Proceedings of Signal Processing with Adaptive Sparse Structured Representations (SPARS'05), pp. 123–126

著者:

  • Shiro Ikeda

Abstract:

We propose a new type of kernel function, where feature space is explicitly given with a piece-wise linear mapping from the input space. This idea is inspired by sparse linear system analysis, where inputs are represented as a sparse linear combination of ``dictionary vectors.’’ This article gives the idea of such kernel function, and some preliminary experimental results.