The present paper deals with some geometric classes of analytic functions, such as starlike, convex and bounded turning property in a complex domain. These classes are defined by a new linear operator in the normalized space of analytic functions. The linear operator is introduced by a convolution of Szego function involving parametric coefficients type Laguerre polynomial, with the normalized ...

The paper deals with a homogenization problem for a nonlocal linear operator with a kernel of convolution type in a medium with a periodic structure. We consider the natural diffusive scaling of this operator and study the limit behavior of the rescaled operators as the scaling parameter tends to 0. More precisely we show that in the topology of resolvent convergence the family of rescaled oper...

Let H be the general, reduced Heisenberg group. Our main result establishes the inverse-closedness of a class of integral operators acting on Lp(H), given by the off-diagonal decay of the kernel. As a consequence of this result, we show that if α1I+Sf , where Sf is the operator given by convolution with f , f ∈ Lv(H), is invertible in B(Lp(H)), then (α1I + Sf )−1 = α2I + Sg, and g ∈ Lv(H). We p...

Deep learning with 3D data such as reconstructed point clouds and CAD models has received great research interests recently. However, the capability of using point clouds with convolutional neural network has been so far not fully explored. In this paper, we present a convolutional neural network for semantic segmentation and object recognition with 3D point clouds. At the core of our network i...

Convolutional neural networks (CNNs), in a few decades, have outperformed the existing state of art methods classification context. However, way they were formalised, CNNs are bound to operate on euclidean spaces. Indeed, convolution is signal operation that defined This has restricted deep learning main use euclidean-defined data such as sound or image. And yet, numerous computer application f...

Abstract. In the present paper, we solve three boundary value problems related to the temperature field in oil strata – the fractional extensions of the incomplete lumped formulation and lumped formulation in the linear case and the fractional generalization of the incomplete lumped formulation in the radial case. By using the Caputo differintegral operator and the Laplace transform, the soluti...

This paper proposes a time optimal path planning while considering the physical constraints of wheeled mobile robots along a high curvature Bezier curve. The proposed algorithm overcomes drawbacks of preceding results. A trajectory produced through acceleration limits showed long traveling time, non-uniform sampling time and unsatisfied terminal velocity. A convolution-based method to consider ...

Uniform asymptotic confidence bands for a multivariate regression function in an in-verse regression model with a convolution-type operator are constructed. The results arederived using strong approximation methods and a limit theorem for the supremum of astationary Gaussian field over an increasing system of sets. As a particular applicationasymptotic confidence bands for a...

In this paper, we present a multiscale “squiral" (square spiral) image processing (SIP) framework. An efficient spiral addressing scheme is deployed for standard pixel based square images to facilitate fast image processing. A SIP-based convolution technique is developed by simulating the “eye tremor" phenomenon of the human visual system. The multiscale SIP operators are constructed by convert...