2018
DOI: 10.3390/s19010074
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Rejecting Chaotic Disturbances Using a Super-Exponential-Zeroing Neurodynamic Approach for Synchronization of Chaotic Sensor Systems

Abstract: Due to the existence of time-varying chaotic disturbances in complex applications, the chaotic synchronization of sensor systems becomes a tough issue in industry electronics fields. To accelerate the synchronization process of chaotic sensor systems, this paper proposes a super-exponential-zeroing neurodynamic (SEZN) approach and its associated controller. Unlike the conventional zeroing neurodynamic (CZN) approach with exponential convergence property, the controller designed by the proposed SEZN approach in… Show more

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Cited by 44 publications
(14 citation statements)
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“…Compared to other EAs, the PSO algorithm has the greatest advantages in terms of its simplicity to implement, fewer parameters to adjust, and no gradient information. Hence, it is widely used in function optimization, neural network training [32], and so on. A great many experiments show that PSO is able to solve a range of optimization problems that genetic algorithms can solve.…”
Section: Hi-bqpso a Preliminarymentioning
confidence: 99%
“…Compared to other EAs, the PSO algorithm has the greatest advantages in terms of its simplicity to implement, fewer parameters to adjust, and no gradient information. Hence, it is widely used in function optimization, neural network training [32], and so on. A great many experiments show that PSO is able to solve a range of optimization problems that genetic algorithms can solve.…”
Section: Hi-bqpso a Preliminarymentioning
confidence: 99%
“…As an important subtopic of recurrent neural network, the Zhang neural network (ZNN) was firstly proposed by Zhang Yunong on March 2001 [1]. In recent years, ZNN has been generally deemed as a benchmark solver for various dynamics systems appeared in practice, such as the robots' kinematic control, the pendulum system [8], the synchronization of chaotic sensor systems [9]. Based on a simple ordinary differential equation (ODE), i.e., the test problem to analyze the stability property of a numerical method for initial value problem, for the ZNN every component of an indefinite error function directly exponentially tends to zero, which endows ZNN with the ability to track the time-dependent solution of time-varying problems in an error-free manner.…”
Section: Introductionmentioning
confidence: 99%
“…For example, for potential digital hardware realization, several multi-step discrete-time ZNNs have been designed in [10][11][12][13]. To accelerate the convergence speed of the ZNN, a super-exponential ZNN with time-varying design parameter is proposed by Chen et al [9]. Moreover, based on some deliberated designed activation functions, many continuous-time ZNNs with finite-time convergence property have been presented [14,15].…”
Section: Introductionmentioning
confidence: 99%
“…The time complexity of such algorithms is described by a polynomial equation and are generally time-consuming, therefore most of these types of algorithms are used in offline planning. The fourth category is bio-heuristic algorithms, including neural networks (NN) [19], genetic algorithm (GA) [20], particle swarm optimization (PSO) [21], ant colony optimization (ACO) algorithm [22] and hybrid leapfrog optimization [23]. These types of path planning have a time complexity of O(n2), which can only be applied in static environments for offline path planning.…”
Section: Introductionmentioning
confidence: 99%