Spinnaker A Spiking Neural Network Architecture
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Author | : Steve Furber |
Publisher | : NowOpen |
Total Pages | : 352 |
Release | : 2020-03-15 |
Genre | : |
ISBN | : 9781680836523 |
This books tells the story of the origins of the world's largest neuromorphic computing platform, its development and its deployment, and the immense software development effort that has gone into making it openly available and accessible to researchers and students the world over
Author | : Alessandro E.P. Villa |
Publisher | : Springer |
Total Pages | : 585 |
Release | : 2016-08-26 |
Genre | : Computers |
ISBN | : 3319447785 |
The two volume set, LNCS 9886 + 9887, constitutes the proceedings of the 25th International Conference on Artificial Neural Networks, ICANN 2016, held in Barcelona, Spain, in September 2016. The 121 full papers included in this volume were carefully reviewed and selected from 227 submissions. They were organized in topical sections named: from neurons to networks; networks and dynamics; higher nervous functions; neuronal hardware; learning foundations; deep learning; classifications and forecasting; and recognition and navigation. There are 47 short paper abstracts that are included in the back matter of the volume.
Author | : Furber |
Publisher | : Pearson Education India |
Total Pages | : 432 |
Release | : 2001-09 |
Genre | : |
ISBN | : 9788131708408 |
Author | : Paul R. Prucnal |
Publisher | : CRC Press |
Total Pages | : 412 |
Release | : 2017-05-08 |
Genre | : Science |
ISBN | : 1498725244 |
This book sets out to build bridges between the domains of photonic device physics and neural networks, providing a comprehensive overview of the emerging field of "neuromorphic photonics." It includes a thorough discussion of evolution of neuromorphic photonics from the advent of fiber-optic neurons to today’s state-of-the-art integrated laser neurons, which are a current focus of international research. Neuromorphic Photonics explores candidate interconnection architectures and devices for integrated neuromorphic networks, along with key functionality such as learning. It is written at a level accessible to graduate students, while also intending to serve as a comprehensive reference for experts in the field.
Author | : A. Ravishankar Rao |
Publisher | : Frontiers Media SA |
Total Pages | : 266 |
Release | : 2016-03-17 |
Genre | : Neurosciences. Biological psychiatry. Neuropsychiatry |
ISBN | : 288919762X |
The amount of data being produced by neuroscientists is increasing rapidly, driven by advances in neuroimaging and recording techniques spanning multiple scales of resolution. The availability of such data poses significant challenges for their processing and interpretation. To gain a deeper understanding of the surrounding issues, the Editors of this e-Book reached out to an interdisciplinary community, and formed the Cortical Networks Working Group, and the genesis of this e-Book thus began with the formation of this Working Group, which was supported by the National Institute for Mathematical and Biological Synthesis in the USA. The Group consisted of scientists from neuroscience, physics, psychology and computer science, and meetings were held in person. (A detailed list of the group members is presented in the Editorial that follows.) At the time we started, in 2010, the term “big data” was hardly in existence, though the volume of data we were handling would certainly have qualified. Furthermore, there was significant interest in harnessing the power of supercomputers to perform large scale neuronal simulations, and in creating specialized hardware to mimic neural function. We realized that the various disciplines represented in our Group could and should work together to accelerate progress in Neuroscience. We searched for common threads that could define the foundation for an integrated approach to solve important problems in the field. We adopted a network-centric perspective to address these challenges, as the data are derived from structures that are themselves network-like. We proposed three inter-twined threads, consisting of measurement of neural activity, analysis of network structures deduced from this activity, and modeling of network function, leading to theoretical insights. This approach formed the foundation of our initial call for papers. When we issued the call for papers, we were not sure how many papers would fall into each of these threads. We were pleased that we found significant interest in each thread, and the number of submissions exceeded our expectations. This is an indication that the field of neuroscience is ripe for the type of integration and interchange that we had anticipated. We first published a special topics issue after we received a sufficient number of submissions. This is now being converted to an e-book to strengthen the coherence of its contributions. One of the strong themes emerging in this e-book is that network-based measures capture better the dynamics of brain processes, and provide features with greater discriminative power than point-based measures. Another theme is the importance of network oscillations and synchrony. Current research is shedding light on the principles that govern the establishment and maintenance of network oscillation states. These principles could explain why there is impaired synchronization between different brain areas in schizophrenics and Parkinson’s patients. Such research could ultimately provide the foundation for an understanding of other psychiatric and neurodegenerative conditions. The chapters in this book cover these three main threads related to cortical networks. Some authors have combined two or more threads within a single chapter. We expect the availability of related work appearing in a single e-book to help our readers see the connection between different research efforts, and spur further insights and research.
