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Accessible for engineers and physicists alike, this high-level work on this hot topic in medical physics covers the issue from principles of neuroscience to in-vivo use. Backed by extensive data tables and software samples on the Web.

Produktbeschreibung
Accessible for engineers and physicists alike, this high-level work on this hot topic in medical physics covers the issue from principles of neuroscience to in-vivo use. Backed by extensive data tables and software samples on the Web.

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Autorenporträt
Ranu Jung holds the Wallace H. Coulter Eminent Scholars Chair in Biomedical Engineering at Florida International University, USA where she is Professor and Chair of the Biomedical Engineering Department. She joined Florida International in 2011 from Arizona State University where she was founding co-director of the Center for Adaptive Neural Systems. She has also co-founded Advensys LLC, a small business R&D company and previously was President of the Organization for Computational Neurosciences, Inc. a non-profit that serves a global community of computational neuroscientists. Jung received her first degree in Electronics & Communication Engineering from National Institute of Technology-Warangal, India and her Masters and Doctorate degrees in Biomedical Engineering from Case Western Reserve University, USA. She is actively engaged in the development of neurotechnology that is inspired by biology, is adaptive and could be used to promote adaptation in the nervous system to overcome neurological disability or trauma.
Inhaltsangabe
Merging Technology with Biology
Principles of Computational Neuroscience
Neuromorphic Electronic Design
Principles of Neural Signal Processing
Dynamic Clamp in Biomimetic and Biohybrid Living- Hardware Systems
Biohybrid Circuits: Nanotransducers Linking Cells and Neural Electrodes
Hybrid Systems Analysis: Real- time Systems for Design and Prototyping of Neural Interfaces and Prostheses
Biomimetic Adaptive Control Algorithms
Neuromorphic Hardware for Control
Biohybrid Systems for Neurocardiology
Bioelectronic Sensing of Insulin Demand