Results 41 to 50 of about 888,833 (294)
A New Modified Conjugate Gradient for Nonlinear Minimization Problems
Science Journal of University of Zakho, 2022 The conjugate gradient is a highly effective technique to solve the unconstrained nonlinear minimization problems and it is one of the most well-known methods. It has a lot of applications.
Hussein Ageel Khatab, Salah G. Sharef
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A new hybrid conjugate gradient method for dynamic force reconstruction
Advances in Mechanical Engineering, 2019 A new hybrid conjugate gradient method is proposed in this article based on the gradient operator and applied to the structural dynamic load identification problem.
Linjun Wang +4 more
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FEBS Letters, EarlyView.We present robust protocols for the preparation of supported lipid bilayers (SLBs) incorporating either Salmonella smooth LPS or outer membrane vesicles (OMVs). We use a combination of quartz crystal microbalance with dissipation (QCM‐D) and fluorescence microscopy to both characterize the SLBs of various compositions and to probe their interactions ...
Hudson P. Pace +6 more
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A Novel hybridization of CG-techniques for Solving Unconstrained Optimization Problems
Wasit Journal for Pure SciencesConjugate gradient methods are an extremely helpful way for handling large scale non-linear optimization issues. In this paper, based on the three famous Dai-yuan (DY), Liu–Storey (LS)and Conjugate-Descent (CD) conjugate gradient methods, a new hybrid ...
Hawraz Jabbar
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IEEE Access, 2020 To accelerate the scanning speed of magnetic resonance imaging (MRI) and improve the quality of magnetic resonance (MR) image reconstruction, a fast MRI technology based on compressed sensing is proposed.
Xiuhan Li +4 more
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Spectral CG Algorithm for Solving Fuzzy Non-linear Equations
Iraqi Journal for Computer Science and Mathematics, 2022 The non-linear conjugate gradient method is a very effective technique for addressing Large-Scale minimization problems, and it has a wide range of applications in Mathematics, Chemistry, Physics, Engineering, and Medicine, etc.
Mezher M. Abed +2 more
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Predict-and-Recompute Conjugate Gradient Variants [PDF]
SIAM Journal on Scientific Computing, 2020 The standard implementation of the conjugate gradient algorithm suffers from communication bottlenecks on parallel architectures, due primarily to the two global reductions required every iteration. In this paper, we study conjugate gradient variants which decrease the runtime per iteration by overlapping global synchronizations, and in the case of ...
Tyler Chen, Erin Carson
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Investigating transcription factor dynamics in health and disease using FRAP
FEBS Letters, EarlyView.FRAP analysis of GFP‐tagged transcription factors reveals how molecular mobility and target engagement change in response to drug treatment. By combining live‐cell imaging, quantitative model fitting, and statistical analysis, this approach uncovers transcription factor dynamics linked to disease mechanisms, providing a powerful framework for ...
Kannan Govindaraj +3 more
wiley +1 more source
An imperfect conjugate gradient algorithm [PDF]
, 1952 summary:A new biorthogonalization algorithm is defined which does not depend on the step-size used. The algorithm is suggested so as to minimize the total error after $n$ steps if imperfect steps are used.
Sloboda, Fridrich +2 more
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Conjugate Gradient Methods for Toeplitz Systems [PDF]
SIAM Review, 1996 The use of preconditioned conjugate gradient methods to solve linear systems of equations with Toeplitz matrices is discussed. Using this iterative method, the complexity is reduced from \(O(n\log^2n)\) operations for fast direct Toeplitz solvers to \(O(n \log n)\).
Raymond H. Chan, Michael K. Ng 0001
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