Least-Squares Wavelet Kernel Method for Regression Estimation

• Published in: Advances in Natural Computation pp. 582 - 591
• Main Authors: Wen, Xiangjun, Xu, Xiaoming, Cai, Yunze
• Format: Book Chapter Conference Proceeding
• Language: English
• Published: Berlin, Heidelberg Springer Berlin Heidelberg 2005; Springer
• Series: Lecture Notes in Computer Science
• Subjects: Applied sciences; Artificial intelligence; Computer science; control theory; systems; Exact sciences and technology; Kernel Operator; Little Square Support Vector Machine; Reproduce Kernel Hilbert Space; Support Vector Machine; Wavelet Frame; Kernel function; Statistical analysis; Wavelet transformation; Least squares method; Vector support machine; Hilbert space; Feasibility; Regression analysis; Kernel method

Based on the wavelet decomposition and reproducing kernel Hilbert space (RKHS), a novel notion of least squares wavelet support vector machine (LS-WSVM) with universal reproducing wavelet kernels is proposed for approximating arbitrary nonlinear functions. The good reproducing property of wavelet ke...