Physical neuromorphic computing and its industrial applications
Author: Toshiyuki Yamane
Publisher: Frontiers Media SA
Published: 2023-08-02
Total Pages: 163
ISBN-13: 2832531288
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Advances in Neuromorphic Memristor Science and Applications
Author: Robert Kozma
Publisher: Springer Science & Business Media
Published: 2012-06-28
Total Pages: 318
ISBN-13: 9400744919
DOWNLOAD EBOOKPhysical implementation of the memristor at industrial scale sparked the interest from various disciplines, ranging from physics, nanotechnology, electrical engineering, neuroscience, to intelligent robotics. As any promising new technology, it has raised hopes and questions; it is an extremely challenging task to live up to the high expectations and to devise revolutionary and feasible future applications for memristive devices. The possibility of gathering prominent scientists in the heart of the Silicon Valley given by the 2011 International Joint Conference on Neural Networks held in San Jose, CA, has offered us the unique opportunity of organizing a series of special events on the present status and future perspectives in neuromorphic memristor science. This book presents a selection of the remarkable contributions given by the leaders of the field and it may serve as inspiration and future reference to all researchers that want to explore the extraordinary possibilities given by this revolutionary concept.
Neural Computing for Advanced Applications
Author: Haijun Zhang
Publisher: Springer Nature
Published:
Total Pages: 367
ISBN-13: 9819770041
DOWNLOAD EBOOKInternational Conference on Neural Computing for Advanced Applications
Author: Haijun Zhang
Publisher: Springer Nature
Published: 2023-08-29
Total Pages: 627
ISBN-13: 9819958474
DOWNLOAD EBOOKThe two-volume set CCIS 1869 and 1870 constitutes the refereed proceedings of the 4th International Conference on Neural Computing for Advanced Applications, NCAA 2023, held in Hefei, China, in July 2023. The 83 full papers and 1 short paper presented in these proceedings were carefully reviewed and selected from 211 submissions. The papers have been organized in the following topical sections: Neural network (NN) theory, NN-based control systems, neuro-system integration and engineering applications; Machine learning and deep learning for data mining and data-driven applications; Computational intelligence, nature-inspired optimizers, and their engineering applications; Deep learning-driven pattern recognition, computer vision and its industrial applications; Natural language processing, knowledge graphs, recommender systems, and their applications; Neural computing-based fault diagnosis and forecasting, prognostic management, and cyber-physical system security; Sequence learning for spreading dynamics, forecasting, and intelligent techniques against epidemic spreading (2); Applications of Data Mining, Machine Learning and Neural Computing in Language Studies; Computational intelligent Fault Diagnosis and Fault-Tolerant Control, and Their Engineering Applications; and Other Neural computing-related topics.
Industrial Applications of Neural Networks
Author: Ian F. Croall
Publisher: Springer Science & Business Media
Published: 2012-12-06
Total Pages: 302
ISBN-13: 3642848370
DOWNLOAD EBOOKNeural network technology encompasses a class of methods which attempt to mimic the basic structures used in the brain for information processing. Thetechnology is aimed at problems such as pattern recognition which are difficult for traditional computational methods. Neural networks have potential applications in many industrial areas such as advanced robotics, operations research, and process engineering. This book is concerned with the application of neural network technology to real industrial problems. It summarizes a three-year collaborative international project called ANNIE (Applications of Neural Networks for Industry in Europe) which was jointly funded by industry and the European Commission within the ESPRIT programme. As a record of a working project, the book gives an insight into the real problems faced in taking a new technology from the workbench into a live industrial application, and shows just how it can be achieved. It stresses the comparison between neural networks and conventional approaches. Even the non-specialist reader will benefit from understanding the limitations as well as the advantages of the new technology.
Neural Networks for Instrumentation, Measurement, and Related Industrial Applications
Author:
Publisher: IOS Press
Published: 2003
Total Pages: 344
ISBN-13: 9781586033033
DOWNLOAD EBOOKNeuromorphic Computing Systems for Industry 4.0
Author: Dhanasekar, S.
Publisher: IGI Global
Published: 2023-07-19
Total Pages: 400
ISBN-13: 1668465981
DOWNLOAD EBOOKAs artificial intelligence (AI) processing moves from the cloud to the edge of the network, battery-powered and deeply embedded devices are challenged to perform AI functions such as computer vision and voice recognition. Microchip Technology Inc., via its Silicon Storage Technology (SST) subsidiary, is addressing this challenge by significantly reducing power with its analog memory technology, the memBrain Memory Solution. The memBrain solution is being adopted by today’s companies looking to advance machine learning capacities in edge devices. Due to its ability to significantly reduce power, this analog in-memory computer solution is ideal for an AI application. Neuromorphic Computing Systems for Industry 4.0 covers the available literature in the field of neural computing-based microchip technology. It provides further research opportunities in this dynamic field. Covering topics such as emotion recognition, biometric authentication, and neural network protection, this premier reference source is an essential resource for technology developers, computer scientists, engineers, students and educators of higher education, librarians, researchers, and academicians.
Neural Information Processing
Author: Long Cheng
Publisher: Springer
Published: 2018-12-03
Total Pages: 664
ISBN-13: 3030041670
DOWNLOAD EBOOKThe seven-volume set of LNCS 11301-11307, constitutes the proceedings of the 25th International Conference on Neural Information Processing, ICONIP 2018, held in Siem Reap, Cambodia, in December 2018. The 401 full papers presented were carefully reviewed and selected from 575 submissions. The papers address the emerging topics of theoretical research, empirical studies, and applications of neural information processing techniques across different domains. The first volume, LNCS 11301, is organized in topical sections on deep neural networks, convolutional neural networks, recurrent neural networks, and spiking neural networks.
Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing
Author: Sudeep Pasricha
Publisher: Springer Nature
Published: 2023-11-01
Total Pages: 418
ISBN-13: 303119568X
DOWNLOAD EBOOKThis book presents recent advances towards the goal of enabling efficient implementation of machine learning models on resource-constrained systems, covering different application domains. The focus is on presenting interesting and new use cases of applying machine learning to innovative application domains, exploring the efficient hardware design of efficient machine learning accelerators, memory optimization techniques, illustrating model compression and neural architecture search techniques for energy-efficient and fast execution on resource-constrained hardware platforms, and understanding hardware-software codesign techniques for achieving even greater energy, reliability, and performance benefits.
Neuromorphic Photonics
Author: Paul R. Prucnal
Publisher: CRC Press
Published: 2017-05-08
Total Pages: 412
ISBN-13: 1498725244
DOWNLOAD EBOOKThis 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.
