Download Free From Synapse To Circuit Book in PDF and EPUB Free Download. You can read online From Synapse To Circuit and write the review.

Based upon the most advanced human-made technology on this planet, CMOS integrated circuit technology, this dissertation examines the design of hardware components and systems to establish a technological foundation for the application of future breakthroughs in the intersection of AI and neuroscience. Humans have long imagined machines, robots, and computers that learn and display intelligence akin to animals and themselves. To advance the development of these machines, specialised research in custom-built hardware designed for specific types of computation, which mirrors the structure of powerful biological nervous systems, is especially important. This dissertation is driven by the quest to harness biological and artificial neural principles to enhance the efficiency, adaptability, and intelligence of electronic neurosynaptic and neuromorphic hardware systems. It investigates the hardware design of bio-inspired neural components and their integration into more extensive scale and efficient chip architectures suitable for edge processing and near-sensor environments. Exploring all steps to the creation of a custom chip, this work selectively surveys and advances the state-of-the-art in bio-inspired mixed-signal subthreshold integrated design for neurosynaptic systems in a practical fashion. Further, it presents a novel asynchronous digital convolutional neuronal network processing pipeline integrated with a vision sensor for smart sensing. In conclusion, it sets forth a series of open challenges and future directions for the field, emphasizing the need for a robust, future-proof base for bio-inspired design and the potential of asynchronous stream processor architectures.
Intercellular communication is part of a complex system of communication that governs basic cellular activities and coordinates cell actions. The ability of cells to perceive and correctly respond to their environment is the basis of growth and development, tissue repair, and immunity as well as normal tissue homeostasis. Errors in cellular information processing are responsible for diseases such as cancer, autoimmunity, diabetes, and neurological and psychiatric disorders. There is substantial drug development concentrating on this and intercellular communication is the basis of much of neuropharmacology. By understanding cell signaling, diseases may be treated effectively and, theoretically, artificial tissues may be yielded. Neurotransmitters/receptors, synaptic structure and organization, gap junctions, neurotrophic factors and neuropeptides are all explored in this volume, as are the ways in which signaling controls neuroendocrinology, neuroimmunology and neuropharmacology. Intercellular Communication in the Nervous System provides a valuable desk reference for all scientists who consider signaling. - Chapters offer impressive scope with topics addressing neurotransmitters/receptors, synaptic structure and organization, neuropeptides, gap junctions, neuropharmacology and more - Richly illustrated in full color with over 200 figures - Contributors represent the most outstanding scholarship in the field, with each chapter providing fully vetted and reliable expert knowledge
A unique and fascinating scientific detective story that traces the origins as well as the complex mechanisms of human self-consciousness.
This book constitutes the refereed proceedings of the 21st International Symposium on VLSI Design and Test, VDAT 2017, held in Roorkee, India, in June/July 2017. The 48 full papers presented together with 27 short papers were carefully reviewed and selected from 246 submissions. The papers were organized in topical sections named: digital design; analog/mixed signal; VLSI testing; devices and technology; VLSI architectures; emerging technologies and memory; system design; low power design and test; RF circuits; architecture and CAD; and design verification.
Integrated circuits and microsystems play a vital role in a variety of biomedical applications including life-saving/changing miniature medical devices, surgical procedures with less invasiveness and morbidity, low-cost preventive healthcare solutions for daily life, solutions for effective chronic disease management, point-of-care diagnosis for early disease detection, high-throughput bio sequencing and drug screening and groundbreaking brain-machine interfaces based on a deep understanding of human intelligence. In response to such strong demands for biomedical circuits and systems, a considerable amount of effort has been devoted to the research and development in this area, both by industry and academia, over recent years. This book, which belongs to the “Tutorials in Circuits and Systems” series, provides readers with an overview of new developments in the field of biomedical circuits and systems. It covers basic information about system-level and circuit-level requirements, operation principles, key factors of considerations, and design/implementation techniques, as well as recent advances in integrated circuits and microsystems for emerging biomedical applications. Technical topics covered in this book include: Biomedical Microsystem Integration; Biomedical Sensor Interface Circuits; Neural Stimulation Circuits; Wireless Power Transfer Circuits for Biomedical Microsystems; Artificial Intelligence Processors for Biomedical Circuits and Systems; Neuro-Inspired Computing and Neuromorphic Processors for Biomedical Circuits and Systems. This book is ideal for personnel in medical devices and biomedical engineering industries as well as academic staff and postgraduate/research students in biomedical circuits and systems.
