作者:
Butola, RajatLi, YimingKola, Sekhar ReddyNational Yang Ming Chiao Tung University
Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program Hsinchu300093 Taiwan Institute of Pioneer Semiconductor Innovation
The Institute of Artificial Intelligence Innovation National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program The Institute of Communications Engineering the Institute of Biomedical Engineering Department of Electronics and Electrical Engineering Hsinchu300093 Taiwan
In this work, a dynamic weighting-artificial neural network (DW-ANN) methodology is presented for quick and automated compact model (CM) generation. It takes advantage of both TCAD simulations for high accuracy and SP...
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Micro-Doppler signatures (mu -DSs) are widely used for human activity recognition (HAR) using radar. However, traditional methods for generating mu -DS, such as the short-time Fourier transform (STFT), suffer from lim...
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We report a compact modeling framework based on the Grove-Frohman (GF) model and artificial neural networks (ANNs) for emerging gate-all-around (GAA) MOSFETs. The framework consists of two ANNs;the first ANN construct...
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In this study, we report the process variation effect (PVE) including the work function fluctuation (WKF) on the DC/AC characteristic fluctuation of stacked gate-all-around silicon complementary field-effect transisto...
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This work presents an adaptive tracking guidance method for robotic fishes. The scheme enables robots to suppress external interference and eliminate motion jitter. An adaptive integral surge line-of-sight guidance ru...
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This work presents an adaptive tracking guidance method for robotic fishes. The scheme enables robots to suppress external interference and eliminate motion jitter. An adaptive integral surge line-of-sight guidance rule is designed to eliminate dynamics interference and sideslip issues. Limited-time yaw and surge speed observers are reported to fit disturbance variables in the model. The approximation values can compensate for the system's control input and improve the robots' tracking ***, this work develops a terminal sliding mode controller and third-order differential processor to determine the rotational torque and reduce the robots' run jitter. Then, Lyapunov's theory proves the uniform ultimate boundedness of the proposed method. Simulation and physical experiments confirm that the technology improves the tracking error convergence speed and stability of robotic fishes.
Zeroing neurodynamics methodology,which dedicates to finding equilibrium points of equations,has been proven to be a powerful tool in the online solving of problems with considerable *** this paper,a method for underw...
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Zeroing neurodynamics methodology,which dedicates to finding equilibrium points of equations,has been proven to be a powerful tool in the online solving of problems with considerable *** this paper,a method for underwater acoustic sensor network(UASN)localisation is proposed based on zeroing neurodynamics methodology to preferably locate moving underwater nodes.A zeroing neurodynamics model specifically designed for UASN localisation is constructed with rigorous theoretical analyses of its *** proposed zeroing neurodynamics model is compatible with some localisation algorithms,which can be utilised to eliminate error in non‐ideal situations,thus further improving its ***,the effectiveness and compatibility of the proposed zeroing neurodynamics model are substantiated by examples and computer simulations.
This paper considers the problem of approximating the infinite-horizon value function of the discrete-time switched LQR *** particular,the authors propose a new value iteration method to generate a sequence of monoton...
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This paper considers the problem of approximating the infinite-horizon value function of the discrete-time switched LQR *** particular,the authors propose a new value iteration method to generate a sequence of monotonically decreasing functions that converges exponentially to the value *** method facilitates us to use coarse approximations resulting from faster but less accurate algorithms for further value iteration,and thus,the proposed approach is capable of achieving a better approximation for a given computation time compared with the existing *** numerical examples are presented in this paper to illustrate the effectiveness of the proposed method.
This paper is concerned with global practical stabilization of the double integrator system with an imperfect sensor and subject to an additive bounded output *** imperfect sensor nonlinearity possesses the nonlinear ...
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This paper is concerned with global practical stabilization of the double integrator system with an imperfect sensor and subject to an additive bounded output *** imperfect sensor nonlinearity possesses the nonlinear characteristics of saturation and dead *** of the presence of output dead zone and the additive disturbance,the states cannot be expected to driven into an arbitrarily small neighborhood of the *** solve the global practical stabilization problem,we proposes a low gain-based linear dynamic output feedback law,under which the first state enters and remains in a bounded set whose size is depended on the bound of disturbance and the range of dead zone and the second state enters and remains in a pre-specified arbitrarily small set,both in finite *** results illustrate the effectiveness of our proposed control method.
A state-dependent discrete memoryless multiple access channel is considered to model an integrated sensing and communication system, where two transmitters wish to convey messages to a receiver while simultaneously es...
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Artificial intelligence (AI) is revolutionizing various sectors, including science,technology, industry and daily life [1,2].One key area where AI can make a significant impact is in material design, crucial for advan...
Artificial intelligence (AI) is revolutionizing various sectors, including science,technology, industry and daily life [1,2].One key area where AI can make a significant impact is in material design, crucial for advancing technologies such as energy storage and catalysis [3,4].
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