Project 732 Pattern Recognition and Neural Networks
Project Part 1: . Select a topic and a simulator that pertains to the subject matter of the class. Make sure the topic is extensive enough and the simulator includes several pattern classifiers AND/OR several neural networks.
You have to deliver a presentation focusing on the following:
1. Brief description of the simulator.
2. You should concentrate on 1-2 classifiers OR 1-2 neural networks (NNs) included into the simulator and some of their applications.
3. A brief report and presentation of respective learning algorithm.
4. Showing demos or snapshots with the chosen simulator.
5. References.
Project Part 2:. You have to deliver a Final Report and a Final Presentation focusing on the following:
a) You should present and explain the topology of particular pattern classifier or particular neural network included into the chosen simulator as well as to discuss and submit a detailed Final Report on design and implementation, training, testing and final classification (clustering) results and conclusions;
b) You should demonstrate learning and testing of the chosen Pattern Classifier or NN by using two generated two-dimensional datasets having 2 classes as well as one expert benchmark and to visualize the results.
Your Final Report must include: cover page, description of the simulator, description of the pattern classifier or NN used by you (topology, learning algorithms etc.), description of the two generated data sets and the expert benchmark.
Attachments to the Final Report: the files of datasets (3 txt or dat or doc files; the visualization of the two generated two-dimensional data sets; the description of experiments done by you including result discussions; conclusions and references.