An Introduction to Neural Networks
An Introduction to Neural Networks
Vincent Cheung Kevin Cannons
Signal & Data Compression Laboratory Electrical & Computer Engineering University of Manitoba Winnipeg, Manitoba, Canada Advisor: Dr. W. Kinsner
May 27, 2002
Outline
Fundamentals Classes Design and Verification Results and Discussion Conclusion
Cheung/Cannons
Neural Networks 1
Classes Fundamentals
Neural Networks
What Are Artificial Neural Networks?
An extremely simplified model of the brain Essentially a function approximator
Transforms inputs into outputs to the best of its ability
Inputs
Outputs
Inputs
NN
Outputs
Design
Results
Cheung/Cannons
2
Classes Fundamentals
Neural Networks
What Are Artificial Neural Networks?
Composed of many "neurons" that co-operate to perform the desired function
Design
Results
Cheung/Cannons
3
Classes Fundamentals
What Are They Used For?
Neural Networks
Classification
Pattern recognition, feature extraction, image matching
Noise Reduction
Recognize patterns in the inputs and produce noiseless outputs
Prediction
Extrapolation based on historical data
Design
Results
Cheung/Cannons
4
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