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Neuromorphic electronic engineering takes its inspiration from the functioning of nervous systems to build more power efficient electronic sensors and processors. Event-based neuromorphic systems are inspired by the brain's efficient data-driven communication design, which is key to its quick responses and remarkable capabilities.

The \"soft\" analytic tools that comprise the field of computational intelligence have matured to the extent that they can, often in powerful combination with one another, form the foundation for a variety of solutions suitable for use by domain experts without extensive programming experience. Computational Intelligence: Concepts to Implementations provides the conceptual and practical knowledge necessary to develop solutions of this kind. Focusing on evolutionary computation, neural networks, and fuzzy logic, the authors have constructed an approach to thinking about and working with computational intelligence that has, in their extensive experience, proved highly effective. Russ Eberhart and Yuhui Shi have succeeded in integrating various natural and engineering disciplines to establish Computational Intelligence. This is the first comprehensive textbook, including lots of practical examples. -Shun-ichi Amari, RIKEN Brain Science Institute, Japan This book is an excellent choice on its own, but, as in my case, will form the foundation for our advanced graduate courses in the CI disciplines. -James M. Keller, University of Missouri-Columbia The excellent new book by Eberhart and Shi asserts that computational intelligence rests on a foundation of evolutionary computation. This refreshing view has set the book apart from other books on computational intelligence. The book has an emphasis on practical applications and computational tools, which are very useful and important for further development of the computational intelligence field. -Xin Yao, The Centre of Excellence for Research in Computational Intelligence and Applications, Birmingham Moves clearly and efficiently from concepts and paradigms to algorithms and implementation techniques by focusing, in the early chapters, on the specific concepts and paradigms that inform the authors' methodologiesExplores a number of key themes, including self-organization, complex adaptive systems, and emergent computationDetails the metrics and analytical tools needed to assess the performance of computational intelligence toolsConcludes with a series of case studies that illustrate a wide range of successful applicationsPresents code examples in C and C++Provides, at the end of each chapter, review questions and exercises suitable for graduate students, as well as researchers and practitioners engaged in self-studyMakes available, on a companion website, a number of software implementations that can be adapted for real-world applications

\"Everything we and other animals do is caused by electrical signals in nerve cells, or neurons. Neurons are organized into circuits, like the electrical circuits that run electronic devices. This book explores how these circuits function to control behaviors. In some circuits, a single neuron acts like a dictator, gathering information from many sources, making decisions, and issuing commands to produce movements, such as fish and crayfish escape maneuvers. In other circuits, a large population of neurons collectively votes, with no single neuron dominating, mediating color perception, for example, and controlling eye and hand movements to objects of interest. Neural circuits control all behaviors, from the simple and automatic to the complex and deliberative. Some of the most critical circuits generate rhythmic outputs that make an animal breathe, chew, digest, walk, run, swim, or fly. These central nervous system circuits can churn out rhythmic signals on their own, like central government programs, but modify output to match demand, using feedback signals from moving body parts. To select the right behavior for each moment, nervous systems use sophisticated sensory surveillance. For example, owl circuits calculate the precise locations of sound sources to catch mice in the dark. Bats catch flying insects by emitting ultrasonic pulses and using specialized circuits to analyze the echoes, a form of sonar. Central nervous systems keep track of their own movement commands to update the surveillance circuits. Although some neural circuits are innate, others, such as those producing human speech and bird song, depend on learning, even in adulthood.\"-- Provided by publisher.

The series is devoted to the publication of high-level monographs which cover the whole spectrum of current nonlinear analysis and applications in various fields, such as optimization, control theory, systems theory, mechanics, engineering, and other sciences. One of its main objectives is to make available to the professional community expositions of results and foundations of methods that play an important role in both the theory and applications of nonlinear analysis. Contributions which are on the borderline of nonlinear analysis and related fields and which stimulate further research at the crossroads of these areas are particularly welcome. Please submit book proposals toJürgen Appell.

Olaf Sporns presents an overview of network approaches to neuroscience in which he explores the origins of brain complexity & the link between brain structure & function.

The biomedical sciences have recently undergone revolutionary change, due to the ability to digitize and store large data sets. In neuroscience, the data sources include measurements of neural activity measured using electrode arrays, EEG and MEG, brain imaging data from PET, fMRI, and optical imaging methods. Analysis, visualization, and management of these time series data sets is a growing field of research that has become increasingly important both for experimentalists and theorists interested in brain function. The first part of the book contains a set of chapters which provide non-technical conceptual background to the subject. Salient features include the adoption of an active perspective of the nervous system, an emphasis on function, and a brief survey of different theoretical accounts in neuroscience. The second part is the longest in the book, and contains a refresher course in mathematics and statistics leading up to time series analysis techniques. The third part contains applications of data analysis techniques to the range of data sources indicated above, and the fourth part contains special topics.