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Handbook of Time Series Analysis
This handbook provides an up-to-date survey of current research topics and applications of time series analysis methods written by leading experts in their fields. It covers recent developments in univariate as well as bivariate and multivariate time series analysis techniques ranging from physics' to life sciences' applications. Each chapter comprises both methodological aspects and applications to real world complex systems, such as the human brain or Earth's climate. Covering an exceptionally broad spectrum of topics, beginners, experts and practitioners who seek to understand the latest developments will profit from this handbook.
Seizure Prediction in Epilepsy
Comprising some 30 contributions, experts from around the world present and discuss recent advances related to seizure prediction in epilepsy. The book covers an extraordinarily broad spectrum, starting from modeling epilepsy in single cells or networks of a few cells to precisely-tailored seizure prediction techniques as applied to human data. This unique overview of our current level of knowledge and future perspectives provides theoreticians as well as practitioners, newcomers and experts with an up-to-date survey of developments in this important field of research.
Methods in Brain Connectivity Inference through Multivariate Time Series Analysis
Interest in brain connectivity inference has become ubiquitous and is now increasingly adopted in experimental investigations of clinical, behavioral, and experimental neurosciences. Methods in Brain Connectivity Inference through Multivariate Time Series Analysis gathers the contributions of leading international authors who discuss different time series analysis approaches, providing a thorough survey of information on how brain areas effectively interact. Incorporating multidisciplinary work in applied mathematics, statistics, and animal and human experiments at the forefront of the field, the book addresses the use of time series data in brain connectivity interference studies. Contribut...
Exploratory Causal Analysis with Time Series Data
Many scientific disciplines rely on observational data of systems for which it is difficult (or impossible) to implement controlled experiments. Data analysis techniques are required for identifying causal information and relationships directly from such observational data. This need has led to the development of many different time series causality approaches and tools including transfer entropy, convergent cross-mapping (CCM), and Granger causality statistics. A practicing analyst can explore the literature to find many proposals for identifying drivers and causal connections in time series data sets. Exploratory causal analysis (ECA) provides a framework for exploring potential causal str...
Research Anthology on Environmental and Societal Impacts of Climate Change
Climate change is an issue that has been generating a significant amount of discussion, research, and debate in recent years. Climate change continues to evolve at a rapid rate and continues to have a wide array of effects on everything from temperature to plant life. Beyond the negative environmental impacts, climate change is also proving to be a detriment to society with increasingly violent natural disasters and human health effects. It is essential to stay up to date on the latest in emerging research within this field as it continues to develop. The Research Anthology on Environmental and Societal Impacts of Climate Change discusses the varied effects of climate change throughout all a...
Handbook of Research on Global Environmental Changes and Human Health
The faster climate change affects the globe, the faster individuals will see the negative consequences, which include the decline of general human health. Comprehension of all climate change-related etiologies is essential to understanding the importance of global environmental stability. The Handbook of Research on Global Environmental Changes and Human Health is a collection of innovative research to manage the ensuing and numerous climate and anthropogenic threats to human health. While highlighting topics including government policy, human security, and population sensitivity, this book is ideally designed for environmentalists, policymakers, sociologists, physio pathologists, epidemiologists, and students seeking current research on reducing population sensitivity in terms of health related to the different climatic risks in the changing world.
Statistical Physics
The application of statistical methods to physics is essential. This unique book on statistical physics offers an advanced approach with numerous applications to the modern problems students are confronted with. Therefore the text contains more concepts and methods in statistics than the student would need for statistical mechanics alone. Methods from mathematical statistics and stochastics for the analysis of data are discussed as well. The book is divided into two parts, focusing first on the modeling of statistical systems and then on the analysis of these systems. Problems with hints for solution help the students to deepen their knowledge. The third edition has been updated and enlarged with new sections deepening the knowledge about data analysis. Moreover, a customized set of problems with solutions is accessible on the Web at extras.springer.com.
Merge in the Mind-Brain
Cover -- Title -- Copyright -- Contents -- Original Publication Details -- Introduction -- Part I Merge in the Mind -- 1 Merge and Bare Phrase Structure -- 2 Merge and (A)symmetry -- 3 Generalized Search and Cyclic Derivation by Phase: A Preliminary Study -- 4 Merge, Labeling, and Projection -- 5 A Note on Weak vs. Strong Generation in Human Language -- 6 0-Search and 0-Merge -- Part II Merge in the Brain -- 7 The Cortical Dynamics in Building Syntactic Structures of Sentences: An MEG Study in a Minimal-Pair Paradigm -- 8 Syntactic Computation in the Human Brain: The Degree of Merger as a Key Factor -- 9 Computational Principles of Syntax in the Regions Specialized for Language: Integrating Theoretical Linguistics and Functional Neuroimaging -- Bibliography -- Author Index -- Subject Index
Mathematical Methods in Time Series Analysis and Digital Image Processing
This coherent and articulate volume summarizes work carried out in the field of theoretical signal and image processing. It focuses on non-linear and non-parametric models for time series as well as on adaptive methods in image processing. The aim of this volume is to bring together research directions in theoretical signal and imaging processing developed rather independently in electrical engineering, theoretical physics, mathematics and the computer sciences.
