Learn IT - Books tags markov

New Directions in Statistical Signal Processing: From Systems to Brains (Neural Information Processing)

MIT Press, 2006

Signal processing and neural computation have separately and significantly influenced many disciplines, but the cross-fertilization of the two fields has begun only recently. Research now shows that each has much to teach the other, as we see highly sophisticated kinds of signal processing and elaborate hierachical levels of neural computation...

Tools and Algorithms for the Construction and Analysis of Systems (Lecture Notes in Computer Science)

Springer, 2007

ETAPS 2007 is the tenth instance of the European Joint Conferences on Theory and Practice of Software, and thus a cause for celebration.

The events that comprise ETAPS address various aspects of the system development process, including specification, design, implementation, analysis and...

Computer Age Statistical Inference: Algorithms, Evidence, and Data Science (Institute of Mathematical Statistics Monographs)

Cambridge University Press, 2016

The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. “Big data,” “data science,” and “machine learning” have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science...

Advanced Signal Processing and Noise Reduction, 2nd Edition

John Wiley & Sons, 2000

This book presents a broad range of theory and application of statistical signal processing. The emphasis is on digital noise reduction algorithms, particularly important in the field of mobile communication. Vaseghi covers a broad range of applications, including spectral estimation, channel equalization, speech coding over noisy channels,...

Matrix Methods, Third Edition: Applied Linear Algebra

Academic Press, 2008

Matrix Methods: Applied Linear Algebra, 3e, as a textbook, provides a unique and comprehensive balance between the theory and computation of matrices. The application of matrices is not just for mathematicians. The use by other disciplines has grown dramatically over the years in response to the rapid changes in technology. Matrix methods is...

Continuous Average Control of Piecewise Deterministic Markov Processes (SpringerBriefs in Mathematics)

Springer, 2013

The intent of this book is to present recent results in the control theory for the long run average continuous control problem of piecewise deterministic Markov processes (PDMPs). The book focuses mainly on the long run average cost criteria and extends to the PDMPs some well-known techniques related to discrete-time and continuous-time...

Metric Embeddings (de Gruyter Studies in Mathematics)

De Gruyter, 2013

Embeddings of discrete metric spaces into Banach spaces recently became an important tool in computer science and topology. The book will help readers to enter and to work in this very rapidly developing area having many important connections with different parts of mathematics and computer science.

The purpose of the book is to...

Random Walks and Diffusions on Graphs and Databases: An Introduction (Springer Series in Synergetics)

Springer, 2011

Most networks and databases that humans have to deal with contain large, albeit finite number of units. Their structure, for maintaining functional consistency of the components, is essentially not random and calls for a precise quantitative description of relations between nodes (or data units) and all network components. This book is an...

Probability Theory: A Comprehensive Course (Universitext)

Springer, 2013

This second edition of the popular textbook contains a comprehensive course in modern probability theory. Overall, probabilistic concepts play an increasingly important role in mathematics, physics, biology, financial engineering and computer science. They help us in understanding magnetism, amorphous media, genetic diversity and the perils...

Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques

Springer, 2011

This volume contains the papers presented at the 14th International Workshop on Approximation Algorithms for Combinatorial Optimization Problems (APPROX 2011) and the 15th International Workshop on Randomization and Computation (RANDOM 2011), which took place concurrently in Princeton University, USA, during August 17–19,...

The Variational Bayes Method in Signal Processing

Springer, 2005

This is the first book-length treatment of the Variational Bayes (VB) approximation in signal processing. It has been written as a self-contained, self-learning guide for academic and industrial research groups in signal processing, data analysis, machine learning, identification and control. It reviews the VB distributional approximation, showing...

Probabilistic Graphical Models: Principles and Techniques (Adaptive Computation and Machine Learning series)

MIT Press, 2009

Most tasks require a person or an automated system to reason--to reach conclusions based on available information. The framework of probabilistic graphical models, presented in this book, provides a general approach for this task. The approach is model-based, allowing interpretable models to be constructed and then manipulated by reasoning...

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