On RNN-Based $k$-WTA Models With Time-Dependent Inputs

Liu, Mei; Shang, Mingsheng

doi:10.1109/jas.2022.105932

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Cited by 9 publications

(1 citation statement)

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“…Inspired by this phe-nomenon, an algorithm named WTA is proposed to pick the maxima from all the inputs. A more general form of WTA algorithm is called k-winner-tall-all (k-WTA) [7], [8], which selects k largest values from a group of inputs. As the WTA model is computationally powerful and can generate useful functions needed in many applications, many models have been proposed by researchers to produce the WTA competition.…”

mentioning

confidence: 99%

A Novel Competition-Based Coordination Model with Dynamic Feedback for Multi-Robot Systems

Peng,

Zhang,

Shang

2023

IEEE/CAA J. Autom. Sinica

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mentioning

confidence: 99%

A Novel Competition-Based Coordination Model with Dynamic Feedback for Multi-Robot Systems

Peng,

Zhang,

Shang

2023

IEEE/CAA J. Autom. Sinica

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Noise suppression zeroing neural network for online solving the time-varying inverse kinematics problem of four-wheel mobile manipulators with external disturbances

Sun,

Zhou,

Tang

et al. 2024

Artif Intell Rev

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A novel noise suppression zeroing neural network (NSZNN) is presented for the trajectory tracking problem on a four Mecanum wheeled mobile manipulator (FMWMM) by solving its time-varying inverse kinematics (TVIK) problem. The holistic kinematic model of the FMWMM is developed, which can receive synergistic control of the mobile manipulator. Different from the situation without external interference addressed in our previous work, this paper considers a variety of common time-varying interferences by studying the basic principles of various noises, and proves the NSZNN model’s of the validity and superiority, which solves the TVIK problem of the FMWMM with external disturbances through theoretical analyses. Compared with the existing gradient neural network (GNN) and the traditional zeroing neural network (ZNN), the most representative hybrid noise is selected to conduct a large number of experiments to substantiate the high efficiency and robustness of the NSZNN model. Finally, the NSZNN model is verified on the FMWMM via a robot operating system (ROS) by a successful execution of the trajectory tracking task.

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A new visual-inertial odometry scheme for unmanned systems in unified framework of zeroing neural networks

Chen,

Jiang,

Wang

et al. 2025

Neurocomputing

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On RNN-Based $k$-WTA Models With Time-Dependent Inputs

Cited by 9 publications

References 15 publications

A Novel Competition-Based Coordination Model with Dynamic Feedback for Multi-Robot Systems

A Novel Competition-Based Coordination Model with Dynamic Feedback for Multi-Robot Systems

Noise suppression zeroing neural network for online solving the time-varying inverse kinematics problem of four-wheel mobile manipulators with external disturbances

A new visual-inertial odometry scheme for unmanned systems in unified framework of zeroing neural networks

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