Artificial Neural Networks
人工神经网络
Introduction
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Table of Contents
• Introduction to ANNs
– Taxonomy
– Features
– Learning
– Applications
I
• Supervised ANNs
– Examples
– Applications
– Further topics
II
• Unsupervised ANNs
– Examples
– Applications
– Further topics
III
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Contents - I
• Introduction to ANNs
– Processing elements (neurons)
– Architecture
• Functional Taxonomy of ANNs
• Structural Taxonomy of ANNs
• Features
• Learning Paradigms
• Applications
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The Biological Neuron
• 10 billion neurons in human brain
• Summation of input stimuli
– Spatial (signals)
– Temporal (pulses)
• Threshold over composed inputs
• Constant firing strength
• billion synapses in human brain
• Chemical transmission and
modulation of signals
• Inhibitory synapses
• Excitatory synapses
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Biological Neural Networks
• 10,000 synapses per
neuron
• Computational power =
connectivity
• Plasticity
– new connections (?)
– strength of
connections modified
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