An Efficient Piecewise Linear Network
| dc.contributor | Rawat, Rohit | en_US |
| dc.date.accessioned | 2010-03-03T23:30:43Z | |
| dc.date.accessioned | 2011-08-24T21:43:22Z | |
| dc.date.available | 2010-03-03T23:30:43Z | |
| dc.date.available | 2011-08-24T21:43:22Z | |
| dc.date.issued | 2010-03-03T23:30:43Z | |
| dc.date.submitted | January 2009 | en_US |
| dc.description.abstract | A Piecewise Linear Network (PLN) is a local network that offers the accuracy of higher order networks and the Multi Layer Perceptron (MLP), with the computational simplicity of linear networks. A method to design a PLN is demonstrated and several clustering algorithms, used in the design procedure, are compared. The performance of the Self Organizing Map (SOM) clustering algorithm has been found to be slightly better than the other clustering methods. Methods to determine the appropriate threshold in the Sequential Leader algorithm have been studied. A binary search based approach was found to be the most efficient in terms of the number of trials needed. Methods to delete extra clusters generated have been studied and compared to pruning. Pruning yields the best networks followed by deleting the smallest clusters. Methods of improving PLN pruning performance have been developed, including segregation of patterns by clusters, the use of partial distances, and redesign of only changed clusters. Results have been presented for several different data files. | en_US |
| dc.identifier.uri | http://hdl.handle.net/10106/2062 | |
| dc.language.iso | EN | en_US |
| dc.publisher | Electrical Engineering | en_US |
| dc.title | An Efficient Piecewise Linear Network | en_US |
| dc.type | M.S. | en_US |