Real Time Multi Chip Neural Network For Cognitive Systems

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Real Time Multi Chip Neural Network For Cognitive Systems

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Author : Amir Zjajo
language : en
Publisher: CRC Press
Release Date : 2022-09-01

Real Time Multi Chip Neural Network For Cognitive Systems written by Amir Zjajo and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-01 with Science categories.

Simulation of brain neurons in real-time using biophysically-meaningful models is a pre-requisite for comprehensive understanding of how neurons process information and communicate with each other, in effect efficiently complementing in-vivo experiments. In spiking neural networks (SNNs), propagated information is not just encoded by the firing rate of each neuron in the network, as in artificial neural networks (ANNs), but, in addition, by amplitude, spike-train patterns, and the transfer rate. The high level of realism of SNNs and more significant computational and analytic capabilities in comparison with ANNs, however, limit the size of the realized networks. Consequently, the main challenge in building complex and biophysically-accurate SNNs is largely posed by the high computational and data transfer demands.Real-Time Multi-Chip Neural Network for Cognitive Systems presents novel real-time, reconfigurable, multi-chip SNN system architecture based on localized communication, which effectively reduces the communication cost to a linear growth. The system use double floating-point arithmetic for the most biologically accurate cell behavior simulation, and is flexible enough to offer an easy implementation of various neuron network topologies, cell communication schemes, as well as models and kinds of cells. The system offers a high run-time configurability, which reduces the need for resynthesizing the system. In addition, the simulator features configurable on- and off-chip communication latencies as well as neuron calculation latencies. All parts of the system are generated automatically based on the neuron interconnection scheme in use. The simulator allows exploration of different system configurations, e.g. the interconnection scheme between the neurons, the intracellular concentration of different chemical compounds (ions), which affect how action potentials are initiated and propagate.

Real Time Multi Chip Neural Network For Cognitive Systems

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Author : Amir Zjajo
language : en
Publisher:
Release Date : 2024-10-21

Real Time Multi Chip Neural Network For Cognitive Systems written by Amir Zjajo and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-21 with Science categories.

Real-Time Multi-Chip Neural Network for Cognitive Systems presents novel real-time, reconfigurable, multi-chip SNN system architecture based on localized communication, which effectively reduces the communication cost to a linear growth.

Toward Replacement Parts For The Brain

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Author : Theodore W. Berger
language : en
Publisher: MIT Press
Release Date : 2005

Toward Replacement Parts For The Brain written by Theodore W. Berger and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with Medical categories.

The latest advances in research on intracranial implantation of hardware models of neural circuitry.

Memristors For Neuromorphic Circuits And Artificial Intelligence Applications

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Author : Jordi Suñé
language : en
Publisher: MDPI
Release Date : 2020-04-09

Memristors For Neuromorphic Circuits And Artificial Intelligence Applications written by Jordi Suñé and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-09 with Technology & Engineering categories.

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.

Synaptic Plasticity For Neuromorphic Systems

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Author : Christian Mayr
language : en
Publisher: Frontiers Media SA
Release Date : 2016-06-26

Synaptic Plasticity For Neuromorphic Systems written by Christian Mayr and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-06-26 with Neurosciences. Biological psychiatry. Neuropsychiatry categories.

One of the most striking properties of biological systems is their ability to learn and adapt to ever changing environmental conditions, tasks and stimuli. It emerges from a number of different forms of plasticity, that change the properties of the computing substrate, mainly acting on the modification of the strength of synaptic connections that gate the flow of information across neurons. Plasticity is an essential ingredient for building artificial autonomous cognitive agents that can learn to reliably and meaningfully interact with the real world. For this reason, the neuromorphic community at large has put substantial effort in the design of different forms of plasticity and in putting them to practical use. These plasticity forms comprise, among others, Short Term Depression and Facilitation, Homeostasis, Spike Frequency Adaptation and diverse forms of Hebbian learning (e.g. Spike Timing Dependent Plasticity). This special research topic collects the most advanced developments in the design of the diverse forms of plasticity, from the single circuit to the system level, as well as their exploitation in the implementation of cognitive systems.

World Congress On Neural Networks

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Author : Paul Werbos
language : en
Publisher: Routledge
Release Date : 2021-09-09

World Congress On Neural Networks written by Paul Werbos and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-09 with Psychology categories.

