Download - Artificial Neural Networks (ANN’s)
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).• They are capable of machine learning and are
exceptional in pattern recognition.• A Network is application specific.
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
Biological Neural Networks• A human neuron has three parts: the cell
body, the axon and dendrites.• The process of sending a signal...
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
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.
Types
• Functiona. Feed Forwardb. Feed Back
• Structurea. Bottleneckb. Deep learning
Current Uses• Recognition
• Image• Speech• Pattern• Character
• Compression• Image• Audio/Video
• ALVINN - Driverless car
Feed Forward Algorithm• Input -> Output• Each neuron must
sum the weighted products from the previous layer.
• Output using activation function.
•
Back Propagation•Output -> Input•Training Algorithm•Calculates Error in the output layer
•Propagates Error backwards to change weights
Criticism/Negative Aspects• Large amounts of computing power and
storage are needed• Cost efficiency• Human abilities
• Instinct• Logic
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
Character Recognition
1
1
1
100..
N = 15
..
N = 10
..1
.
.
0
0
2. Input data in the ANN
Character Recognition
1
1
1
100..
N = 15
..
N = 10
..1
.
.
0
0
2. Input data in the ANN