8. The method for recognizing a handwritten character of claim 1 , wherein the step D comprises the following sub-steps of: selecting a part of eigenvalues from the multi-dimensional eigenvector of the inputted character according to the Fisher criteria, wherein the inputted character has an eigenvector composed of the selected eigenvalues and having the same dimensionality as the samples of the character classes; and matching the inputted character with the coarse classification template and selecting a plurality of candidate character classes having the greatest similarity from the pre-stored character classes.
8. The method for recognizing a handwritten character of claim 1 , wherein the step D comprises the following sub-steps of: selecting a part of eigenvalues from the multi-dimensional eigenvector of the inputted character according to the Fisher criteria, wherein the inputted character has an eigenvector composed of the selected eigenvalues and having the same dimensionality as the samples of the character classes; and matching the inputted character with the coarse classification template and selecting a plurality of candidate character classes having the greatest similarity from the pre-stored character classes. 9. The method for recognizing a handwritten character of claim 8 , wherein the step E comprises the following sub-steps of: performing eigen transformation on the inputted character by using the eigen transformation matrix that has been iteratively adjusted to obtain a low-dimensionality eigenvector; and matching the low-dimensionality eigenvector of the inputted character with the sample centers of the candidate character classes selected from the fine classification template respectively, and determining the most similar character classes among the candidate character classes for the user to select.