Learn IT - Books tags stochastic

Level Sets and Extrema of Random Processes and Fields

John Wiley & Sons, 2009

Level Sets and Extrema of Random Processes and Fields discusses how to understand the properties of the level sets of paths as well as how to compute the probability distribution of its extremal values, which are two general classes of problems that arise in the study of random processes and fields and in related applications. This book...

The Investopedia Guide to Wall Speak: The Terms You Need to Know to Talk Like Cramer, Think Like Soros, and Buy Like Buffett

McGraw-Hill, 2009

Have you ever used a stochastic oscillator?

Does your portfolio have spiders in it?

Do you really know what a derivative is?

From the creators of one of today’s most popular investing Web sites, The Investopedia Guide to Wall Speak...

Introduction to Random Signals and Noise

John Wiley & Sons, 2005

Random signals and noise are present in many engineering systems and networks. Signal processing techniques allow engineers to distinguish between useful signals in audio, video or communication equipment, and interference, which disturbs the desired signal.

With a strong mathematical grounding, this text...

Mobile Fading Channels: Modelling, Analysis, & Simulation

John Wiley & Sons, 2002

All relevant components of a mobile radio system, from digital modulation techniques over channel coding through to network aspects, are determined by the propagation characteristics of the channel. Therefore, a precise knowledge of mobile radio channels is crucial for the development, evaluation and test of current and future mobile radio...

Virtual Crowds: Methods, Simulation, and Control (Synthesis Lectures on Computer Graphics and Animation)

Morgan and Claypool Publishers, 2008

There are many applications of computer animation and simulation where it is necessary to model virtual crowds of autonomous agents. Some of these applications include site planning, education, entertainment, training, and human factors analysis for building evacuation. Other applications include simulations of scenarios where masses of people...

Advances in Minimum Description Length: Theory and Applications (Neural Information Processing)

MIT Press, 2005

The process of inductive inference—to infer general laws and principles from particular instances—is the basis of statistical modeling, pattern recognition, and machine learning. The Minimum Descriptive Length (MDL) principle, a powerful method of inductive inference, holds that the best explanation, given a limited set of observed...

Fuzzy Systems in Bioinformatics and Computational Biology (Studies in Fuzziness and Soft Computing)

Springer, 2009

Biological systems are inherently stochastic and uncertain. Thus, research in bioinformatics, biomedical engineering and computational biology has to deal with a large amount of uncertainties.

Fuzzy logic has shown to be a powerful tool in capturing different uncertainties in engineering systems. In recent years, fuzzy logic based modeling and...

Chaotic Modelling and Simulation: Analysis of Chaotic Models, Attractors and Forms

CRC Press, 2008

Chaotic Modelling and Simulation: Analysis of Chaotic Models, Attractors and Forms presents the main models developed by pioneers of chaos theory, along with new extensions and variations of these models. Using more than 500 graphs and illustrations, the authors show how to design, estimate, and test an array of models....

Kalman Filtering: Theory and Practice Using MATLAB

John Wiley & Sons, 2008

From Reviews of the First Edition

"An authentic magnum opus worth much more than its weight in gold!"
—IEEE Transactions on Automatic Control

The proven textbook on Kalman filtering—now fully updated, revised, and expanded

...

Introduction to Statistical Relational Learning (Adaptive Computation and Machine Learning)

MIT Press, 2007

Handling inherent uncertainty and exploiting compositional structure are fundamental to understanding and designing large-scale systems. Statistical relational learning builds on ideas from probability theory and statistics to address uncertainty while incorporating tools from logic, databases, and programming languages to represent structure. In...

Applications of Evolutionary Computing: EvoWorkshops 2007:EvoCOMNET, EvoFIN, EvoIASP, EvoINTERACTION, EvoMUSART, EvoSTOC, and EvoTransLog, Valencia, Spain

Springer, 2007

This book constitutes the refereed joint proceedings of seven workshops on evolutionary computing, EvoWorkshops 2007, held in Valencia, Spain in April 2007.

The 55 revised full papers and 24 revised short papers presented were carefully reviewed and selected from a total of 160 submissions. In accordance with the seven workshops covered, the...

Intelligent Data Analysis

Springer, 2007

This monograph is a detailed introductory presentation of the key classes of intelligent data analysis methods. The ten coherently written chapters by leading experts provide complete coverage of the core issues.

The first half of the book is devoted to the discussion of classical statistical issues, ranging from the basic concepts of...

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