This is an elegant, compact book that renders visible the too-often naturalized equation of brain and computer. A critical examination of the figure of the neural network as it mediates neuroscientific and computational discourses and technical practices.

Beginning with an introductory discussion on the role of neural networks in scientific data analysis, this book provides a solid foundation of basic neural network concepts. It is a systematic introduction to neural networks, biological foundation.

This book provides a clear and detailed coverage of fundamental neural network architectures and learning rules. It emphasizes a coherent presentation of the principal neural networks, methods for training them and their applications to practical problems.

This book describes recent theoretical advances in the study of artificial neural networks. It explores probabilistic models of supervised learning problems, and addresses the key statistical and computational questions.

In this book, theoretical laws and models previously scattered in the literature are brought together into a general theory of artificial neural nets. It is aimed at readers who seek an overview of the field or who wish to deepen their knowledge.

This book is a collection of lecture notes that offers an accessible introduction to Neural Networks and machine learning in general. The focus lies on classical machine learning techniques, with a bias towards classification and regression.

An insightful investigation into the mechanisms underlying the predictive functions of neural networks - and their ability to chart a new path for AI. Delve into the known neural architecture of the mammalian brain to illuminate the structure of predictive networks.

An accessible undergraduate textbook in computational neuroscience that provides an introduction to the mathematical and computational modeling of neurons and networks of neurons in Python. Build a foundation for modeling Neural Circuits.

Neural networks and deep learning currently provide the best solutions to many problems in image recognition, speech recognition, and natural language processing. This book will teach you the core concepts behind neural networks and deep learning.

This open access book unites the views from both academia and industry, where computer vision and machine learning meet environment perception for highly automated driving and artificial intelligence.

This modern and self-contained book offers a clear and accessible introduction to the important topic of machine learning with neural networks. It provides comprehensive coverage of neural networks, their evolution, their structure, their applications, etc.

This fundamental book on Artificial Neural Networks (ANN) has its emphasis on clear concepts, ease of understanding and simple examples. It presents a large variety of standard neural networks with architecture, algorithms and applications.

Intended to introduce readers to the use of Artificial Neural Networks in the study of music, this book contains numerous case studies and research findings that address problems related to identifying scales, keys, classifying musical chords, etc.

This book shows developers how they can bring Deep Learning technology to the web. Written by the main authors of the TensorFlow library, it provides fascinating use cases and in-depth instruction for deep learning apps in JavaScript in your browser or on Node.

In this book, highly qualified multidisciplinary scientists grasp their recent researches motivated by the importance of Artificial Neural Networks (ANN). It addresses advanced applications and innovative case studies for different fields using ANN.

This book leads you through the fundamental concepts of neural networks, including its architecture, its input-output, tanh and softmax activation, back-propagation, error and accuracy, normalization and encoding, and model interpretation.

It compactly summarises relevant work, much of it from the previous millennium. Shallow and deep learners are distinguished by the depth of their credit assignment paths, which are chains of possibly learnable, causal links between actions and effects.

This book focuses on the application of neural networks to a diverse range of fields and problems. It collates contributions concerning neural network applications in areas such as engineering, hydrology and medicine.

With an easy to understand format using graphical illustrations and multidisciplinary scientific context, this book fills the gap in the market for neural networks for multi-dimensional scientific data, and relates neural networks to statistics.

This book covers a range of models, circuits and systems built with Memristor devices and networks in applications to neural networks. It is divided into three parts: (1) Devices, (2) Models and (3) Applications.

Due to its nano-scale dimensions, non-volatility and memorizing properties, the Memristor is a sound potential candidate for application in computer high-density memories, artificial neural networks and in many other electronic devices.

Introduces the Java programmer to the world of Neural Networks and Artificial Intelligence using SNIPE. Examples include the traveling salesman problem, handwriting recognition, financial prediction, game strategy, mathematical functions, and Internet bots.

This is a current book on Artificial Neural Networks and Applications, bringing recent advances in the area to the reader interested in this always-evolving machine learning technique. It contains chapters on basic concepts of artificial neural networks.

This book covers architectures, design, optimization, and analysis of artificial neural networks as well as applications of artificial neural networks in a wide range of areas including biomedical, industrial, physics, and financial applications.

The book begins with fundamentals of artificial neural networks, which cover an introduction, design, and optimization. Advanced architectures for biomedical applications, which offer improved performance and desirable properties, follow.

Advanced information regarding the theory, concepts and applications of recurrent neural networks and the field of soft computing has been highlighted in this elaborative book. Additional topics in this vein are the application of AI techniques to electromagnetic interference problems, etc.

By presenting the latest research work the book demonstrates how real-time recurrent neural networks (RNNs) can be implemented to expand the range of traditional signal processing techniques and to help combat the problem of prediction.

This book investigates the following Recurrent Neural Networks (RNNs) models which solve some practical problems, together with their corresponding analysis on stability and convergence.

It provides algorithms, functions, and apps to create, train, visualize, and simulate neural networks. You can perform classification, regression, clustering, dimensionality reduction, time-series forecasting, and dynamic system modeling and control.

This book teaches you how to create your own neural network to solve classification problems, or problems where the outcomes can only be one of several values. Learn about encoding and normalizing data, activation functions and how to choose the right one.

Provides a logical and easy-to-follow progression through C++ programming for two of the most popular technologies for artificial intelligence: neural and fuzzy programming. Covers theory as well as practical working examples with reusable code.

This book focuses on using the neural network capabilities of Encog with the Java programming language. It begins with an introduction to the kinds of tasks neural networks are suited towards.

This book introduces the Java programmer to the world of Neural Networks and Artificial Intelligence. Neural network architectures such as the feedforward backpropagation, Hopfield, and Kohonen networks are discussed.

This book gives you a complete walkthrough of the process of developing basic to advanced practical examples based on neural networks with Java. No previous knowledge of neural networks is required as this book covers the concepts from scratch.