In this article we present the multivariate approximation of time splitting random functions defined on a box or RN,N∈N, by neural network operators quasi-interpolation type. We achieve these approximations obtaining quantitative-type Jackson inequalities engaging modulus continuity related function its partial high-order derivatives. use density to define our operators. These derive from logis...

In deep learning models, the inputs to network are processed using activation functions generate output corresponding these inputs. Deep models of particular importance in analyzing big data with numerous parameters and forecasting useful for image processing, natural language object recognition, financial forecasting. Also, algorithms, have been developed by taking into account features such a...

This study proposes novel Long Short-Term Memory (LSTM)-based classifiers through developing the internal structure of LSTM neural networks using 26 state activation functions as alternatives to traditional hyperbolic tangent (tanh) function. The have high performance in solving vanishing gradient problem that is observed recurrent networks. Performance investigations were carried out utilizing...

Tangent measure distributions were introduced by Bandt 2] and Graf 8] as a means to describe the local geometry of self-similar sets generated by iteration of contractive similitudes. In this paper we study the tangent measure distributions of hyperbolic Cantor sets generated by certain contractive mappings, which are not necessarily similitudes. We show that the tangent measure distributions o...

A.1. Slow Slip Episodes In this section, we discuss the relevant information for identification of slow slip episodes, with additional details presented elsewhere (Holtkamp et al., 2006, ms. in prep.). The GPS data analyzed for slow slip episodes is from the PANGA network provided by the Central Washington University clearinghouse (2005). PANGA time series are network solutions with phase ambig...

Abstract We provide optimal bounds for the sine and hyperbolic tangent means in terms of various weighted arithmetic centroidal

In Euclidean geometry, it is well-known that the k-order Voronoi diagram in R can be computed from the vertical projection of the k-level of an arrangement of hyperplanes tangent to a convex potential function in R: the paraboloid. Similarly, we report for the Klein ball model of hyperbolic geometry such a concave potential function: the northern hemisphere. Furthermore, we also show how to bui...

The psychometric function's slope provides information about the reliability of psychophysical threshold estimates. Furthermore, knowing the slope allows one to compare, across studies, thresholds that were obtained at different performance criterion levels. Unfortunately, the empirical validation of psychometric function slope estimates is hindered by the bewildering variety of slope measures ...