Author | : Chris Eliasmith |
Publisher | : MIT Press |
Total Pages | : 384 |
Release | : 2003 |
Genre | : Computers |
ISBN | : 9780262550604 |
A synthesis of current approaches to adapting engineering tools to the study of neurobiological systems.
Author | : Guoqi Li |
Publisher | : Frontiers Media SA |
Total Pages | : 234 |
Release | : 2020-06-05 |
Genre | : |
ISBN | : 2889637670 |
Author | : Stefan Wermter |
Publisher | : Springer |
Total Pages | : 874 |
Release | : 2014-08-18 |
Genre | : Computers |
ISBN | : 3319111795 |
The book constitutes the proceedings of the 24th International Conference on Artificial Neural Networks, ICANN 2014, held in Hamburg, Germany, in September 2014. The 107 papers included in the proceedings were carefully reviewed and selected from 173 submissions. The focus of the papers is on following topics: recurrent networks; competitive learning and self-organisation; clustering and classification; trees and graphs; human-machine interaction; deep networks; theory; reinforcement learning and action; vision; supervised learning; dynamical models and time series; neuroscience; and applications.
Author | : Wulfram Gerstner |
Publisher | : Cambridge University Press |
Total Pages | : 498 |
Release | : 2002-08-15 |
Genre | : Computers |
ISBN | : 9780521890793 |
Neurons in the brain communicate by short electrical pulses, the so-called action potentials or spikes. How can we understand the process of spike generation? How can we understand information transmission by neurons? What happens if thousands of neurons are coupled together in a seemingly random network? How does the network connectivity determine the activity patterns? And, vice versa, how does the spike activity influence the connectivity pattern? These questions are addressed in this 2002 introduction to spiking neurons aimed at those taking courses in computational neuroscience, theoretical biology, biophysics, or neural networks. The approach will suit students of physics, mathematics, or computer science; it will also be useful for biologists who are interested in mathematical modelling. The text is enhanced by many worked examples and illustrations. There are no mathematical prerequisites beyond what the audience would meet as undergraduates: more advanced techniques are introduced in an elementary, concrete fashion when needed.
Author | : Harish Garg |
Publisher | : Elsevier |
Total Pages | : 289 |
Release | : 2024-11-25 |
Genre | : Computers |
ISBN | : 0443214824 |
Primer to Neuromorphic Computing highlights critical and ongoing research into the diverse applications of neuromorphic computing. It includes an overview of primary scientific concepts for the research topic of neuromorphic computing, such as neurons as computational units, artificial intelligence, machine learning, and neuromorphic models. It also discusses the fundamental design method and organization of neuromorphic architecture. Hardware for neuromorphic systems can be developed by exploiting the magnetic properties of different materials. These systems are more energy efficient and enable faster computation . Magnetic tunnel junctions and magnetic textures can be employed to act as neurons and synapses. Neuromorphic systems have general intelligence like humans as they can apply knowledge gained in one domain to other domains. - Discusses potential neuromorphic applications in computing - Presents current trends and models in neuromorphic computing and neural network hardware architectures - Shows the development of novel devices and hardware to enable neuromorphic computing - Offers information about computation and learning principles for neuromorphic systems - Provides information about Neuromorphic implementations of neurobiological learning algorithms - Discusses biologically inspired neuromorphic systems and devices (including adaptive bio interfacing and hybrid systems consisting of living matter and synthetic matter)