Analytical Study of Neural Network Techniques: SOM, MLP and Classifier-A Survey
Journal Title: IOSR Journals (IOSR Journal of Computer Engineering) - Year 2014, Vol 16, Issue 3
Abstract
Abstract: This paper focuses on the various neural network techniques including Multilayer perceptron (MLP) neural network, classifier and self-organizing maps (SOMs). Various aspects of neural network techniques are mentioned in this paper along with the advantages and drawbacks. The neural network models are trained with measured values of the field strength at arbitrary points. The back propagation training algorithm is used for the learning process in MLP. The mechanism of supervised and unsupervised learning are also specified.
Authors and Affiliations
Sonali B. Wankhede
Keywords
Related Articles
- EP ID EP105163
- DOI 10.9790/0661-16378692
- Views 139
- Downloads 0
Modeling and Simulation of Solar Photovoltaic module using Matlab/Simulink
This paper presents the circuit model of photovoltaic (PV) module. Simulation and modeling is done using MATLAB/ Simulink software package. The proposed model is user friendly and can be used as a common pl...
A Review on Geometrical Analysis in Character Recognition
Abstract: Character Recognition is a prominent area in the field of image processing. Most of the basicconcepts in image processing have been introduced in connection with research carried out in characterrecogniti...
Survey on Restful Web Services Using Open Authorization (Oauth)
Web services are application based programming interfaces (API) or web APIs that are accessed through Hypertext Transfer Protocol (HTTP) to execute on a remote system hosting the requested services. A RESTF...
Energy Efficient Query Optimization in WSN usingThreeLevel Modelling
Abstract:With advancement in microprocessor technology, wireless sensor networks is playing vital role in different types of applications such as health care monitoring, fire detection etc. In these applications, large a...
A Review on Face Recognition and Video Databases
Abstract: Each And Every Face Databases Have Its Own Limitations And Description To Test The Performance Of Face Recognition Technique. Even Though, Current Machine Recognition Systems Have Approached To Certain Level Of...