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In this paper, a convergence-enhanced gradient neural network (CEGNN) is proposed and investigated for solving online Sylvester equation that is widely used in the control community. Different from the conventional gradient neural network (CGNN), the proposed CEGNN model possesses a specially-constructed nonlinear activation function, and thus possesses the better convergence performance (i.e., finite-time...
Kinematic calibration is of great significance to the application of handling robot in the field of stamping industry. In this paper, a novel kinematic calibration method of a 5-DOF handling robot is proposed based on optimal trajectory planning. In order to illustrate our independently developed mechanical structure composed of three rotary joints and two translational joints, the forward kinematic...
Artificial To better achieve character recognition, analyze the impact of noise character. BP neural network application describes the process of character recognition, and the corresponding algorithm improvements. Created with MATLAB and training the neural network to identify the different samples, combined toolbox simulink simulation module, so that the character recognition to get better recognition...
In order to estimate fault resistance accurately in real-time, a new approach is proposed based on the emerging synchronized measurement technology, using synchronized data sampled at both line terminals. This new approach uses n type equivalent model and time-domain signals during the fault to estimate fault resistance online by solving differential equations of the circuit. The approach does not...
Frequency-derived identification of the propagation of information between brain regions has quickly become a popular area in the neurosciences. Of the various techniques used to study the propagation of activation within the central nervous system, the directed transfer function (DTF) has been well used to explore the functional connectivity during a variety of brain states and pathological conditions...
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