CWT-Support Vector Regression Model and Its Application
Near-infrared spectroscopy (NIR) analytical technique is simple, fast and low cost, making neither pollution nor damage to the samples, and can determine many components simultaneously. Continuous wavelet transform (CWT), as an application direction of the wavelet analysis, is keener to the signal slight change. Support vector machine (SVM) is based on the principle of structural risk minimization, which makes SVM has better generalization ability than other traditional learning machines that are based on the learning principle of empirical risk minimization. In this paper, we use CWT- SVM model to predict meat’s component. Compared with Partial Least Squares (PLS) and SVR, we get more satisfactory result.
Zhenyu Du and X.B Sun
J. F. Liu et al., "CWT-Support Vector Regression Model and Its Application", Advanced Materials Research, Vols. 113-116, pp. 207-210, 2010