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algorithm steps » algorithm its (Expand Search)
algorithm wave » algorithm novel (Expand Search), algorithm fa (Expand Search), algorithm a (Expand Search)
wave function » taste function (Expand Search)
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Brain Source Localization in the Presence of Leadfield Perturbations
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A New Penalty Function Algorithm For Convex Quadratic Programming
Published 2020“…In this paper, we develop an exterior point algorithm for convex quadratic programming using a penalty function approach. …”
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Kernel-Ridge-Regression-Based Randomized Network for Brain Age Classification and Estimation
Published 2024“…Effective and reliable assessment methods are required to accurately classify and estimate brain age. In this study, a brain age classification and estimation framework is proposed using structural magnetic resonance imaging (sMRI) scans, a 3-D convolutional neural network (3-D-CNN), and a kernel ridge regression-based random vector functional link (KRR-RVFL) network. …”
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Adaptive step-size sign least mean squares
Published 2004“…A powerful adaptation scheme is used to adapt the step-size of the sign function inside the recursion of the sign algorithm. …”
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On the Optimization of Band Gaps in Periodic Waveguides
Published 2025“…<h3 dir="ltr">Purpose</h3><p dir="ltr">This work applies a computational framework for vibration attenuation in periodic structures by combining the established wave and finite element (WFE) method with nature-inspired optimization algorithms. …”
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Design of an innovative and self-adaptive-smart algorithm to investigate the structural integrity of a rail track using Rayleigh waves emitted and sensed by a fully non-contact las...
Published 2020“…In view of this, an innovative signal processing technique called a self-adaptive-smart algorithm (SASA) was designed and developed. In SASA, the incident wave that is the first coming wave-packet is taken as a mother wavelet. …”
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DRL-Based IRS-Assisted Secure Hybrid Visible Light and mmWave Communications
Published 2024“…Within the system, both sheets function as IRS. The aim is to enhance the secrecy capacity (SC) of the system by optimizing the beamforming weights at the VLC fixtures, the beamforming weights at the mmWave AP, the mirror array configurations, and the phase shift vector while meeting specific power constraints. …”
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Autism Detection of MRI Brain Images Using Hybrid Deep CNN With DM-Resnet Classifier
Published 2023“…Earlier diagnosis of ASD from brain image is necessary for reducing the effect of disorder. …”
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Optimization of Support Structures for Offshore Wind Turbines using Genetic Algorithm with Domain-Trimming (GADT)
Published 2017“…These constraints are managed via dynamically modified, nonstationary penalty functions. The structures are subject to gravity, wind, wave, and earthquake loading conditions. …”
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Tracking analysis of normalized adaptive algorithms
Published 2003“…Close agreement between analytical analysis and simulation results is obtained for the case of the NLMS algorithm. The results show that, unlike the stationary case, the steady-state excess-mean-square error is not a monotonically increasing function of the step-size, while the ability of the adaptive algorithm to track the variations in the environment degrades by increasing the frequency offset.…”
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A Comparative Study of Elgamal Based Cryptographic Algorithms
Published 2004“…In this work we implement the classical and modified ElGamal cryptosystem to compare and to test their functionality, reliability and security. To test the security of the algorithms we use a famous attack algorithm called Baby-Step-Giant algorithm which works in the domain of natural integers. …”
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Genetic and heuristic algorithms for regrouping service sites. (c2000)
Published 2000Get full text
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Convergence analysis of the variable weight mixed-norm LMS-LMFadaptive algorithm
Published 2000“…In this work, the convergence analysis of the variable weight mixed-norm LMS-LMF (least mean squares-least mean fourth) adaptive algorithm is derived. The proposed algorithm minimizes an objective function defined as a weighted sum of the LMS and LMF cost functions where the weighting factor is time varying and adapts itself so as to allow the algorithm to keep track of the variations in the environment. …”
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Tracking analysis of the NLMS algorithm in the presence of both random and cyclic nonstationarities
Published 2003“…The results show that, unlike in the stationary case, the steady-state excess MSE is not a monotonically increasing function of the step size. Moreover, the ability of the adaptive algorithm to track the variations in the environment is shown to degrade with increasing frequency offset.…”
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A comparative study of ElGamal based digital signature algorithms
Published 2006“…We implement the classical and modified ElGamal digital signature scheme to compare and to test their functionality, reliability and security. To test the security of the algorithms we use a famous attack algorithm called Baby-Step-Giant algorithm which works in the domain of natural integers. …”
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