The property of the Kullback-Leibler Kernel for Normalized Frequency Spectrum
-
- ISHIGAKI Tsukasa
- Department of Statistical Science, Graduate School of Multidisciplinary Sciences, The Graduate University for Advanced Studies
-
- HIGUCHI Tomoyuki
- The Institute of Statistical Mathematics
Bibliographic Information
- Other Title
-
- Kullback-Leibler カーネルの正規化スペクトル判別における特性
Abstract
<p>The kernel classifier that realizes a nonlinear classification such as Support Vector Machine has been successfully implemented in a number of fields. In the kernel method, the appropriate selection or design of the kernel function is important for the construction of a classifier that has high performance. The present paper describes a normalized frequency spectrum classification method using the SVM with the Kullback-Leibler (KL) kernel. We introduce the KL kernel to normalized spectrum classification and study the property of similarity calculation of the KL kernel and other common kernels with respect to the change in the appearance position of spectrum peaks.</p>
Journal
-
- JSAI Technical Report, Type 2 SIG
-
JSAI Technical Report, Type 2 SIG 2007 (DMSM-A701), 15-, 2007-07-25
The Japanese Society for Artificial Intelligence
- Tweet
Details 詳細情報について
-
- CRID
- 1390289225020714112
-
- NII Article ID
- 130008079488
-
- ISSN
- 24365556
-
- Text Lang
- ja
-
- Data Source
-
- JaLC
- CiNii Articles
- KAKEN
-
- Abstract License Flag
- Allowed