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What are artificial neural networks? What are their components and associated learning algorithms? What can they be used for? What are their properties and limitations? Elements of Artificial Neural Networks book addresses these questions, providing a clear introduction to neural networks to newcomers to the field who want to use them as well as understand the underlying principles and algorithms. The authors of this book on artificial neural networks, who have team-taught the material in a one-semester course for more than 10 years, describe most of the basic neural network models (with several detailed solved examples) and discuss their rationale and relative advantages.  Their approach requires little mathematical or technical background.  Written from an algorithmic perspective, this text on artificial neural networks stresses links to contiguous fields and can serve as a first course for students in computer science as well as disciplines such as engineering, medicine, economics and management, where the goal is to learn how to develop practical applications using neural network tools.