Object-Oriented Neural Networks in C++

It may suprise some people to learn that not all programmers are experts at higher math. I had gone through dozens of web sites and several books looking for a way to implement a neural network. All of these sites talked about network theory and analysis with lots of greek letters that meant nothing to me but none of them had any code. This book lays out object oriented code for four of the most common types of neural networks and explains every property and function in detail. If you are looking for a book on neural network theory this is not it. If you are looking for code samples that let you build basic networks and play with them yourself this book is perfect.

Some knowledge of C++ is essential, but classes are very well laid out, and code is easy to use and re-use. To an extent, it is too academic, and could be streamlined a bit for performance. More comprehensive examples would be a plus. Overall an excellent introduction to neural net programming. A follow-up on other neural net architectures would be greatly appreciated.

After returning Practical Neural Network Recipies, I decided to throw the dice once more and try this text. I found it to be an excellent explanation of what NNs are and how to implement them in an OO fashion. The book is lucid and can be read from cover to cover much like a novel.

I've always wanted to learn about neural network programming, but have been disappointed with the books on the subject in the past. This book presents the reader with a complete object-oriented approach to neural network programming, and provides a basis upon which any new neural network design may be based. The example programs are short and easy to follow, and the entire source code for the class libraries are listed in the back of the book for reference (and also included on the disk).What I'm most fascinated with is image and pattern recognition, and this is the path I plan to take with this library. It is certainly robust enough to handle any neural network concept, and extensible. The source code was written with straight ANSI C++ (or standard template library, as I recall), so it is portable to almost any platform.

Unlike many books on similar topics, Object-Oriented Neural-Networks in C++ provides a truly object-oriented approach to the design and implementation of neural networks. This book is not only a good tool for those beginning with neural-networks giving step-by-step instructions for constructing a variety of neural network architectures, it also provides a good set of tools for the advanced neural network user to build more flexible and powerful neural-network architectures. The book covers 4 basic neural network architectures (ADALINE, Backpropagation, Self-Organizing, and BAM); however, the object foundation provided by the book can be the basis for any neural network architecture. The book contains a complete set of source code (in print and on disk) for all objects described, real-world examples, and a review of the C++ programming techniques used throughout the book