Clustering of self organizing map

Type :

Theses

Pages :

31 pages

Format :

.doc

Published date :

05/27/2009

Category :

Science & technology

Sub category :

Physics & chemistry

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Summary :

Introduction
1. Neural network
2. Application and neural network
3. Supervised and unsupervised learning
4. Self organizing map
5. Clustering
6. Types of clustering
Required analysis and specification
1. Introduction
2. Feasibility
3. Preparation of SRS
Software configuration and requirement
Function oriented software design
1. Structure analysis and DFD
Coding and testing
1. Introduction
2. Code review
3. Types of testing
Implementation
Conclusion
References

Abstract

This project is based on the research work on the clustering of self organizing map. SOM is an excellent tool, which is utilized to visualize the properties of data. The number of SOM units is larger than it is clustered in similar group. Use the SOM for clustering data without knowing the class memberships of the input data. The SOM can be used to detect features inherent to the problem and thus has also been called SOFM, the self-organizing Feature map. Use the SOM for clustering data without knowing the class memberships of the input data. The SOM can be used to detect features inherent to the problem and thus has also been called SOFM, the self-organizing Feature map.

Provides a topology preserving mapping from the high dimensional space to map units. map units, or neurons, usually form a two-dimensional lattice and thus the mapping is a mapping from high dimensional space onto a plane. The property of topology preserving means that the mapping preserves the relative distance between the points. Points that are near each other in the input space are mapped to nearby map units in the SOM. The SOM can thus serve as a cluster analyzing tool of high-dimensional data.

Here the system is totally based on the Matlab techniques and this is not the development of a new system it is only the research of the listing of self organizing map. Here we are using only the tools and techniques of the software engineering. No any software development model is using over the project. An artificial neural network (ANN), also called a simulated neural network (SNN) or commonly just neural network (NN) is an interconnected group of artificial neurons that uses a mathematical or computational model for information processing based on a connectionist approach to computation. In most cases an ANN is an adaptive system that changes its structure based on external or internal information that flows through the network..They can be used to model complex relationships between inputs and outputs.