Artificial Intelligence (AI) has found many applications in the past decade due to the ever increasing computing power. Artificial Neural Networks are inspired in the brain structure and consist in the interconnection of artificial neurons through artificial synapses. Training these systems requires huge amounts of data and, after the network is trained, it can recognize unforeseen data and provide useful information. The so-called Spiking Neural Networks behave similarly to how the brain functions and are very energy efficient. Up to this moment, both spiking and conventional neural networks have been implemented in software programs running on conventional computing units. However, this approach requires high computing power, a large physical space and is energy inefficient. Thus, there is an increasing interest in developing AI tools directly implemented in hardware. The first hardware demonstrations have been based on CMOS circuits for neurons and specific communication protocols for synapses. However, to further increase training speed and energy efficiency while decreasing system size, the combination of CMOS neurons with memristor synapses is being explored. The memristor is a resistor with memory which behaves similarly to biological synapses. This book explores the state-of-the-art of neuromorphic circuits implementing neural networks with memristors for AI applications.
Papers presented at the 2003 Neural Information Processing Conference by leading physicists, neuroscientists, mathematicians, statisticians, and computer scientists. The annual Neural Information Processing (NIPS) conference is the flagship meeting on neural computation. It draws a diverse group of attendees -- physicists, neuroscientists, mathematicians, statisticians, and computer scientists. The presentations are interdisciplinary, with contributions in algorithms, learning theory, cognitive science, neuroscience, brain imaging, vision, speech and signal processing, reinforcement learning and control, emerging technologies, and applications. Only thirty percent of the papers submitted are accepted for presentation at NIPS, so the quality is exceptionally high. This volume contains all the papers presented at the 2003 conference.
Mixed-Signal Circuits offers a thoroughly modern treatment of integrated circuit design in the context of mixed-signal applications. Featuring chapters authored by leading experts from industry and academia, this book: Discusses signal integrity and large-scale simulation, verification, and testing Demonstrates advanced design techniques that enable digital circuits and sensitive analog circuits to coexist without any compromise Describes the process technology needed to address the performance challenges associated with developing complex mixed-signal circuits Deals with modeling topics, such as reliability, variability, and crosstalk, that define pre-silicon design methodology and trends, and are the focus of companies involved in wireless applications Develops methods to move analog into the digital domain quickly, minimizing and eliminating common trade-offs between performance, power consumption, simulation time, verification, size, and cost Details approaches for very low-power performances, high-speed interfaces, phase-locked loops (PLLs), voltage-controlled oscillators (VCOs), analog-to-digital converters (ADCs), and biomedical filters Delineates the respective parts of a full system-on-chip (SoC), from the digital parts to the baseband blocks, radio frequency (RF) circuitries, electrostatic-discharge (ESD) structures, and built-in self-test (BIST) architectures Mixed-Signal Circuits explores exciting opportunities in wireless communications and beyond. The book is a must for anyone involved in mixed-signal circuit design for future technologies.
This book constitutes the refereed proceedings of the 16th International Conference on Engineering Applications of Neural Networks, EANN 2015, held in Rhodes, Greece, in September 2015. The 36 revised full papers presented together with the abstracts of three invited talks and two tutorials were carefully reviewed and selected from 84 submissions. The papers are organized in topical sections on industrial-engineering applications of ANN; bioinformatics; intelligent medical modeling; life-earth sciences intelligent modeling; learning-algorithms; intelligent telecommunications modeling; fuzzy modeling; robotics and control; smart cameras; pattern recognition-facial mapping; classification; financial intelligent modeling; echo state networks.
Hopping, climbing and swimming robots, nano-size neural networks, motorless walkers, slime mould and chemical brains - "Artificial Life Models in Hardware" offers unique designs and prototypes of life-like creatures in conventional hardware and hybrid bio-silicon systems. Ideas and implementations of living phenomena in non-living substrates cast a colourful picture of state-of-art advances in hardware models of artificial life.