Name
Abstract | ||
|---|---|---|
In this paper, a new constructive auto-associative neural network performing nonlinear principal component analysis is presented. The developed constructive neural network maps the data nonlinearly into its principal components and preserves the order of principal components at the same time. The weights of the neural network are trained by a combination of Back Propagation (BP) and Genetic Algorithm (GA) which accelerates the training process by preventing local minima. The performance of the proposed method was evaluated by means of two different experiments that illustrated its efficiency. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/IJCNN.2007.4371017 | 2007 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-6 |
Keywords | Field | DocType |
back propagation,local minima,principal component analysis,neural nets,neural network,genetic algorithm,genetic algorithms,backpropagation,principal component | Pattern recognition,Constructive,Computer science,Stochastic neural network,Maxima and minima,Time delay neural network,Artificial intelligence,Artificial neural network,Backpropagation,Genetic algorithm,Principal component analysis,Machine learning | Conference |
ISSN | Citations | PageRank |
2161-4393 | 4 | 0.59 |
References | Authors | |
9 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Behrooz Makki | 1 | 366 | 34.36 |
| Seyed Ali Seyed Salehi | 2 | 4 | 0.93 |
| Mona Noori Hosseini | 3 | 28 | 4.85 |
| Nasser Sadati | 4 | 140 | 22.16 |