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Maths for computer scientists

See below for a selection of the latest books from Maths for computer scientists category. Presented with a red border are the Maths for computer scientists books that have been lovingly read and reviewed by the experts at Lovereading. With expert reading recommendations made by people with a passion for books and some unique features Lovereading will help you find great Maths for computer scientists books and those from many more genres to read that will keep you inspired and entertained. And it's all free!

Linear Algebra And Optimization With Applications To Machine Learning - Volume I: Linear Algebra For Computer Vision, Robotics, And Machine Learning

Linear Algebra And Optimization With Applications To Machine Learning - Volume I: Linear Algebra For Computer Vision, Robotics, And Machine Learning

This book provides the mathematical fundamentals of linear algebra to practicers in computer vision, machine learning, robotics, applied mathematics, and electrical engineering. By only assuming a knowledge of calculus, the authors develop, in a rigorous yet down to earth manner, the mathematical theory behind concepts such as: vectors spaces, bases, linear maps, duality, Hermitian spaces, the spectral theorems, SVD, and the primary decomposition theorem. At all times, pertinent real-world applications are provided. This book includes the mathematical explanations for the tools used which we believe that is adequate for computer scientists, engineers and mathematicians who really want to do serious research and make significant contributions in their respective fields.

Linear Algebra And Optimization With Applications To Machine Learning - Volume I: Linear Algebra For Computer Vision, Robotics, And Machine Learning

Linear Algebra And Optimization With Applications To Machine Learning - Volume I: Linear Algebra For Computer Vision, Robotics, And Machine Learning

Author: Jean H (Univ Of Pennsylvania, Usa) Gallier, Jocelyn (Univ Of Pennsylvania, Usa) Quaintance Format: Paperback / softback Release Date: 16/01/2020

This book provides the mathematical fundamentals of linear algebra to practicers in computer vision, machine learning, robotics, applied mathematics, and electrical engineering. By only assuming a knowledge of calculus, the authors develop, in a rigorous yet down to earth manner, the mathematical theory behind concepts such as: vectors spaces, bases, linear maps, duality, Hermitian spaces, the spectral theorems, SVD, and the primary decomposition theorem. At all times, pertinent real-world applications are provided. This book includes the mathematical explanations for the tools used which we believe that is adequate for computer scientists, engineers and mathematicians who really want to do serious research and make significant contributions in their respective fields.

A User-Friendly Introduction to Discrete Mathematics for Computer Science

A User-Friendly Introduction to Discrete Mathematics for Computer Science

Author: W.A. Labuschagne Format: Paperback / softback Release Date: 11/11/2019

What mathematical skills do you need to understand computers and the problems they can solve? This book introduces the basic ideas of set theory, logic and combinatorics. Intended for those who work alone and whose experiences of mathematics have in the past perhaps been somewhat intimidating, the book adopts an informal tone and chats to the reader as a well-informed friend might. In addition to its treatment of mathematical topics, it draws the attention of the reader to general patterns of thought, some of which constitute useful problem-solving skills that may be used in other domains.

Wavelets A Mathematical Tool for Signal Analysis

Wavelets A Mathematical Tool for Signal Analysis

Author: Charles K. (Texas A & M University) Chui Format: Paperback / softback Release Date: 11/11/2019

Wavelets continue to be powerful mathematical tools that can be used to solve problems for which the Fourier (spectral) method does not perform well or cannot handle. This book is for engineers, applied mathematicians, and other scientists who want to learn about using wavelets to analyze, process, and synthesize images and signals. Applications are described in detail and there are step-by-step instructions about how to construct and apply wavelets. The only mathematically rigorous monograph written by a mathematician specifically for nonspecialists, it describes the basic concepts of these mathematical techniques, outlines the procedures for using them, compares the performance of various approaches, and provides information for problem solving, putting the reader at the forefront of current research. Written for an interdisciplinary audience of engineers, applied mathematicians, and other scientists with little or no knowledge of wavelets, readers with an undergraduate background in applied mathematics or engineering will appreciate this book.

