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Analysis of Gradient Vanishing of RNNs and Performance Comparison
Information, 2021 A recurrent neural network (RNN) combines variable-length input data with a hidden state that depends on previous time steps to generate output data. RNNs have been widely used in time-series data analysis, and various RNN algorithms have been proposed ...
Seol-Hyun Noh
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Performance Comparison of CNN Models Using Gradient Flow Analysis
Informatics, 2021 Convolutional neural networks (CNNs) are widely used among the various deep learning techniques available because of their superior performance in the fields of computer vision and natural language processing.
Seol-Hyun Noh
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Lacunary statistical convergence [PDF]
Pacific Journal of Mathematics, 1993 The sequence \(x\) is statistically convergent to \(L\) provided that for each \(\varepsilon>0\), \[ \lim_ n {1 \over n} \{\text{the number of } k \leq n:| x_ k-L | \geq \varepsilon\}=0. \] A related concept is introduced by replacing the set \(\{k:k \leq n\}\) with \(\{ k:k_{r-1}
Fridy, J. A., Orhan, C.
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On (f, ρ)−Statistical convergence and strong (f, ρ)−summability of order α [PDF]
E-Journal of Analysis and Applied Mathematics, 2022 The main object of this article is to introduce the concepts of (f, ρ)− statistical convergence of order α and strong (f, ρ)− summability of order α of sequences of real numbers and give some inclusion relations between these spaces.
Hacer Şengül Kandemir +2 more
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On f-strongly Cesàro and f-statistical derivable functions
AIMS Mathematics, 2022 In this manuscript, we introduce the following novel concepts for real functions related to f-convergence and f-statistical convergence: f-statistical continuity, f-statistical derivative, and f-strongly Cesàro derivative.
Bilal Altay +2 more
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Rough statistical convergence in intuitionistic fuzzy normed spaces
Filomat, 2021 In this paper, we have defined rough statistical convergence in intuitionistic fuzzy normed spaces which is an useful characterization in the field of statistical convergence.
Reena Antal +2 more
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ON DISCRETE WEIGHTED STATISTICAL CONVERGENCE [PDF]
Facta Universitatis, Series: Mathematics and Informatics, 2021 In the present paper, the notion of discrete weighted mean method of summability isextended the concept of statistical convergence. We also give the notion of statistical (M,P_{λ})-summability and [M,P_{λ}]_{q}-summability.
Ercan, Sinan +2 more
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Journal of Mathematical Sciences and Modelling, 2019 In this paper, we introduce the concepts of αβ−statistical convergence and strong αβ− summability of double sequences and investigate the relation between these two new concepts. Moreover, statistical convergence and αβ− statistical convergence of double
Selma Altundağ, Bayram Sözbir
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Properties of J_p-Statistical Convergence
Cumhuriyet Science Journal, 2022 In this study, different characterizations of J_p-statistically convergent sequences are given. The main features of J_p-statistically convergent sequences are investigated and the relationship between J_p-statistically convergent sequences and J_p ...
Canan Sümbül +2 more
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Fast global convergence of gradient methods for high-dimensional statistical recovery [PDF]
, 2011 Many statistical $M$-estimators are based on convex optimization problems formed by the combination of a data-dependent loss function with a norm-based regularizer. We analyze the convergence rates of projected gradient and composite gradient methods for
Agarwal, Alekh +2 more
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