Principles of Artificial Neural Networks

📁 Principles of Artificial Neural Networks

✍ Daniel Graupe 📂 Library 📅 1997 🏛 World Scientific Publishing Company 🌐 English

This textbook is intended for a first-year graduate course on artificial neural networks. It assumes no prior background in the subject and is directed to MS students in electrical engineering, computer science and related fields, with background in at least one programming language or in a programm

📁 Principles of Artificial Neural Networks

✍ Daniel Graupe 📂 Library 📅 2013 🏛 World Scientific Publishing Company 🌐 English

Artificial neural networks are most suitable for solving problems that are complex, ill-defined, highly nonlinear, of many and different variables, and/or stochastic. Such problems are abundant in medicine, in finance, in security and beyond. <P> This volume covers the basic theory and architecture

Principles of artificial neural networks

📁 Principles of artificial neural networks

✍ Graupe, Daniel 📂 Library 📅 2007 🏛 World Scientific 🌐 English

The book should serve as a text for a university graduate course or for an advanced undergraduate course on neural networks in engineering and computer science departments. It should also serve as a self-study course for engineers and computer scientists in the industry. Covering major neural networ

Principles of artificial neural networks

📁 Principles of artificial neural networks

✍ Graupe, Daniel 📂 Library 📅 2013 🏛 World Scientific Publ 🌐 English

Principles of artificial neural networks

📁 Principles of artificial neural networks

✍ Daniel Graupe 📂 Library 📅 2007 🏛 World Scientific 🌐 English

Principles of artificial neural networks

📁 Principles of artificial neural networks

✍ Daniel Graupe 📂 Library 📅 2007 🏛 World Scientific 🌐 English

The book should serve as a text for a university graduate course or for an advanced undergraduate course on neural networks in engineering and computer science departments. It should also serve as a self-study course for engineers and computer scientists in the industry. Covering major neural networ