures and algorithms are fundamental tools every developer should have. In this book, you'll learn how to implement key data structures in Kotlin, and how to use them to solve a robust set of algorithms.This book is for intermediate Kotlin or Android developers who already know the basics of the language and want to improve their knowledge.Topics Covered in This BookIntroduction to Kotlin: If you're new to Kotlin, you can learn the main constructs and begin writing code.Complexity: When you study algorithms, you need a way to compare their performance in time and space. Learn about the Big-O notation to help you do this.Elementary Data Structures: Learn how to implement Linked List, Stacks, and Queues in Kotlin.Trees: Learn everything you need about Trees - in particular, Binary Trees, AVL Trees, as well as Binary Search and much more.Sorting Algorithms: Sorting algorithms are critical for any developer. Learn to implement the main sorting algorithms, using the tools provided by Kotlin.Graphs: Have you ever heard of Dijkstra and the calculation of the shortest path between two different points? Learn about Graphs and how to use them to solve the most useful and important algorithms.
Book Synopsis Python Algorithms by : Magnus Lie Hetland
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.
Book Synopsis A Logical Approach to Discrete Math by : David Gries
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 Think Complexity written by Allen Downey and published by "O'Reilly Media, Inc.". This book was released on 2012-03-02 with total page 159 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dive into Python's advanced possibilities, including algorithm analysis, graphs, scale-free networks, and cellular automata with this in-depth, hands-on guide.
Book Synopsis Time and the Rhythms of Emancipatory Education by : Michel Alhadeff-Jones
Download or read book Time and the Rhythms of Emancipatory Education written by Michel Alhadeff-Jones and published by Routledge. This book was released on 2016-10-26 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: Time and the Rhythms of Emancipatory Education argues that by rethinking the way we relate to time, we can fundamentally rethink the way we conceive education. Beyond the contemporary rhetoric of acceleration, speed, urgency or slowness, this book provides an epistemological, historical and theoretical framework that will serve as a comprehensive resource for critical reflection on the relationship between the experience of time and emancipatory education. Drawing upon time and rhythm studies, complexity theories and educational research, Alhadeff-Jones reflects upon the temporal and rhythmic dimensions of education in order to (re)theorize and address current societal and educational challenges. The book is divided into three parts. The first begins by discussing the specificities inherent to the study of time in educational sciences. The second contextualizes the evolution of temporal constraints that determine the ways education is institutionalized, organized, and experienced. The third and final part questions the meanings of emancipatory education in a context of temporal alienation. This is the first book to provide a broad overview of European and North-American theories that inform both the ideas of time and rhythm in educational sciences, from school instruction, curriculum design and arts education, to vocational training, lifelong learning and educational policies. It will be of key interest to academics, researchers and postgraduate students in the fields of philosophy of education, sociology of education, history of education, psychology, curriculum and learning theory, and adult education. The Open Access version of this book, available at http://www.taylorfrancis.com, has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives 4.0 license.
Book Synopsis An Introduction to Kolmogorov Complexity and Its Applications by : Ming Li
Download or read book An Introduction to Kolmogorov Complexity and Its Applications written by Ming Li and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 655 pages. Available in PDF, EPUB and Kindle. Book excerpt: Briefly, we review the basic elements of computability theory and prob ability theory that are required. Finally, in order to place the subject in the appropriate historical and conceptual context we trace the main roots of Kolmogorov complexity. This way the stage is set for Chapters 2 and 3, where we introduce the notion of optimal effective descriptions of objects. The length of such a description (or the number of bits of information in it) is its Kolmogorov complexity. We treat all aspects of the elementary mathematical theory of Kolmogorov complexity. This body of knowledge may be called algo rithmic complexity theory. The theory of Martin-Lof tests for random ness of finite objects and infinite sequences is inextricably intertwined with the theory of Kolmogorov complexity and is completely treated. We also investigate the statistical properties of finite strings with high Kolmogorov complexity. Both of these topics are eminently useful in the applications part of the book. We also investigate the recursion theoretic properties of Kolmogorov complexity (relations with Godel's incompleteness result), and the Kolmogorov complexity version of infor mation theory, which we may call "algorithmic information theory" or "absolute information theory. " The treatment of algorithmic probability theory in Chapter 4 presup poses Sections 1. 6, 1. 11. 2, and Chapter 3 (at least Sections 3. 1 through 3. 4).
Book Synopsis Algorithms and Complexity by : Herbert S. Wilf
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.
Book Synopsis Algorithms For Dummies by : John Paul Mueller
Download or read book Algorithms For Dummies written by John Paul Mueller and published by John Wiley & Sons. This book was released on 2017-04-24 with total page 434 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover how algorithms shape and impact our digital world All data, big or small, starts with algorithms. Algorithms are mathematical equations that determine what we see—based on our likes, dislikes, queries, views, interests, relationships, and more—online. They are, in a sense, the electronic gatekeepers to our digital, as well as our physical, world. This book demystifies the subject of algorithms so you can understand how important they are business and scientific decision making. Algorithms for Dummies is a clear and concise primer for everyday people who are interested in algorithms and how they impact our digital lives. Based on the fact that we already live in a world where algorithms are behind most of the technology we use, this book offers eye-opening information on the pervasiveness and importance of this mathematical science—how it plays out in our everyday digestion of news and entertainment, as well as in its influence on our social interactions and consumerism. Readers even learn how to program an algorithm using Python! Become well-versed in the major areas comprising algorithms Examine the incredible history behind algorithms Get familiar with real-world applications of problem-solving procedures Experience hands-on development of an algorithm from start to finish with Python If you have a nagging curiosity about why an ad for that hammock you checked out on Amazon is appearing on your Facebook page, you'll find Algorithm for Dummies to be an enlightening introduction to this integral realm of math, science, and business.
