Non-Linear Feedback Neural Networks

VLSI Implementations and Applications
2014
ISBN: 978-81-322-1562-2
Verlag: Springer India

Buch, Englisch, Band 508, 201 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 4616 g

Reihe: Studies in Computational Intelligence

This book aims to present a viable alternative to the Hopfield Neural Network (HNN) model for analog computation. It is well known the standard HNN suffers from problems of convergence to local minima, and requirement of a large number of neurons and synaptic weights. Therefore, improved solutions are needed. The non-linear synapse neural network (NoSyNN) is one such possibility and is discussed in detail in this book. This book also discusses the applications in computationally intensive tasks like graph coloring, ranking, and linear as well as quadratic programming. The material in the book is useful to students, researchers and academician working in the area of analog computation.

Zielgruppe

Research

Autoren/Hrsg.

Ansari, Mohd. Samar

Fachgebiete

• Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik Bauelemente, Schaltkreise
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Neuronale Netzwerke

Inhaltsverzeichnis

Introduction.- Background.- Voltage-mode Neural Network for the Solution of Linear Equations.- Mixed-mode Neural Circuit for Solving Linear Equations.- Non-Linear Feedback Neural Circuits for Linear and Quadratic Programming.- OTA-based Implementations of Mixed-mode Neural Circuits.- Appendix A: Mixed-mode Neural Network for Graph Colouring.- Appendix B: Mixed-mode Neural Network for Ranking.

Über Autor(innen)

Dr. Mohammad Samar Ansari is an Assistant Professor of the Department of Electronics Engineering at Aligarh Muslim University, Aligarh, India. Before this he worked at the same university as a Lecturer and Guest Faculty from September 2004. Dr. Ansari also worked with Defense Research Development Organization (DRDO) and Siemens Limited during the years 2001–2003. He obtained PhD in 2012 (thesis title: Neural Circuits for Solving Linear Equations with Extensions for Mathematical Programming), and completed MTech (Electronics Engineering) in 2007 and BTech (Electronics Engineering) in 2001 from the same university. He has published 15 international journal papers and more than 30 international and national conference papers. He is a Life Member of The Institution of Electronics and Telecommunication Engineers (IETE), India.