In this study we consider general linear second-order partial differential equations and we solve three fundamental equations by replacing the non-homogeneous terms with double convolution functions and data by a single convolution.

Using convolution, classes of p-valent functions with respect to symmetric conjugate points are introduced. Integral representation and closure properties under convolution of general classes with respect to (2j, k) symmetric points are investigated. AMS (MOS) Subject Classification Codes: 30C45

In this paper we consider how to use the convolution method to construct approximations, which consist of fuzzy numbers sequences with good properties, for a general fuzzy number. It shows that this convolution method can generate differentiable approximations in finite steps for fuzzy numbers which have finite nondifferentiable points. In the previous work, this convolution method only can be ...

where φ :Rn → C and φt(x)= t−nφ(x/t), t > 0. For conditions of validity of identity (1.1), we may refer to [3]. Hankel convolution introduced by Hirschman Jr. [5] related to the Hankel transform was studied at length by Cholewinski [1] and Haimo [4]. Its distributional theory was developed byMarrero and Betancor [6]. Pathak and Pandey [8] used Hankel convolution in their study of pseudodifferen...

Multipath fading is a major problem of the wireless communication channel. To eliminate this fading problem and to have reliable communications in wireless channel, channel coding techniques are used. In this paper BER (bit error rate) performance is shown, by the means of Rayleigh and Rician multipath fading channels. Here the convolution encoding is used. The performance of convolution encode...

Convolution is one of the most widely used digital signal processing operations. This work aims to distribute twodimensional convolution operation across Intel’s Single-Chip Cloud Computer (SCC), an experimental processor created by Intel Labs. This platform enables experiments with varying both the data sizes and the physical parameters of the platform such as voltage, frequency, and number of...

Signal processing and pattern recognition algorithms make extensive use of convolution. In many cases, computational accuracy is not as important as computational speed. In feature extraction, for instance, the features of interest in a signal are usually quite distorted. This form of noise justi es some level of quantization in order to achieve faster feature extraction. Our approach consists ...

in this paper, we introduce new classes $sum_{k,p,n}(alpha ,m,lambda ,l,rho )$ and $mathcal{t}_{k,p,n}(alpha ,m,lambda ,l,rho )$ of p-valent meromorphic functions defined by using the extended multiplier transformation operator. we use a strong convolution technique and derive inclusion results. a radius problem and some other interesting properties of these classes are discussed.

In this paper, we give a fundamental convexity preserving for spectral functions. Indeed, we investigate infimal convolution, Moreau envelope and proximal average for convex spectral functions, and show that this properties are inherited from the properties of its corresponding convex function. This results have many applications in Applied Mathematics such as semi-definite programmings and eng...