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Neuromorphic Systems Engineering
Neuromorphic Systems Engineering: Neural Networks in Silicon emphasizes three important aspects of this exciting new research field. The term neuromorphic expresses relations to computational models found in biological neural systems, which are used as inspiration for building large electronic systems in silicon. By adequate engineering, these silicon systems are made useful to mankind. Neuromorphic Systems Engineering: Neural Networks in Silicon provides the reader with a snapshot of neuromorphic engineering today. It is organized into five parts viewing state-of-the-art developments within neuromorphic engineering from different perspectives. Neuromorphic Systems Engineering: Neural Networ...
Neural Engineering
This third edition overviews the essential contemporary topics of neuroengineering, from basic principles to the state-of-the-art, and is written by leading scholars in the field. The book covers neural bioelectrical measurements and sensors, EEG signal processing, brain-computer interfaces, implantable and transcranial neuromodulation, peripheral neural interfacing, neuroimaging, neural modelling, neural circuits and system identification, retinal bioengineering and prosthetics, and neural tissue engineering. Each chapter is followed by homework questions intended for classroom use. This is an ideal textbook for students at the graduate and advanced undergraduate level as well as academics,...
Learning on Silicon
Learning on Silicon combines models of adaptive information processing in the brain with advances in microelectronics technology and circuit design. The premise is to construct integrated systems not only loaded with sufficient computational power to handle demanding signal processing tasks in sensory perception and pattern recognition, but also capable of operating autonomously and robustly in unpredictable environments through mechanisms of adaptation and learning. This edited volume covers the spectrum of Learning on Silicon in five parts: adaptive sensory systems, neuromorphic learning, learning architectures, learning dynamics, and learning systems. The 18 chapters are documented with examples of fabricated systems, experimental results from silicon, and integrated applications ranging from adaptive optics to biomedical instrumentation. As the first comprehensive treatment on the subject, Learning on Silicon serves as a reference for beginners and experienced researchers alike. It provides excellent material for an advanced course, and a source of inspiration for continued research towards building intelligent adaptive machines.
Implantable Sensors and Systems
Implantable sensing, whether used for transient or long-term monitoring of in vivo physiological, bio-electrical, bio-chemical and metabolic changes, is a rapidly advancing field of research and development. Underpinned by increasingly small, smart and energy efficient designs, they become an integral part of surgical prostheses or implants for both acute and chronic conditions, supporting optimised, context aware sensing, feedback, or stimulation with due consideration of system level impact. From sensor design, fabrication, on-node processing with application specific integrated circuits, to power optimisation, wireless data paths and security, this book provides a detailed explanation of ...
Pattern Recognition with Support Vector Machines
This book constitutes the refereed proceedings of the First International Workshop on Pattern Recognition with Support Vector Machines, SVM 2002, held in Niagara Falls, Canada in August 2002.The 16 revised full papers and 14 poster papers presented together with two invited contributions were carefully reviewed and selected from 57 full paper submissions. The papers presented span the whole range of topics in pattern recognition with support vector machines from computational theories to implementations and applications.
Fundamentals of Organic Neuromorphic Systems
This book describes the essential requirements for the realization of neuromorphic systems, where memristive devices play a key role. A comprehensive description to organic memristive devices, including working principles and models of the function, preparation methods, properties and different applications is presented. A comparative analysis of organic and inorganic systems is given. The author discusses all aspects of current research in organic memristive devices: fabrication techniques, properties, synapse mimicking circuits, and neuromorphic systems (including perceptrons), etc. Describes requirements of electronic circuits and systems to be considered as neuromorphic systems; Provides a single-source reference to the state-of-the-art in memristive devices as key elements of neuromorphic systems; Provides a comparative analysis of advantages and drawbacks between organic and inorganic devices and systems; Includes a systematic overview of organic memristive devices, including fabrication methods, properties, synapse mimicking circuits, and neuromorphic systems; Discusses a variety of unconventional applications, based on bio-inspired circuits and neuromorphic systems.
Neural Computation, Neural Devices, and Neural Prosthesis
In the past decades, interdisciplinary investigations overlapping biology, medicine, information science, and engineering have formed a very exciting and active field that attracts scientists, medical doctors, and engineers with knowledge in different domains. A few examples of such investigations include neural prosthetic implants that aim to improve the quality of life for patients suffering from neurologic disease and injury; brain machine interfaces that sense, analyze, and translate electrical signals from the brain to build closed-loop, biofeedback systems; and fundamental studies of intelligence, cognitive functions, and psychological behaviors correlated to their neurological basis. ...
Advanced Memory Technology
Advanced memory technologies are impacting the information era, representing a vibrant research area of huge interest in the electronics industry. The demand for data storage, computing performance and energy efficiency is increasing exponentially and will exceed the capabilities of current information technologies. Alternatives to traditional silicon technology and novel memory principles are expected to meet the need of modern data-intensive applications such as “big data” and artificial intelligence (AI). Functional materials or methodologies may find a key role in building novel, high speed and low power consumption computing and data storage systems. This book covers functional mate...
Wireless Power Transfer and Data Communication for Neural Implants
This book presents new circuits and systems for implantable biomedical applications targeting neural recording. The authors describe a system design adapted to conform to the requirements of an epilepsy monitoring system. Throughout the book, these requirements are reflected in terms of implant size, power consumption, and data rate. In addition to theoretical background which explains the relevant technical challenges, the authors provide practical, step-by-step solutions to these problems. Readers will gain understanding of the numerical values in such a system, enabling projections for feasibility of new projects.
Smart Adaptive Systems on Silicon
Intelligent/smart systems have become common practice in many engineering applications. On the other hand, current low cost standard CMOS technology (and future foreseeable developments) makes available enormous potentialities. The next breakthrough will be the design and development of "smart adaptive systems on silicon" i.e. very power and highly size efficient complete systems (i.e. sensing, computing and "actuating" actions) with intelligence on board on a single silicon die. Smart adaptive systems on silicon will be able to "adapt" autonomously to the changing environment and will be able to implement "intelligent" behaviour and both perceptual and cognitive tasks. At last, they will co...
