This book develops and details a rigorous, canonical modeling approach for analyzing spatio-temporal brain wave dynamics. The nonlinear, nonstationary behavior of brain wave measures and general uncertainty associated...
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ISBN:
(数字)9783031235290
ISBN:
(纸本)9783031235283;9783031235313
This book develops and details a rigorous, canonical modeling approach for analyzing spatio-temporal brain wave dynamics. The nonlinear, nonstationary behavior of brain wave measures and general uncertainty associated with the brain makes it difficult to apply modern system identification techniques to such systems. While there is a substantial amount of literature on the use of stationary analyses for brain waves, relatively less work has considered real-time estimation and imaging of brain waves from noninvasive measurements. This book addresses the issue of modeling and imaging brain waves and biomarkers generally, treating the nonlinear and nonstationary dynamics in near real-time. Using a modal state-space formulation leads to intuitive, physically significant models which are used for analysis and diagnosis.;provides a much-needed reference for practicing researchers in biomarker modeling leveraging the lens of engineering dynamics.
This book shows how mathematics, computer science and science can be usefully and seamlessly intertwined. It begins with a general model of cognitiveprocesses in a network of computational nodes, such as neurons, usi...
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ISBN:
(数字)9789812878717
ISBN:
(纸本)9789812878694;9789811357183
This book shows how mathematics, computer science and science can be usefully and seamlessly intertwined. It begins with a general model of cognitiveprocesses in a network of computational nodes, such as neurons, using a variety of tools from mathematics, computational science and neurobiology. It then moves on to solve the diffusion model from a low-level random walk point of view. It also demonstrates how this idea can be used in a new approach to solving the cable equation, in order to better understand the neural computation approximations. It introduces specialized data for emotional content, which allows a brain model to be built using MatLab tools, and also highlights a simple model of cognitive dysfunction.
This Handbook offers the first comprehensive reference guide to the interdisciplinary field of abductive cognition, providing readers with extensive information on the process of reasoning to hypotheses in humans, ani...
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ISBN:
(数字)9783031101359
ISBN:
(纸本)9783031101342
This Handbook offers the first comprehensive reference guide to the interdisciplinary field of abductive cognition, providing readers with extensive information on the process of reasoning to hypotheses in humans, animals, and in computational machines. It highlights the role of abduction in both theory practice: in generating and testing hypotheses and explanatory functions for various purposes and as an educational device. It merges logical, cognitive, epistemological and philosophical perspectives with more practical needs relating to the application of abduction across various disciplines and practices, such as in diagnosis, creative reasoning, scientific discovery, diagrammatic and ignorance-based cognition, and adversarial strategies. It also discusses the inferential role of models in hypothetical reasoning, abduction and creativity, including the process of development, implementation and manipulation for different scientific and technological purposes. Written by a group ofinternationally renowned experts in philosophy, logic, general epistemology, mathematics, cognitive, and computer science, as well as life sciences, engineering, architecture, and economics, the Handbook of Abductive Cognition offers a unique reference guide for readers approaching the process of reasoning to hypotheses from different perspectives and for various theoretical and practical purposes. Numerous diagrams, schemes and other visual representations are included to promote a better understanding of the relevant concepts and to make concepts highly accessible to an audience of scholars and students with different scientific backgrounds.
This handbook gathers together the state of the art on mathematicalmodels and algorithms for imaging and vision. Its emphasis lies on rigorous mathematical methods, which represent the optimal sol...
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ISBN:
(数字)9783030986612
ISBN:
(纸本)9783030986605
This handbook gathers together the state of the art on mathematicalmodels and algorithms for imaging and vision. Its emphasis lies on rigorous mathematical methods, which represent the optimal solutions to a class of imaging and vision problems, and on effective algorithms, which are necessary for the methods to be translated to practical use in various applications. Viewing discrete images as data sampled from functional surfaces enables the use of advanced tools from calculus, functions and calculus of variations, and nonlinear optimization, and provides the basis of high-resolution imaging through geometry and variational models. Besides, optimization naturally connects traditional model-driven approaches to the emerging data-driven approaches of machine and deep learning. No other framework can provide comparable accuracy and precision to imaging and vision.
Written by leading researchers in imaging and vision, the chapters in this handbook all start with gentle introductions, which make this work accessible to graduate students. For newcomers to the field, the book provides a comprehensive and fast-track introduction to the content, to save time and get on with tackling new and emerging challenges. For researchers, exposure to the state of the art of research works leads to an overall view of the entire field so as to guide new research directions and avoid pitfalls in moving the field forward and looking into the next decades of imaging and information services. This work can greatly benefit graduate students, researchers, and practitioners in imaging and vision; applied mathematicians; medical imagers; engineers; and computer scientists.
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