Results 41 to 50 of about 45,363 (158)
A Class of Power Series q-Distributions
MathematicsA class of power series q-distributions, generated by considering a q-Taylor expansion of a parametric function into powers of the parameter, is discussed. Its q-factorial moments are obtained in terms of q-derivatives of its series (parametric) function.
Charalambos A. Charalambides
doaj +1 more source
Time inhomogeneous quantum dynamical maps
Scientific Reports, 2022 We discuss a wide class of time inhomogeneous quantum evolution which is represented by two-parameter family of completely positive trace-preserving maps. These dynamical maps are constructed as infinite series of jump processes.
Dariusz Chruściński
doaj +1 more source
Convolution Operators on Holomorphic Dirichlet Series
Tokyo Journal of Mathematics, 1997 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire +3 more sources
Shifted convolution L-series values for elliptic curves [PDF]
Archiv der Mathematik, 2018 Journal ...
Ali, Asra, Mani, Nitya
openaire +3 more sources
Optimization Method for Convolutional Computing Based on Vector Transformation [PDF]
Jisuanji gongchengTo solve efficiency problems in convolution calculations, this paper proposes a convolution calculation optimization method OAC. The objective is to improve the efficiency of convolution calculations to address the increasing demand for high convolution ...
WANG Peiji, ZOU Chengming
doaj +1 more source
The Convolution on Time Scales
Abstract and Applied Analysis, 2007 The main theme in this paper is an initial value problem containing a dynamic version of the transport equation. Via this problem, the delay (or shift) of a function defined on a time scale is introduced, and the delay in turn is used to introduce the ...
Martin Bohner, Gusein Sh. Guseinov
doaj +1 more source
CONVOLUTION SUMS AND THEIR RELATIONS TO EISENSTEIN SERIES [PDF]
Bulletin of the Korean Mathematical Society, 2013 In this paper, we consider several convolution sums, namely, Ai(m;n; N) (i = 1; 2; 3; 4), Bj(m;n;N) (j = 1; 2; 3), and Ck(m;n;N) (k = 1; 2; 3;:::, 12), and establish certain identities involving their nite products. Then we extend these types of product convolution identities to products involving Faulhaber sums.
Daeyeoul Kim +2 more
openaire +1 more source
Correlating Time Series With Interpretable Convolutional Kernels
IEEE Transactions on Knowledge and Data EngineeringThis study addresses the problem of convolutional kernel learning in univariate, multivariate, and multidimensional time series data, which is crucial for interpreting temporal patterns in time series and supporting downstream machine learning tasks.
Xinyu Chen 0002 +3 more
openaire +2 more sources
Journal of Measurement Science and Instrumentation, 2022 In view of the problems of multi-scale changes of segmentation targets, noise interference, rough segmentation results and slow training process faced by medical image semantic segmentation, a multi-scale residual aggregation U-shaped attention network ...
SHAO Shuo, GE Hongwei
doaj
Time series clustering with random convolutional kernels
Data Mining and Knowledge DiscoveryAbstractTime series data, spanning applications ranging from climatology to finance to healthcare, presents significant challenges in data mining due to its size and complexity. One open issue lies in time series clustering, which is crucial for processing large volumes of unlabeled time series data and unlocking valuable insights.
Jorge Marco-Blanco, Rubén Cuevas
openaire +4 more sources