Buch, Englisch, Band 31, 210 Seiten, HC runder Rücken kaschiert, Format (B × H): 160 mm x 241 mm, Gewicht: 4675 g
Reihe: Cognitive Systems Monographs
Buch, Englisch, Band 31, 210 Seiten, HC runder Rücken kaschiert, Format (B × H): 160 mm x 241 mm, Gewicht: 4675 g
Reihe: Cognitive Systems Monographs
ISBN: 978-81-322-3701-3
Verlag: Springer India
This book covers all major aspects of cutting-edge research in the field of neuromorphic hardware engineering involving emerging nanoscale devices. Special emphasis is given to leading works in hybrid low-power CMOS-Nanodevice design. The book offers readers a bidirectional (top-down and bottom-up) perspective on designing efficient bio-inspired hardware. At the nanodevice level, it focuses on various flavors of emerging resistive memory (RRAM) technology. At the algorithm level, it addresses optimized implementations of supervised and stochastic learning paradigms such as: spike-time-dependent plasticity (STDP), long-term potentiation (LTP), long-term depression (LTD), extreme learning machines (ELM) and early adoptions of restricted Boltzmann machines (RBM) to name a few. The contributions discuss system-level power/energy/parasitic trade-offs, and complex real-world applications. The book is suited for both advanced researchers and students interested in the field.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik Bauelemente, Schaltkreise
- Technische Wissenschaften Technik Allgemein Nanotechnologie
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
- Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion
Weitere Infos & Material
Phase Change Memory for Neuromorphics.- Filamentary resistive memory for Neuromorphics.- Metal oxide based memory for Neuromorphics.- Nano Organic Transistors for Neuromorphics.- Neuromorphic System design.- Neuromorphic System and algorithms optimization.- Memristor Technology for Neuromorphics.- PCMO based devices for Neuromorphics.- Resistive Memory for Neuromorphics.- Overall Perspective on Neuromorphic Hardware.