artificial neural networks (ann’s)
DESCRIPTION
Artificial Neural Networks (ANN’s). Jacob Drilling & Justin Brown. What is an Artificial Neural Network?. A computational model inspired by animals’ central nervous systems. Composed of connected processing nodes (neurons). - PowerPoint PPT PresentationTRANSCRIPT
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Artificial Neural Networks (ANN’s)
Jacob Drilling&
Justin Brown
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What is an Artificial Neural Network?• A computational model inspired by animals’
central nervous systems.• Composed of connected processing nodes
(neurons).• They are capable of machine learning and are
exceptional in pattern recognition.• A Network is application specific.
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History•Warren McCulloch and Walter Pitts
• Threshold Logic•Frank Rosenblatt
• Perceptron•Marvin Minsky and Seymour Papert
• The Society of Mind Theory•Paul Werbos
• Backpropagation•David E. Rumelhart and James McClelland
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Biological Neural Networks• A human neuron has three parts: the cell
body, the axon and dendrites.• The process of sending a signal...
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Artificial Networks● The Artificial model is comprised of many
processing nodes (neurons).● Nodes are highly connected with weighted
paths.● It has 3 layers:
○ Input○ Hidden○ Output
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Artificial Networks● Each node does its own
processing.● Nodes output according to
their activation function.● Initial weights are random.● Back Propagation Algorithm
“teaches” by changing weights.
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Types
• Functiona. Feed Forwardb. Feed Back
• Structurea. Bottleneckb. Deep learning
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Current Uses• Recognition
• Image• Speech• Pattern• Character
• Compression• Image• Audio/Video
• ALVINN - Driverless car
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Feed Forward Algorithm• Input -> Output• Each neuron must
sum the weighted products from the previous layer.
• Output using activation function.
•
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Back Propagation•Output -> Input•Training Algorithm•Calculates Error in the output layer
•Propagates Error backwards to change weights
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Criticism/Negative Aspects• Large amounts of computing power and
storage are needed• Cost efficiency• Human abilities
• Instinct• Logic
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Character Recognition
1. Image Processing
1 1 0 0 0 0 0 0 1 11 0 1 1 1 1 1 0 0 10 1 1 1 1 1 1 1 0 10 1 1 1 1 1 1 1 1 00 1 1 1 1 1 1 1 1 00 1 1 1 1 1 1 1 1 01 0 1 1 1 1 1 1 1 01 0 1 1 1 1 1 1 0 11 1 0 0 1 1 1 0 1 11 1 1 0 0 0 0 1 1 1
10
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Character Recognition
1
1
1
100..
N = 15
..
N = 10
..1
.
.
0
0
2. Input data in the ANN
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Character Recognition
1
1
1
100..
N = 15
..
N = 10
..1
.
.
0
0
2. Input data in the ANN