In this article we study the hypercyclic behavior of non-convolution operators defined on spaces of analytic functions of different holomorphy types over Banach spaces. The operators in the family we analyze are a composition ...

We study hypercyclicity properties of a family of non-convolution operators defined on the spaces of entire functions on CN. These operators are a composition of a differentiation operator and an affine composition operator, ...

A theorem of Godefroy and Shapiro states that non-trivial convolution operators on the space of entire functions on (Formula Presented.) are hypercyclic. Moreover, it was shown by Bonilla and Grosse-Erdmann that they have ...

Graph Convolutional Networks (GCNs) have been established as a fundamental approach for representation learning on graphs, based on convolution operations on non-Euclidean domain, defined by graph-structured data. GCNs and ...

Recurring expenses associated with preventative maintenance and inspectionproduce operational inefficiencies and unnecessary spending. Human inspec-tors may submit inaccurate damage assessments and physically inaccessibl ...

The aim of Neuroevolution is to nd neural networks and convolutional neural network (CNN) architectures automatically through evolutionary algorithms. A crucial problem in neuroevolution is search time, since multiple ...

The study of signals and systems makes a study field very important for Engineering. It’s through this kind of study that it’s possible to model, represent, study and understand various phenomena that occurs in peoples ...

Let μ be a non-negative Ahlfors n-dimensional measure on Rd. In this context we shall consider convolution type operators Tαf = Kα ∗f, 0 <α< n, where the kernels Kα are supposed to satisfy certain size and regularity ...