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 network approaches and architectures with the theories, this text presents detailed case studies for each of the approaches, accompanied with complete computer codes and the corresponding computed results. The case studies are designed to allow easy comparison of network performance to illustrate strengths and weaknesses of the different networks.

本书应作为大学研究生课程或工程和计算机科学系的神经网络高级本科课程的教材。它还应作为工业界的工程师和计算机科学家的自学课程。本书涵盖了主要的神经网络方法和架构的理论，为每种方法提供了详细的案例研究，并附有完整的计算机代码和相应的计算结果。案例研究的目的是便于比较网络性能，以说明不同网络的优势和劣势。