Classics in Applied Mathematics Singular Perturbation Methods in Control: Analysis and Design

Classics in Applied Mathematics Singular Perturbation Methods in Control: Analysis and Design

Author: Petar V. Kokotovic, Hassan K. Khali, John O'Reilly Format: Paperback / softback Release Date: 09/11/2019

Singular perturbations and time-scale techniques were introduced to control engineering in the late 1960s and have since become common tools for the modeling, analysis, and design of control systems. In this SIAM Classics edition of the 1986 book, the original text is reprinted in its entirety (along with a new preface), providing once again the theoretical foundation for representative control applications. This book continues to be essential in many ways. It lays down the foundation of singular perturbation theory for linear and nonlinear systems, it presents the methodology in a pedagogical way that is not available anywhere else, and it illustrates the theory with many solved examples, including various physical examples and applications. So while new developments may go beyond the topics covered in this book, they are still based on the methodology described here, which continues to be their common starting point.

Stochastic Models in Reliability, Network Security and System Safety Essays Dedicated to Professor Jinhua Cao on the Occasion of His 80th Birthday

Stochastic Models in Reliability, Network Security and System Safety Essays Dedicated to Professor Jinhua Cao on the Occasion of His 80th Birthday

Author: Quan-Lin Li Format: Paperback / softback Release Date: 30/10/2019

This book is dedicated to Jinhua Cao on the occasion of his 80th birthday. Jinhua Cao is one of the most famous reliability theorists. His main contributions include: published over 100 influential scientific papers; published an interesting reliability book in Chinese in 1986, which has greatly influenced the reliability of education, academic research and engineering applications in China; initiated and organized Reliability Professional Society of China (the first part of Operations Research Society of China) since 1981. The high admiration that Professor Cao enjoys in the reliability community all over the world was witnessed by the enthusiastic response of each contributor in this book. The contributors are leading researchers with diverse research perspectives. The research areas of the book iclude a broad range of topics related to reliability models, queueing theory, manufacturing systems, supply chain finance, risk management, Markov decision processes, blockchain and so forth. The book consists of a brief Preface describing the main achievements of Professor Cao; followed by congratulations from Professors Way Kuo and Wei Wayne Li, and by Operations Research Society of China, and Reliability Professional Society of China; and further followed by 25 articles roughly grouped together. Most of the articles are written in a style understandable to a wide audience. This book is useful to anyone interested in recent developments in reliability, network security, system safety, and their stochastic modeling and analysis.

Mathematical Optimization Theory and Operations Research 18th International Conference, MOTOR 2019, Ekaterinburg, Russia, July 8 - 12, 2019, Revised Selected Papers

Mathematical Optimization Theory and Operations Research 18th International Conference, MOTOR 2019, Ekaterinburg, Russia, July 8 - 12, 2019, Revised Selected Papers

Author: Igor Bykadorov Format: Paperback / softback Release Date: 27/10/2019

This book constitutes revised and selected papers from the 18th International Conference on Mathematical Optimization Theory and Operations Research, MOTOR 2019, held in Ekaterinburg, Russia, in July 2019. The 40 full papers and 4 short papers presented in this volume were carefully reviewed and selected from a total of 170 submissions. The papers in the volume are organised according to the following topical headings: combinatorial optimization; game theory and mathematical economics; data mining and computational geometry; integer programming; mathematical programming; operations research; optimal control and applications.

Information Technologies and Mathematical Modelling. Queueing Theory and Applications 18th International Conference, ITMM 2019, Named after A.F. Terpugov, Saratov, Russia, June 26-30, 2019, Revised Se

Information Technologies and Mathematical Modelling. Queueing Theory and Applications 18th International Conference, ITMM 2019, Named after A.F. Terpugov, Saratov, Russia, June 26-30, 2019, Revised Se

Author: Alexander Dudin Format: Paperback / softback Release Date: 21/10/2019

This book constitutes the proceedings of the 18th International Conference on Information Technologies and Mathematical Modelling, ITMM 2019, named after A.F. Terpugov, held in Saratov, Russia, in June 2019. The 25 full papers presented in this volume were carefully reviewed and selected from 72 submissions. The conference covers various aspects of information technologies, focusing on queueing theory, stochastic processes, Markov processes, renewal theory, network performance equation and network protocols.

