Zobrazeno 1 - 10
of 27 226
pro vyhledávání: '"Gradient Descent"'
Publikováno v:
River, Vol 3, Iss 4, Pp 399-407 (2024)
Abstract The Water Cloud Model (WCM) plays a crucial role in active microwave soil moisture inversion applications. Empirical parameters are important factors affecting the accuracy of WCM simulation, but the current evaluation of empirical parameter
Externí odkaz:
https://doaj.org/article/2edd4e5f2df0429dbd23fbbe2c6cb978
Publikováno v:
AIMS Mathematics, Vol 9, Iss 12, Pp 33401-33422 (2024)
Composite sparsity generalizes the standard sparsity that considers the sparsity on a linear transformation of the variables. In this paper, we study the composite sparse optimization problem consisting of minimizing the sum of a nondifferentiable lo
Externí odkaz:
https://doaj.org/article/1a423b6417c842b0a03b578d5b33e60e
Autor:
Mathias M. Nilsen, Andreas S. Stordal, Rolf J. Lorentzen, Patrick N. Raanes, Kjersti S. Eikrem
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-13 (2024)
Abstract We investigate the use of various momentum methods in combination with an ensemble approximation of gradients, for accelerated optimization. Although momentum gradient descent methods are popular in machine learning, it is unclear how they p
Externí odkaz:
https://doaj.org/article/04abd20f666f4513a1d7ead1bd06921f
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 18, Pp 2042-2051 (2025)
Tomographic synthetic aperture radar (TomoSAR) has garnered significant attention recently due to its 3-D imaging capabilities. However, interchannel phase errors present in practical applications severely degrade the quality of 3-D reconstruction re
Externí odkaz:
https://doaj.org/article/ae21b8a0a6f644bcb060416aca523ed0
Autor:
Edisanter Lo
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 18, Pp 1718-1733 (2025)
Conventional algorithms for subpixel target detection of a rare target in hyperspectral imaging are derived from the generalized likelihood ratio test. Artificial neural networks are designed for classification, which needs large samples of pixels fo
Externí odkaz:
https://doaj.org/article/46d1226af5f640688870cfed836c45b3
Autor:
Kose, Oguz
Publikováno v:
Aircraft Engineering and Aerospace Technology, 2024, Vol. 96, Issue 5, pp. 669-678.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/AEAT-01-2023-0002
Modified Step Size for Enhanced Stochastic Gradient Descent: Convergence and Experiments
Publikováno v:
Mathematics Interdisciplinary Research, Vol 9, Iss 3, Pp 237-253 (2024)
This paper introduces a novel approach to enhance the performance of the stochastic gradient descent (SGD) algorithm by incorporating a modified decay step size based on $\frac{1}{\sqrt{t}}$. The proposed step size integrates a logarithmic t
Externí odkaz:
https://doaj.org/article/b7233bfe54f24bb698c14cf72b658fad
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-16 (2024)
Abstract This paper proposed the additional fractional gradient descent identification algorithm based on the multi-innovation principle for autoregressive exogenous models. This algorithm incorporates an additional fractional order gradient to the i
Externí odkaz:
https://doaj.org/article/359111a6c6654eb7a18bfd8c3c805a0c
Publikováno v:
BMC Bioinformatics, Vol 25, Iss 1, Pp 1-25 (2024)
Abstract Background Copy number variants (CNVs) have become increasingly instrumental in understanding the etiology of all diseases and phenotypes, including Neurocognitive Disorders (NDs). Among the well-established regions associated with ND are sm
Externí odkaz:
https://doaj.org/article/277eae9c344b49e2b20a0136fae4e8a2
Publikováno v:
Frontiers in Human Neuroscience, Vol 18 (2024)
BackgroundApplying convolutional neural networks to a large number of EEG signal samples is computationally expensive because the computational complexity is linearly proportional to the number of dimensions of the EEG signal. We propose a new Gated
Externí odkaz:
https://doaj.org/article/880884c3c0db4845908f574965905be2