Deep Learning Classifiers with Memristive Networks: Theory and Applications

✍ Scribed by Alex Pappachen James

Publisher: Springer International Publishing
Year: 2020
Tongue: English
Leaves: 216
Series: Modeling and Optimization in Science and Technologies 14
Edition: 1st ed.
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

This book introduces readers to the fundamentals of deep neural network architectures, with a special emphasis on memristor circuits and systems. At first, the book offers an overview of neuro-memristive systems, including memristor devices, models, and theory, as well as an introduction to deep learning neural networks such as multi-layer networks, convolution neural networks, hierarchical temporal memory, and long short term memories, and deep neuro-fuzzy networks. It then focuses on the design of these neural networks using memristor crossbar architectures in detail. The book integrates the theory with various applications of neuro-memristive circuits and systems. It provides an introductory tutorial on a range of issues in the design, evaluation techniques, and implementations of different deep neural network architectures with memristors.

✦ Table of Contents

Front Matter ....Pages i-xiii
Front Matter ....Pages 1-1
Introduction to Neuro-Memristive Systems (Alex Pappachen James)....Pages 3-12
Memristors: Properties, Models, Materials (Olga Krestinskaya, Aidana Irmanova, Alex Pappachen James)....Pages 13-40
Deep Learning Theory Simplified (Adilya Bakambekova, Alex Pappachen James)....Pages 41-55
Getting Started with TensorFlow Deep Learning (Yeldar Toleubay, Alex Pappachen James)....Pages 57-67
Speech Recognition Application Using Deep Learning Neural Network (Akzharkyn Izbassarova, Aziza Duisembay, Alex Pappachen James)....Pages 69-79
Deep-Learning-Based Approach for Outdoor Electrical Insulator Inspection (Damira Pernebayeva, Alex Pappachen James)....Pages 81-88
Front Matter ....Pages 89-89
Learning Algorithms and Implementation (Olga Krestinskaya, Alex Pappachen James)....Pages 91-102
Multi-level Memristive Memory for Neural Networks (Aidana Irmanova, Serikbolsyn Myrzakhmet, Alex Pappachen James)....Pages 103-116
Memristive Threshold Logic Networks (Irina Dolzhikova, Akshay Kumar Maan, Alex Pappachen James)....Pages 117-130
Memristive Deep Convolutional Neural Networks (Olga Krestinskaya, Alex Pappachen James)....Pages 131-137
Overview of Long Short-Term Memory Neural Networks (Kamilya Smagulova, Alex Pappachen James)....Pages 139-153
Memristive LSTM Architectures (Kazybek Adam, Kamilya Smagulova, Alex Pappachen James)....Pages 155-167
HTM Theory (Yeldos Dauletkhanuly, Olga Krestinskaya, Alex Pappachen James)....Pages 169-180
Memristive Hierarchical Temporal Memory (Olga Krestinskaya, Irina Dolzhikova, Alex Pappachen James)....Pages 181-194
Deep Neuro-Fuzzy Architectures (Anuar Dorzhigulov, Alex Pappachen James)....Pages 195-213

✦ Subjects

Engineering; Computational Intelligence; Pattern Recognition; Data Mining and Knowledge Discovery; Image Processing and Computer Vision

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