Learn IT - Books tags undergraduate

Numerical Computing with MATLAB

SIAM, 2008

This is a lively textbook for an introductory course in numerical methods, MATLAB, and technical computing, which emphasises the informed use of mathematical software. Numerical Computing with MATLAB helps readers learn about the mathematical functions in MATLAB, how to appreciate their limitations, and how to use and modify them appropriately....

Principles of Distributed Database Systems

Springer, 2011

This third edition of a classic textbook can be used to teach at the senior undergraduate and graduate levels. The material concentrates on fundamental theories as well as techniques and algorithms. The advent of the Internet and the World Wide Web, and, more recently, the emergence of cloud computing and streaming data applications, has forced...

Finite Element Modeling for Materials Engineers Using MATLAB®

Springer, 2011

The finite element method is often used for numerical computation in the applied sciences. It makes a major contribution to the range of numerical methods used in the simulation of systems and irregular domains, and its importance today has made it an important subject of study for all engineering students.

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Agile Software Engineering (Undergraduate Topics in Computer Science)

Springer, 2008

This textbook presents the current issues in software development methods. Special emphasis is placed on agile software development, being one of the mainstream paradigms for the management of software projects. Features and topics: (1) Examines the Agile manifesto and its implications. (2) Discusses the delivery of software projects on time and...

Evolutionary Optimization Algorithms

John Wiley & Sons, 2013

A clear and lucid bottom-up approach to the basic principles of evolutionary algorithms

Evolutionary algorithms (EAs) are a type of artificial intelligence. EAs are motivated by optimization processes that we observe in nature, such as natural selection, species migration, bird swarms, human culture, and ant...

Graphs, Networks and Algorithms (Algorithms and Computation in Mathematics)

Springer, 2012

From the reviews of the previous editions

".... The book is a first class textbook and seems to be indispensable for everybody who has to teach combinatorial optimization. It is very helpful for students, teachers, and researchers in this area. The author finds a striking synthesis of nice and interesting...

Optimization Algorithms for Networks and Graphs

CRC Press, 1992

A revised and expanded advanced-undergraduate/graduate text (first ed., 1978) about optimization algorithms for problems that can be formulated on graphs and networks. This edition provides many new applications and algorithms while maintaining the classic foundations on which contemporary algorithm...

Introduction to Probability and Statistics Using R

K. G. Saur, 2019

This is a textbook for an undergraduate course in probability and statistics. The approximate prerequisites are two or three... More > semesters of calculus and some linear algebra. Students attending the class include mathematics, engineering, and computer science majors....

Multivariate Time Series Analysis: With R and Financial Applications

John Wiley & Sons, 2013

An accessible guide to the multivariate time series tools used in numerous real-world applications

Multivariate Time Series Analysis: With R and Financial Applications is the much anticipated sequel coming from one of the most influential and prominent experts on the topic of time series. Through a...

Circuit Analysis II With Matlab Applications

Orchard Publications, 2003

This text is written for use in a second course in circuit analysis. The reader of this book should have the traditional undergraduate knowledge of an introductory circuit analysis material such as Circuit Analysis I with MATLAB® Applications by this author. Another prerequisite would be knowledge of differential equations, and in most...

Solving Problems in Scientific Computing Using Maple and MATLAB®

Springer, 2001

From the reviews: ".. An excellent reference on undergraduate mathematical computing." (American Mathematical Monthly) "... manuals for such systems (Maple and MATLAB) tend to use trivial examples, making it difficult for new users of such systems to quickly apply their power to real problems. The authors have written a good book...

An Introduction to Bootstrap Methods with Applications to R

John Wiley & Sons, 2011

A comprehensive introduction to bootstrap methods in the R programming environment

Bootstrap methods provide a powerful approach to statistical data analysis, as they have more general applications than standard parametric methods. An Introduction to Bootstrap Methods with Applications to R explores the...

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