A hyperchaotic map with multi-elliptic cavities based on modulation and coupling

Wu, Chenyang; Sun, Kehui; Xiao, Yan

doi:10.1140/epjs/s11734-021-00126-9

Cited by 12 publications

(8 citation statements)

References 28 publications

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“…Given that the initial positions of the black widow population are randomly generated, the study employs chaotic initialization using the Sine function from the chaos mapping strategy ( Wu et al, 2021 ). This improves the quality of initial solutions, ensuring a more uniform distribution of the population within the search space.…”

Section: Methodsmentioning

confidence: 99%

Research on the method of identifying upper and lower limb coordinated movement intentions based on surface EMG signals

Feng,

Yu,

Dong

et al. 2024

Front. Bioeng. Biotechnol.

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Rehabilitation robots have gained considerable focus in recent years, aiming to assist immobilized patients in regaining motor capabilities in their limbs. However, most current rehabilitation robots are designed specifically for either upper or lower limbs. This limits their ability to facilitate coordinated movement between upper and lower limbs and poses challenges in accurately identifying patients’ intentions for multi-limbs coordinated movement. This research presents a multi-postures upper and lower limb cooperative rehabilitation robot (U-LLCRR) to address this gap. Additionally, the study proposes a method that can be adjusted to accommodate multi-channel surface electromyographic (sEMG) signals. This method aims to accurately identify upper and lower limb coordinated movement intentions during rehabilitation training. By using genetic algorithms and dissimilarity evaluation, various features are optimized. The Sine-BWOA-LSSVM (SBL) classification model is developed using the improved Black Widow Optimization Algorithm (BWOA) to enhance the performance of the Least Squares Support Vector Machine (LSSVM) classifier. Discrete movement recognition studies are conducted to validate the exceptional precision of the SBL classification model in limb movement recognition, achieving an average accuracy of 92.87%. Ultimately, the U-LLCRR undergoes online testing to evaluate continuous motion, specifically the movements of “Marching in place with arm swinging”. The results show that the SBL classification model maintains high accuracy in recognizing continuous motion intentions, with an average identification rate of 89.25%. This indicates its potential usefulness in future rehabilitation robot-active training methods, which will be a promising tool for a wide range of applications in the fields of healthcare, sports, and beyond.

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Section: Methodsmentioning

confidence: 99%

Research on the method of identifying upper and lower limb coordinated movement intentions based on surface EMG signals

Feng,

Yu,

Dong

et al. 2024

Front. Bioeng. Biotechnol.

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“…Using chaotic sequences for population initialization, selection, crossover and mutation will affect the whole process of the algorithm and usually achieve better results than pseudorandom numbers [52]. Chaotic mapping commonly used in the field of intelligent optimization includes Logistic-Sine mapping [53], Tent mapping [54], Chebyshev mapping [55], ICMIC mapping [56], and Cubic mapping [57], etc. To analyze the chaotic properties of the above six one-dimensional chaotic graphs, their bifurcation diagrams are plotted separately, as shown in figure 5.…”

Section: Chaotic Mapmentioning

confidence: 99%

Fault diagnosis in asynchronous motors based on an optimal deep bidirectional long short-term memory networks

Xu,

Li,

Liu

et al. 2023

Meas. Sci. Technol.

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Fault diagnosis of asynchronous motors has become a pressing need in the metallurgical industry. Due to the complex structure of asynchronous motors, fault types and fault characteristics are diverse, with strong nonlinear relationships between them, which leads to the difficulty of fault diagnosis. To efficiently and accurately diagnose various motor faults, we propose a fault diagnosis method based on an optimal deep bidirectional long short-term memory neural network. First, the three-phase current, multidimensional vibrational signal, and acoustic signal of the asynchronous motor are collected and construct diverse and robust data sample set to enhance the generalization ability of the model. Next, a modified 3D logistics-sine complex chaotic map (3D LSCCM) is constructed to improve the global and local search capabilities of the pigeon swarm optimization algorithm (PIO). Then, we construct a deep bidirectional long short-term memory network (Bid-LSTM) with attention mechanism to mine high-value fault characteristic information. Meanwhile, the optimal hyper-parameters of the deep ABid-LSTM are explored using the modified PIO to improve the training performance of the model. Finally, the fault data samples of asynchronous motor are induced to train and test the proposed framework. By fusing diverse data samples, the proposed method outperforms conventional deep Bid-LSTM and achieves fault diagnosis accuracy of 99.13%. It provides a novel diagnostic strategy for motor fault diagnosis.

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“…The more variables and parameters, the larger the key space of the high-dimensional chaotic map and the more complex the structure. At the same time, orbit estimation and parameter prediction are more difficult, so they are more suitable for cryptography applications and secure communications [27,28]. Motivated by the above analysis, we construct a class of fractional-order highdimensional hyperchaotic maps based on Gauss maps to explore more complex dynamics.…”

Section: Introductionmentioning

confidence: 99%

A class of fractional-order discrete map with multi-stability and its digital circuit realization

Liu¹,

Mou²,

Jahanshahi³

et al. 2022

Phys. Scr.

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In this paper, a class of nonlinear functions and Gaussian function are modulated to construct a new high-dimensional discrete map. Based on Caputo fractional-order difference definition, the fractional form of the map is given, and its dynamical behaviors are explored. The three discrete maps with different nonlinear functions are compared and analyzed by bifurcation diagrams and Lyapunov exponents, especially the dynamical phenomena that evolve with the order. In addition, the maps have multiple rich stability, including homogeneous and heterogeneous coexistence attractors and hyperchaos coexistence attractors. The spectral entropy (SE) algorithm is used to measure the complexity of one-dimensional and two-dimensional maps. Performance tests show that the fractional-order map has more complex dynamics than the original map. Finally, the new maps were successfully implemented on the digital platform, which shows the simplicity and feasibility of the map implementation. The experimental results provide a reference for the research on the multi-stability of fractional discrete maps.

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A hyperchaotic map with multi-elliptic cavities based on modulation and coupling

Cited by 12 publications

References 28 publications

Research on the method of identifying upper and lower limb coordinated movement intentions based on surface EMG signals

Research on the method of identifying upper and lower limb coordinated movement intentions based on surface EMG signals

Fault diagnosis in asynchronous motors based on an optimal deep bidirectional long short-term memory networks

A class of fractional-order discrete map with multi-stability and its digital circuit realization

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