Centered around 20 major topic areas of both theoretical and practical importance, the World Congress on Neural Networks provides its registrants -- from a diverse background encompassing industry, academia, and government -- with the latest research and applications in the neural network field.

Toward Robotic Socially Believable Behaving Systems Volume I

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Author : Anna Esposito
language : en
Publisher: Springer
Release Date : 2016-03-21

Toward Robotic Socially Believable Behaving Systems Volume I written by Anna Esposito and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-03-21 with Technology & Engineering categories.

This volume is a collection of research studies on the modeling of emotions in complex autonomous systems. Several experts in the field are reporting their efforts and reviewing the literature in order to shed lights on how the processes of coding and decoding emotional states took place in humans, which are the physiological, physical, and psychological variables involved, invent new mathematical models and algorithms to describe them, and motivate these investigations in the light of observable societal changes and needs, such as the aging population and the cost of health care services. The consequences are the implementation of emotionally and socially believable machines, acting as helpers into domestic spheres, where emotions drive behaviors and actions. The contents of the book are highly multidisciplinary since the modeling of emotions in robotic socially believable systems requires a holistic perspective on topics coming from different research domains such as computer science, engineering, sociology, psychology, linguistic, and information communication. The book is of interest both to experts and students since last research works on a so complex multidisciplinary topic are described in a neat and didactical scientific language.

Cognitive Systems And Signal Processing

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Author : Fuchun Sun
language : en
Publisher: Springer Nature
Release Date : 2021-05-04

Cognitive Systems And Signal Processing written by Fuchun Sun and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-04 with Computers categories.

This book constitutes the refereed post-conference proceedings of the 5th International Conference on Cognitive Systems and Signal Processing, ICCSIP 2020, held in Zhuhai, China, in December 2020. The 59 revised papers presented were carefully reviewed and selected from 120 submissions. The papers are organized in topical sections on algorithm; application; manipulation; bioinformatics; vision; and autonomous vehicles.

Big Data Analytics For Cloud Iot And Cognitive Computing

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Author : Kai Hwang
language : en
Publisher: John Wiley & Sons
Release Date : 2017-08-14

Big Data Analytics For Cloud Iot And Cognitive Computing written by Kai Hwang and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-08-14 with Computers categories.

The definitive guide to successfully integrating social, mobile, Big-Data analytics, cloud and IoT principles and technologies The main goal of this book is to spur the development of effective big-data computing operations on smart clouds that are fully supported by IoT sensing, machine learning and analytics systems. To that end, the authors draw upon their original research and proven track record in the field to describe a practical approach integrating big-data theories, cloud design principles, Internet of Things (IoT) sensing, machine learning, data analytics and Hadoop and Spark programming. Part 1 focuses on data science, the roles of clouds and IoT devices and frameworks for big-data computing. Big data analytics and cognitive machine learning, as well as cloud architecture, IoT and cognitive systems are explored, and mobile cloud-IoT-interaction frameworks are illustrated with concrete system design examples. Part 2 is devoted to the principles of and algorithms for machine learning, data analytics and deep learning in big data applications. Part 3 concentrates on cloud programming software libraries from MapReduce to Hadoop, Spark and TensorFlow and describes business, educational, healthcare and social media applications for those tools. The first book describing a practical approach to integrating social, mobile, analytics, cloud and IoT (SMACT) principles and technologies Covers theory and computing techniques and technologies, making it suitable for use in both computer science and electrical engineering programs Offers an extremely well-informed vision of future intelligent and cognitive computing environments integrating SMACT technologies Fully illustrated throughout with examples, figures and approximately 150 problems to support and reinforce learning Features a companion website with an instructor manual and PowerPoint slides www.wiley.com/go/hwangIOT Big-Data Analytics for Cloud, IoT and Cognitive Computing satisfies the demand among university faculty and students for cutting-edge information on emerging intelligent and cognitive computing systems and technologies. Professionals working in data science, cloud computing and IoT applications will also find this book to be an extremely useful working resource.

Synaptic Circuits And Functions In Bio Inspired Integrated Architectures

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Author : Ole Richter
language : en
Publisher: University of Groningen
Release Date : 2024-10-15

Synaptic Circuits And Functions In Bio Inspired Integrated Architectures written by Ole Richter and has been published by University of Groningen this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-15 with Technology & Engineering categories.

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.