This article presents a survey of various methods for nonparametric identification of nonlinear systems. Nonparametric identification methods are those that measure Wiener kernels or Volterra kernels, since an output of a nonlinear system can be described by the convolution integral of Wiener or Volterra kernels and the system input. Section 1 highlights the representation methods of nonlinear ...

Besides using standard radial basis functions, there are a few good reasons to look for kernels with special properties. This survey will provide several examples, starting from an introduction into kernel construction techniques. After providing the “missing” Wendland functions, we focus on kernels based on series expansions. These have some very interesting special cases, namely polynomial an...

Kernels for structured data are rapidly becoming an essential part of the machine learning toolbox. Graph kernels provide similarity measures for complex relational objects, such as molecules and enzymes. Graph kernels based on walks are popular due their fast computation but their predictive performance is often not satisfactory, while kernels based on subgraphs suffer from high computational ...

We propose a family of kernels based on the Binet-Cauchy theorem and its extension to Fredholm operators. This includes as special cases all currently known kernels derived from the behavioral framework, diffusion processes, marginalized kernels, kernels on graphs, and the kernels on sets arising from the subspace angle approach. Many of these kernels can be seen as the extrema of a new continu...

An entirely new set of criteria for the design of kernels (generating functions) for time-frequency representations (TFRs) is presented. These criteria aim only to produce kernels (and thus, TFRs) which will enable more accurate classification. We refer to these kernels, which are optimized to discriminate among several classes of signals, as signal class dependent kernels, or simply class depe...

This paper provides an overview of string kernels. String kernels compare text documents by the substrings they contain. Because of high computational complexity, methods for approximating string kernels are shown. Several extensions for string kernels are also presented. Finally string kernels are compared to BOW.

microwave assisted fluidized bed drying is a novel drying technique which reduces drying time and yields higher quality products. in this study the effect of this method on color changes of whole and cut hazelnut kernels was investigated. the parameters of color and resulting total color change, chroma, hue angle and browning index were also calculated during drying in three temperatures (40, 5...

abstract. in this paper, we classify all of the finite p-groups with at most three non linear irreducible character kernels.

Abstract. In this paper, we classify all of the finite p-groups with at most three non linear irreducible character kernels.