We give an algorithm to compute N steps of a convolution quadrature approximation to a continuous temporal convolution using only O(N logN) multiplications and O(logN) active memory. The method does not require evaluations of the convolution kernel, but instead O(logN) evaluations of its Laplace transform, which is assumed sectorial. The algorithm can be used for the stable numerical solution w...

in this paper, we defined two classes $s_{p}^{ast }(n,lambda ,a,b)$ and $ k_{p}(n,lambda ,a,b)$ of meromorphic $p-$valent functions associated with a new linear operator. we obtained convolution properties for functions in these classes.

In this paper, we investigate periodic solutions of linear and nonlinear discrete Volterra equations of convolution or non-convolution type with unbounded memory. For linear discrete Volterra equations of convolution type, we establish Fredholm’s alternative theorem and for equations of non-convolution type, and we prove that a unique periodic solution exists for a particular bounded initial fu...

For gambles—non-numerical consequences attached to uncertain chance events—analogues are proposed for the sum of independent random variables and their convolution. Joint receipt of gambles is the analogue of the sum of random variables. Because it has no unique expansion as a first-order gamble analogous to convolution, a definition of qualitative convolution is proposed. Assuming ranked, weig...

We present new methods to approximate the offset and convolution of planar curves. These methods can be used as fundamental tools in various geometric applications such as NC machining and collision detection of planar curved objects. Using quadratic curve approximation and tangent field matching, the offset and convolution curves can be approximated by polynomial or rational curves within the ...

In this article, we propose a method for computing convolution of large 3D images. The convolution is performed in a frequency domain using a convolution theorem. The algorithm is accelerated on a graphic card by means of the CUDA parallel computing model. Convolution is decomposed in a frequency domain using the decimation in frequency algorithm. We pay attention to keeping our approach effici...