Описание: Spiking neural networks (SNN) are biologically inspired computational models that represent and process information internally as trains of spikes. This monograph book presents the classical theory and applications of SNN, including original author’s contribution to the area. The book introduces for the first time not only deep learning and deep knowledge representation in the human brain and in brain-inspired SNN, but takes that further to develop new types of AI systems, called in the book brain-inspired AI (BI-AI). BI-AI systems are illustrated on: cognitive brain data, including EEG, fMRI and DTI; audio-visual data; brain-computer interfaces; personalized modelling in bio-neuroinformatics; multisensory streaming data modelling in finance, environment and ecology; data compression; neuromorphic hardware implementation. Future directions, such as the integration of multiple modalities, such as quantum-, molecular- and brain information processing, is presented in the last chapter. The book is a research book for postgraduate students, researchers and practitioners across wider areas, including computer and information sciences, engineering, applied mathematics, bio- and neurosciences.
Автор: Ata Mahjoubfar; Claire Lifan Chen; Bahram Jalali Название: Artificial Intelligence in Label-free Microscopy ISBN: 3319514474 ISBN-13(EAN): 9783319514475 Издательство: Springer Рейтинг: Цена: 16769.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book introduces time-stretch quantitative phase imaging (TS-QPI), a high-throughput label-free imaging flow cytometer developed for big data acquisition and analysis in phenotypic screening.
Автор: Sch?ning Название: Label-Free Biosensing ISBN: 3319752197 ISBN-13(EAN): 9783319752198 Издательство: Springer Рейтинг: Цена: 53106.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
This volume summarizes the state-of-the-art technologies, key advances and future trends in the field of label-free biosensing. It provides detailed insights into the different types of solid-state, label-free biosensors, their underlying transducer principles, advanced materials utilized, device-fabrication techniques and various applications. The book offers graduate students, academic researchers, and industry professionals a comprehensive source of information on all facets of label-free biosensing and the future trends in this flourishing field.
Highlights of the subjects covered include label-free biosensing with:
- semiconductor field-effect devices such as nanomaterial-modified capacitive electrolyte-insulator-semiconductor structures, silicon nanowire transistors, III-nitride semiconductor devices and light-addressable potentiometric sensors
- impedimetric biosensors using planar and 3D electrodes
- nanocavity and solid-state nanopore devices
- carbon nanotube and graphene/graphene oxide biosensors
- electrochemical biosensors using molecularly imprinted polymers
- biomimetic sensors based on acoustic signal transduction
- enzyme logic systems and digital biosensors based on the biocomputing concept
Описание: Spiking neural networks (SNN) are biologically inspired computational models that represent and process information internally as trains of spikes. This monograph book presents the classical theory and applications of SNN, including original author’s contribution to the area. The book introduces for the first time not only deep learning and deep knowledge representation in the human brain and in brain-inspired SNN, but takes that further to develop new types of AI systems, called in the book brain-inspired AI (BI-AI). BI-AI systems are illustrated on: cognitive brain data, including EEG, fMRI and DTI; audio-visual data; brain-computer interfaces; personalized modelling in bio-neuroinformatics; multisensory streaming data modelling in finance, environment and ecology; data compression; neuromorphic hardware implementation. Future directions, such as the integration of multiple modalities, such as quantum-, molecular- and brain information processing, is presented in the last chapter. The book is a research book for postgraduate students, researchers and practitioners across wider areas, including computer and information sciences, engineering, applied mathematics, bio- and neurosciences.
Автор: Michael J. Sch?ning; Arshak Poghossian Название: Label-Free Biosensing ISBN: 3030091732 ISBN-13(EAN): 9783030091736 Издательство: Springer Рейтинг: Цена: 53106.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This volume summarizes the state-of-the-art technologies, key advances and future trends in the field of label-free biosensing. It provides detailed insights into the different types of solid-state, label-free biosensors, their underlying transducer principles, advanced materials utilized, device-fabrication techniques and various applications. The book offers graduate students, academic researchers, and industry professionals a comprehensive source of information on all facets of label-free biosensing and the future trends in this flourishing field. Highlights of the subjects covered include label-free biosensing with:· semiconductor field-effect devices such as nanomaterial-modified capacitive electrolyte-insulator-semiconductor structures, silicon nanowire transistors, III-nitride semiconductor devices and light-addressable potentiometric sensors· impedimetric biosensors using planar and 3D electrodes· nanocavity and solid-state nanopore devices · carbon nanotube and graphene/graphene oxide biosensors· electrochemical biosensors using molecularly imprinted polymers· biomimetic sensors based on acoustic signal transduction· enzyme logic systems and digital biosensors based on the biocomputing concept· heat-transfer as a novel transducer principle· ultrasensitive surface plasmon resonance biosensors · magnetic biosensors and magnetic imaging devices
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