Leverage the numerical and mathematical modules in Python and its standard library as well as popular open source numerical Python packages like NumPy, SciPy, FiPy, matplotlib and more. This fully revised edition, updated with the latest details of each package and changes to Jupyter projects, demonstrates how to numerically compute...
Explore the concepts, patterns, and architecture behind AppRun applications. With this end-to-end guide, you will be able to build web apps fast to the market with the low learning curve and high development productivity.
You will learn how to break down the application logic into three decoupled parts:...
This is the first book where mathematics and computer science are directly confronted and joined to tackle intricate problems in computer science with deep mathematical approaches. It contains a collection of refereed papers presented at the Colloquium on Mathematics and Computer Science held at the University of Versailles-St-Quentin on...
This comprehensive compendium of algorithms and data structures covers many theoretical issues from a practical perspective. Chapters include information on finite precision issues as well as discussions on specific algorithms where algorithmic techniques are of special importance - for example, algorithms for drawing graphs, algorithms for...
Mathematical Methods and Algorithms for Signal Processing tackles the challenge of providing readers and practitioners with the broad tools of mathematics employed in modern signal processing. Building from an assumed background in signals and stochastic processes, the book provides a solid foundation in analysis, linear...
This book presents a comprehensive overview of medical image analysis. Practical in approach, the text is uniquely structured by potential applications. Features: presents learning objectives, exercises and concluding remarks in each chapter, in addition to a glossary of abbreviations; describes a range of common imaging techniques,...
Graphical models (e.g., Bayesian and constraint networks, influence diagrams, and Markov decision processes) have become a central paradigm for knowledge representation and reasoning in both artificial intelligence and computer science in general. These models are used to perform many reasoning tasks, such as scheduling, planning and...
This volume contains articles written by leading researchers in the fields of algorithms, architectures, and information systems security. The first five chapters address several challenging geometric problems and related algorithms. These topics have major applications in pattern recognition, image analysis, digital geometry, surface...
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...
This volume presents an extensive collection of contributions covering aspects of the exciting and important research field of data mining techniques in biomedicine. Coverage includes new approaches for the analysis of biomedical data; applications of data mining techniques to real-life problems in medical practice; comprehensive...
With the advancement of statistical methodology inextricably linked to the use of computers, new methodological ideas must be translated into usable code and then numerically evaluated relative to competing procedures. In response to this, Statistical Computing in C++ and R concentrates on the writing of code rather...
