fruits are one of the oldest forms of food known to man. there are many references to fruits in ancient literature. according to quran, the fruits like grape, date, fig, olive and pomegranate are gifts and heavenly fruits of god.  fresh and dry fruits are the natural staple food of man. they contain substantial quantities of essential nutrients in a rational proportion. persons subsisting on th...

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...

Motivated by mathematical learning from training data, we introduce the notion of refinable kernels. Various characterizations of refinable kernels are presented. The concept of refinable kernels leads to the introduction of wavelet-like reproducing kernels. We also investigate a refinable kernel that forms a Riesz basis. In particular, we characterize refinable translation invariant kernels, a...

We study the existence of polynomial kernels, for parameterized problems without a kernel on general graphs, when restricted to graphs bounded twin-width. Our main result is that k -Dominating Set twin-width at most 4 would contradict standard complexity-theoretic assumption. The reduction quite involved, especially get upper bound down 4, and can be tweaked work Connected Total (albeit with wo...

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...