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