Pattern recognition using neural networks: theory and algorithms for engineers and scientists
Pattern recognition using neural networks: theory and algorithms for engineers and scientists
Learning and Design of Principal Curves
IEEE Transactions on Pattern Analysis and Machine Intelligence
Process Modeling, Simulation, and Control for Chical Engineers
Process Modeling, Simulation, and Control for Chical Engineers
A k-segments algorithm for finding principal curves
Pattern Recognition Letters
Hi-index | 0.00 |
This paper proposes a strategy for feature extraction of noisy high dimensional data. Firstly, the moving median filter is used for reducing the effect of noise and outliers in the measurement data. Then, the data is projected to a lower dimension feature space using radial basis function (RBF) network and polygonal line (PL). A case study based on a simulated continuos stirred tank reactor (CSTR) has been investigated to check the effectiveness of the proposed strategy. The result shows that it is very effective for dimensionality reduction with minimum loss of information.