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Introduction to Basic Concepts
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Acorn Archimedes activation level active units Apple Macintosh architecture auto-associative nets backpropagation Beginner's Guide biological calculated cells Chapter click Continue click Filer click Learn click Options cognition Competitive Learning Covariance rule cycles decrease Delta rule epochs error example Excite exercise familiar shapes feature feed-forward floppy disks generalisation gradient descent Hebbian learning Hebbian rules hidden layer hidden units Hinton increase input patterns input units internal input lateral inhibition learned patterns learning rate learning rules mapping units McClelland and Rumelhart module mouse button multiplied neo-cortex netj neural computation neural nets neurons object units output function output patterns output unit parallel distributed processing pattern of activity pattern pairs pattern set post-synaptic unit Pre-synaptic rule pre-synaptic unit problem procedure produce receptive fields representation retina Rumelhart Select Learn signal specify Stent-Singer rule synaptic test input test pattern unit activation unit in L2 values weights matrix weights on connections WtDec