Another improved Wei–Yao–Liu nonlinear conjugate gradient method with sufficient descent property

Dai, Zhifeng; Wen, Fenghua

doi:10.1016/j.amc.2011.12.091

Cited by 55 publications

(51 citation statements)

References 19 publications

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“…In numerical result we compare the three-term BZAU method with TMPRP1 method [32]. As in [32] the TMPRP1 method is shown to be numerically efficient when it comes to comparison with other two robust methods such as CG Descent method [41] and DTPRP method [42]. That is the reason for comparing our BZAU method with TMPRP1 method.…”

Section: Resultsmentioning

confidence: 99%

A New Modified Three-Term Conjugate Gradient Method with Sufficient Descent Property and Its Global Convergence

Baluch

Salleh

Alhawarat

et al. 2017

Journal of Mathematics

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A new modified three-term conjugate gradient (CG) method is shown for solving the large scale optimization problems. The idea relates to the famous Polak-Ribière-Polyak (PRP) formula. As the numerator of PRP plays a vital role in numerical result and not having the jamming issue, PRP method is not globally convergent. So, for the new three-term CG method, the idea is to use the PRP numerator and combine it with any good CG formula's denominator that performs well. The new modification of three-term CG method possesses the sufficient descent condition independent of any line search. The novelty is that by using the Wolfe Powell line search the new modification possesses global convergence properties with convex and nonconvex functions. Numerical computation with the Wolfe Powell line search by using the standard test function of optimization shows the efficiency and robustness of the new modification.

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Section: Resultsmentioning

confidence: 99%

A New Modified Three-Term Conjugate Gradient Method with Sufficient Descent Property and Its Global Convergence

Baluch

Salleh

Alhawarat

et al. 2017

Journal of Mathematics

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“…In [23] relied on WYL to suggest a new conjugate gradient method, NPRP, and he proved that the NPRP method satisfied descent condition and the Global convergence property under strong Wolfe line search. Subsequently, in [24] introduced an improved NPRP method known as the DPRP method. In this section, enlightened by previous ideas [22][23][24], we propose our which known as .…”

Section: New Formula For and Its Propertiesmentioning

confidence: 99%

Solving a large scale nonlinear unconstrained optimization problems by using new coefficient of conjugate gradient method with exact line search direction

Alkouli¹,

Mamat²,

Rivaie³

et al. 2018

IJET

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In this paper, an efficient modification of nonlinear conjugate gradient method and an associated implementation, based on an exact line search, are proposed and analyzed to solve large-scale unconstrained optimization problems. The method satisfies the sufficient descent property. Furthermore, global convergence result is proved. Computational results for a set of unconstrained optimization test problems, some of them from CUTE library, showed that this new conjugate gradient algorithm seems to converge more stable and outperforms the other similar methods in many situations.

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“…0.20 2 (27) to estimate the parameters of this system, the parameter estimates and their errors are shown in Table 1 and Fig. 3 with the data length L e = 2,000, where the parameter estimation errors are defined by δ := θ k − θ / θ .…”

Section: Examplesmentioning

confidence: 99%

“…The stochastic gradient (SG) algorithms include the conjugate gradient algorithms [2], the alternative gradient algorithms [41], the gradient projection algorithms [1], and the steepest descent algorithms [20]. Two typical algorithms are the multi-innovation SG algorithm and the gradient-based iterative algorithm [8,10].…”

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confidence: 99%

Gradient-Based Parameter Identification Algorithms for Observer Canonical State Space Systems Using State Estimates

Ding

2014

Circuits Syst Signal Process

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This paper considers the parameter identification problem of the state space observer canonical model for linear stochastic systems, and proposes a Kalman filterbased gradient iterative algorithm and an observer-based multi-innovation stochastic gradient algorithm. The fundamental idea is to replace the unmeasurable states in the information vector with the estimated states and to compute the states of the systems through the Kalman filter or the state observer using the previous parameter estimates. Examples are provided to confirm the effectiveness of the proposed algorithms.

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Another improved Wei–Yao–Liu nonlinear conjugate gradient method with sufficient descent property

Cited by 55 publications

References 19 publications

A New Modified Three-Term Conjugate Gradient Method with Sufficient Descent Property and Its Global Convergence

A New Modified Three-Term Conjugate Gradient Method with Sufficient Descent Property and Its Global Convergence

Solving a large scale nonlinear unconstrained optimization problems by using new coefficient of conjugate gradient method with exact line search direction

Gradient-Based Parameter Identification Algorithms for Observer Canonical State Space Systems Using State Estimates

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