Agile development methods began to emerge around 20 years ago. However, it was not until the early 2000s that they began to be widely used in industry. This growth was often due to the advent of Internet services requiring faster cycles of development in order to heighten the rate at which an ever-greater number of functionalities...
Here is a state of art examination on exact and approximate algorithms for a number of important NP-hard problems in the field of integer linear programming, which the authors refer to as ``knapsack.'' Includes not only the classical knapsack problems such as binary, bounded, unbounded or binary multiple, but also less familiar problems...
An introduction to probability at the undergraduate level
Chance and randomness are encountered on a daily basis. Authored by a highly qualified professor in the field, Probability: With Applications and R delves into the theories and applications essential to obtaining a thorough understanding of probability.
A thorough and insightful introduction to using genetic algorithms to optimize electromagnetic systems
Genetic Algorithms in Electromagnetics focuses on optimizing the objective function when a computer algorithm, analytical model, or experimental result describes the performance of an electromagnetic system. It...
Learn how to solve complex differential equations using MATLAB®
Introduction to Numerical Ordinary and Partial Differential Equations Using MATLAB® teaches readers how to numerically solve both ordinary and partial differential equations with ease. This innovative publication brings together a skillful treatment of MATLAB...
A hands-on tutorial on building and using multidimensional data warehouses
The SQL query language is used to access data in most simple databases. But for multidimensional (or OLAP) data warehouses, Microsoft developed MDX. The MDX query language has become essential know-how for developers and users alike, whether for data...
Modern microprocessors such as Intel's Pentium chip typically contain millions of transitors. Known generically as Very Large-Scale Integrated (VLSI) systems, the chips have a scale and complexity that has necessitated the development of CAD tools to automate their design. This book focuses on the algorithms which are the building blocks of...
Data mining is the process of automatically searching large volumes of data for models and patterns using computational techniques from statistics, machine learning and information theory; it is the ideal tool for such an extraction of knowledge. Data mining is usually associated with a business or an organization's need to identify...
Now updated—the systematic introductory guide to modern analysis of large data sets
As data sets continue to grow in size and complexity, there has been an inevitable move towards indirect, automatic, and intelligent data analysis in which the analyst works via more complex and sophisticated software tools. This book...
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...
This book is designed to provide a comprehensive introduction to the design and
analysis of computer algorithms and data structures. In terms M the computer science
and computer engineering curricula, we have written this book to be primarily
focused on the Junior-Senior level Algorithms (CS7) course, which is taught as a...
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...
