1. Modular Neural Networks for Pattern Classification Using LabVIEW®
CS 539 Neural Networks and Fuzzy Systems
Rey Hernandez
CS539 Final Project
Goals
Description
Competing Models
LabVIEW®
Implementation Differences From Standard Approaches
Current Status
9/16/2018
University of Wisconsin - Madison

2. Goals Goal: To develop a pattern classifier in LabVIEW®
9/16/2018
University of Wisconsin - Madison
Goals
Goal: To develop a pattern classifier in LabVIEW®
Pattern Classifiers normally developed with C++ or Matlab
Equations used in Modular Neural Network

3. University of Wisconsin - Madison
9/16/2018
University of Wisconsin - Madison
Description
There is a strong interest in developing robust pattern classifiers that can handle an assortment of data
Modular Neural networks provide that robustness by specializing in different areas of the data without sacrificing on generalizing capabilities

4. University of Wisconsin - Madison
9/16/2018
University of Wisconsin - Madison
Competing Models
Multilayer perceptrons (MLP)
Preferred choice when doing pattern recognition
MLPs can learn from data that is not linearly separable
Weaknesses of MNNs
In LabVIEW® a weakness of the MNN approach is its large memory usage

5. Competing Models Cont. Strengths of Modular Neural Networks (MNN)
9/16/2018
Competing Models Cont.
Strengths of Modular Neural Networks (MNN)
MNNs can also learn from not-linearly separable data
MNNs can perform better than MLPs because they can devote each module to a separate piece of data
MLPs may have difficulty with data sets that are discontinuous

6. University of Wisconsin - Madison
9/16/2018
University of Wisconsin - Madison
LabVIEW®
Popular Data Acquisition and Analysis Tool
Uses a completely modular approach to programming
Rather than written code, LabVIEW® uses icons and ‘wires’ to control the flow of data and computation
LabVIEW® makes very efficient use of arrays which can be an asset when calculating the weights of the networks

7. 9/16/2018
LabVIEW® cont.
Modularity inherent to both LabVIEW® and Modular Neural Networks
MNN can benefit from the ease of designing separate modules for simple tasks
In MNN there are modules which are single layer perceptrons
In LabVIEW® can make a module to behave like a perceptron network

8. Implementation Differences From Standard Approaches
9/16/2018
University of Wisconsin - Madison
Implementation Differences From Standard Approaches
Again, not written code, graphical in nature
Equations can’t be handled in the usual way
As in the pictorial representations of MNNs, so to does LabVIEW® provide a pictorial view of the MNN

9. University of Wisconsin - Madison
9/16/2018
University of Wisconsin - Madison
Current Status
The Program is in the initial stages right now
Working version classifies nicely
More can be added along the way of making a larger hierarchical structure
Features to add and goals to accomplish
Can classify new data but can’t save it
Statistical information about the network is non-existent
Ability to use a larger hierarchy would be nice