Wyniki wyszukiwania - BazTech

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Inertial shrinking projection algorithm with self-adaptive step size for split generalized equilibrium and fixed point problems for a countable family of nonexpansive multivalued mappings

Olona Musa A., Alakoya Timilehin O., Owolabi Abd-semii O.-E., Mewomo Oluwatosin T.

Demonstratio Mathematica

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2021

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Vol. 54, nr 1

47--67

EN

In this paper, we introduce a shrinking projection method of an inertial type with self-adaptive step size for finding a common element of the set of solutions of a split generalized equilibrium problem and the set of common fixed points of a countable family of nonexpansive multivalued mappings in real Hilbert spaces. The self-adaptive step size incorporated helps to overcome the difficulty of having to compute the operator norm, while the inertial term accelerates the rate of convergence of the proposed algorithm. Under standard and mild conditions, we prove a strong convergence theorem for the problems under consideration and obtain some consequent results. Finally, we apply our result to solve split mixed variational inequality and split minimization problems, and we present numerical examples to illustrate the efficiency of our algorithm in comparison with other existing algorithms. Our results complement and generalize several other results in this direction in the current literature.

2

Two modifications of the inertial Tseng extragradient method with self-adaptive step size for solving monotone variational inequality problems

Alakoya Timilehin Opeyemi, Jolaoso Lateef Olakunle, Mewomo Oluwatosin Temitope

Demonstratio Mathematica

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2020

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Vol. 53, nr 1

208--224

EN

In this work, we introduce two new inertial-type algorithms for solving variational inequality problems (VIPs) with monotone and Lipschitz continuous mappings in real Hilbert spaces. The first algorithm requires the computation of only one projection onto the feasible set per iteration while the second algorithm needs the computation of only one projection onto a half-space, and prior knowledge o fthe Lipschitz constant of the monotone mapping is not required in proving the strong convergence theorems for the two algorithms. Under some mild assumptions, we prove strong convergence results for the proposed algorithms to a solution of a VIP. Finally, we provide some numerical experiments to illustrate the efficiency and advantages of the proposed algorithms.

3

Synchronization analysis of inertial memristive neural networks with time-varying delays

Wei R., Cao J.

Journal of Artificial Intelligence and Soft Computing Research

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2018

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Vol. 8, No. 4

269--282

EN

This paper investigates the global exponential synchronization and quasi-synchronization of inertial memristive neural networks with time-varying delays. By using a variable transmission, the original second-order system can be transformed into first-order differential system. Then, two types of drive-response systems of inertial memristive neural networks are studied, one is the system with parameter mismatch, the other is the system with matched parameters. By constructing Lyapunov functional and designing feedback controllers, several sufficient conditions are derived respectively for the synchronization of these two types of drive-response systems. Finally, corresponding simulation results are given to show the effectiveness of the proposed method derived in this paper.

4

Inertial Navigation Static Calibration

Niespodziany S.

International Journal of Electronics and Telecommunications

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2018

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Vol. 64, No. 2

243--248

EN

Inertial navigation is a device, which estimates its position, based on sensing external conditions (such as acceleration or angular velocity). It is widely used in various applications. Its presence in a drone vehicle for example, allows flight stabilization, by position estimation and feedback-based regulation algorithm execution. A smartphone makes a use of inertial navigation by detecting movement and flipping screen orientation. It is a ubiquitous part of many devices of everyday use, but before using filters and algorithms allowing to calculate the position, a calibration must first be applied to the device. This paper focuses on a separate calibration of each of the sensors - an accelerometer, gyroscope and magnetometer. The further step requires a cross-sensor calibration, and the third step is implementation of data filtration algotithm.

5

Adaptive Filter for Inertial Systems

Orzyłowski M.

Journal of Applied Computer Science Methods

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2013

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Vol. 5 No. 1

5--15

EN

The stochastic model of the disturbances handled by Kalman filters and the necessity of accurate identification of the dynamic model of the controlled system or process bring about a significant limitation of use of Kalman filters in practice. The paper presents filter designed for inertial systems whose models and control signals are not well known or are beyond description. The assumptions leading to a significant simplification of Kalman algorithm are described. On this basis, the algorithm with an experimentally matched parameter for the filter properties modification is introduced. An example of effective adaptive filtration is presented also.