Queueing Theory and Network Applications 14th International Conference, QTNA 2019, Ghent, Belgium, August 27-29, 2019, Proceedings

Queueing Theory and Network Applications 14th International Conference, QTNA 2019, Ghent, Belgium, August 27-29, 2019, Proceedings

Author: Tuan Phung-Duc Format: Paperback / softback Release Date: 15/08/2019

This book constitutes the proceedings of the 14th International Conference on Queueing Theory and Network Applications, QTNA 2019, held in Ghent, Belgium, in August 2019.The 23 full papers included in this volume were carefully reviewed and selected from 49 initial submissions. The papers are organized in topical sections on Retrial Queues; Controllable Queues; Strategic Queues; Queueing Networks; Scheduling Policies; Multidimensional Systems; and Queueing Models in Applications.

Computing with Foresight and Industry 15th Conference on Computability in Europe, CiE 2019, Durham, UK, July 15-19, 2019, Proceedings

Computing with Foresight and Industry 15th Conference on Computability in Europe, CiE 2019, Durham, UK, July 15-19, 2019, Proceedings

Author: Florin Manea Format: Paperback / softback Release Date: 19/06/2019

This book constitutes the refereed proceedings of the 15th Conference on Computability in Europe, CiE 2019, held in Durham, UK, in July 2019. The 20 revised full papers presented were carefully reviewed and selected from 35 submissions. In addition, this volume includes 7 invited papers. The conference CiE 2018 had the following six special sessions: computational neuroscience, history and philosophy of computing, lowness notions in computability, probabilistic programming and higher-order computation, smoothed and probabilistic analysis of algorithms, and transnite computations.

Probability and Statistics for Computer Scientists, Third Edition

Probability and Statistics for Computer Scientists, Third Edition

Author: Michael (American University, Washington, DC) Baron Format: Hardback Release Date: 14/06/2019

Praise for the Second Edition: The author has done his homework on the statistical tools needed for the particular challenges computer scientists encounter... [He] has taken great care to select examples that are interesting and practical for computer scientists. ... The content is illustrated with numerous figures, and concludes with appendices and an index. The book is erudite and ... could work well as a required text for an advanced undergraduate or graduate course. ---Computing Reviews Probability and Statistics for Computer Scientists, Third Edition helps students understand fundamental concepts of Probability and Statistics, general methods of stochastic modeling, simulation, queuing, and statistical data analysis; make optimal decisions under uncertainty; model and evaluate computer systems; and prepare for advanced probability-based courses. Written in a lively style with simple language and now including R as well as MATLAB, this classroom-tested book can be used for one- or two-semester courses. Features: Axiomatic introduction of probability Expanded coverage of statistical inference and data analysis, including estimation and testing, Bayesian approach, multivariate regression, chi-square tests for independence and goodness of fit, nonparametric statistics, and bootstrap Numerous motivating examples and exercises including computer projects Fully annotated R codes in parallel to MATLAB Applications in computer science, software engineering, telecommunications, and related areas In-Depth yet Accessible Treatment of Computer Science-Related Topics Starting with the fundamentals of probability, the text takes students through topics heavily featured in modern computer science, computer engineering, software engineering, and associated fields, such as computer simulations, Monte Carlo methods, stochastic processes, Markov chains, queuing theory, statistical inference, and regression. It also meets the requirements of the Accreditation Board for Engineering and Technology (ABET). About the Author Michael Baron is David Carroll Professor of Mathematics and Statistics at American University in Washington D. C. He conducts research in sequential analysis and optimal stopping, change-point detection, Bayesian inference, and applications of statistics in epidemiology, clinical trials, semiconductor manufacturing, and other fields. M. Baron is a Fellow of the American Statistical Association and a recipient of the Abraham Wald Prize for the best paper in Sequential Analysis and the Regents Outstanding Teaching Award. M. Baron holds a Ph.D. in statistics from the University of Maryland. In his turn, he supervised twelve doctoral students, mostly employed on academic and research positions.