Oscillatory Neural Networks
From Devices to Computing Architectures
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Beschreibung
This book covers oscillatory computing devices (a.k.a. Oscillatory Neural Networks, ONNs), a type of analog device architecture at the forefront of research for neuromorphic (edge-AI) applications that promises to boost the energy efficiency of neuromorphic computing pipelines by orders of magnitude. The authors provide a comprehensive overview of this multidisciplinary field, covering device physics, circuit design, and computing architectures, as well as the mathematical principles of oscillator synchronization. The chapters are written in a manner that allows non-experts to explore and appreciate the connections between different facets of the subject. This book serves as a resource for a diverse audience, catering to physicists and nanotechnology researchers involved in developing novel oscillator devices. It is also pertinent to the circuit design community, offering fresh perspectives on sensory processing and edge-AI processing. Finally, it serves as an asset for the rapidlyexpanding machine learning/AI community, providing insights into leveraging the processing capabilities of Oscillatory Neural Network (ONN) hardware.
Discusses Oscillatory Neural Networks (ONNs), from device physics to analog circuit design and AI/machine learning
Emphasizes diverse application domains, including NP-hard problems, neuromorphic computing, and sensory processing
Includes comprehensive introductory chapters and contributions from experts representing key pillars in the ONN field
This book covers oscillatory computing devices (a.k.a. Oscillatory Neural Networks, ONNs), a type of analog device architecture at the forefront of research for neuromorphic (edge-AI) applications that promises to boost the energy efficiency of neuromorphic computing pipelines by orders of magnitude. The authors provide a comprehensive overview of this multidisciplinary field, covering device physics, circuit design, and computing architectures, as well as the mathematical principles of oscillator synchronization. The chapters are written in a manner that allows non-experts to explore and appreciate the connections between different facets of the subject. This book serves as a resource for a diverse audience, catering to physicists and nanotechnology researchers involved in developing novel oscillator devices. It is also pertinent to the circuit design community, offering fresh perspectives on sensory processing and edge-AI processing. Finally, it serves as an asset for the rapidlyexpanding machine learning/AI community, providing insights into leveraging the processing capabilities of Oscillatory Neural Network (ONN) hardware.
Discusses Oscillatory Neural Networks (ONNs), from device physics to analog circuit design and AI/machine learning Emphasizes diverse application domains, including NP-hard problems, neuromorphic computing, and sensory processing Includes comprehensive introductory chapters and contributions from experts representing key pillars in the ONN field
Autor*in
Aida Todri-Sanial
Themen in »Oscillatory Neural Networks«
Oscillator networks Oscillator-based computing Memristor computing Analog computing devices Phase-based computing