Kevin Gurney has on-line a preliminary draft of his book, An Introduction to
Neural Networks, at 
http://www.shef.ac.uk/psychology/gurney/notes/index.html The book is now in
print and is one of the better general-purpose introductory textbooks on
NNs. Here is the table of contents from the on-line version: 

1. Computers and Symbols versus Nets and Neurons 
2. TLUs and vectors - simple learning rules 
3. The delta rule 
4. Multilayer nets and backpropagation 
5. Associative memories - the Hopfield net 
6. Hopfield nets (contd.) 
7. Kohonen nets 
8. Alternative node types 
9. Cubic nodes (contd.) and Reward Penalty training 
10. Drawing things together - some perspectives 

Another on-line book by Ben Kröse and Patrick van der Smagt, also called An
Introduction to Neural Networks, can be found at 
ftp://ftp.wins.uva.nl/pub/computer-systems/aut-sys/reports/neuro-intro/neuro-intro.ps.gz
or http://www.robotic.dlr.de/Smagt/books/neuro-intro.ps.gz. or 
http://www.supelec-rennes.fr/acth/net/neuro-intro.ps.gz 
Here is the table of contents: 

1. Introduction 
2. Fundamantals 
3. Perceptron and Adaline 
4. Back-Propagation 
5. Recurrent Networks 
6. Self-Organising Networks 
7. Reinforcement Learning 
8. Robot Control 
9. Vision 
10. General Purpose Hardware 
11. Dedicated Neuro-Hardware 

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