From industrial and teaching experience the authors provide a blend of theory and practice of digital signal processing (DSP) for advanced undergraduate and post-graduate engineers reading electronics. This fast-moving, developing area is driven by the information technology revolution. It is a source book in research and development for...
Combining concepts of mathematics and computer science, this book is about the sequences of symbols that can be generated by simple models of computation called "finite automata". Suitable for graduate students or advanced undergraduates, it starts from elementary principles and develops the basic theory. The study then progresses...
If you have a working knowledge of Haskell, this hands-on book shows you how to use the language’s many APIs and frameworks for writing both parallel and concurrent programs. You’ll learn how parallelism exploits multicore processors to speed up computation-heavy programs, and how concurrency enables you to write programs...
Extend your C# skills to F#—and create data-rich computational and parallel software components faster and more efficiently. Focusing on F# 3.0 and Microsoft Visual Studio 2012, you’ll learn how to exploit F# features to solve both computationally-complex problems as well as everyday programming tasks.
Explosive growth in the size of spatial databases has highlighted the need for spatial
data analysis and spatial data mining techniques to mine the interesting but implicit
spatial patterns within these large databases. Extracting useful and interesting patterns
from massive geo-spatial datasets is important for many application...
As we enter the "decade of data," the disparity between the vast amount of data storage capacity (measurable in terabytes and petabytes) and the bandwidth available for accessing it has created an input/output bottleneck that is proving to be a major constraint on the effective use of scientific data for research. Scalable...
This graduate-level textbook introduces fundamental concepts and methods in machine learning. It describes several important modern algorithms, provides the theoretical underpinnings of these algorithms, and illustrates key aspects for their application. The authors aim to present novel theoretical tools and concepts while giving concise...
Includes Complete Coverage of the OpenGL® Shading Language!
Today’s OpenGL software interface enables programmers to produce extraordinarily high-quality computer-generated images and interactive applications using 2D and 3D objects,...
Financial Modelling - Theory, Implementation and Practice is a unique combination of quantitative techniques, the application to financial problems and programming using Matlab. The book enables the reader to model, design and implement a wide range of financial models for derivatives pricing and asset allocation, providing...
With the increasing applications of intelligent robotic systems in various fields, the design and control of these systems have increasingly attracted interest from researchers. This edited book entitled Design and Control of Intelligent Robotic Systems in the book series of Studies in Computational Intelligence is a collection of some...
Recent years have seen the widespread application of Natural Computing algorithms (broadly defined in this context as computer algorithms whose design draws inspiration from phenomena in the natural world) for the purposes of financial modelling and optimisation. A related stream of work has also seen the application of learning mechanisms...
This collaborative volume presents recent trends arising from the fruitful interaction between the themes of combinatorics on words, automata and formal language theory, and number theory. Presenting several important tools and concepts, the authors also reveal some of the exciting and important relationships that exist between these...
