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A neural network method combined with simulated annealing algorithm is proposed for power system harmonic analysis. This method is aimed at the system in which the sampling frequency cannot be locked on the actual fundamental frequency. By updating the relevant parameters including the learning rate of fundamental frequency, fundamental frequency, harmonic phases and amplitudes, the accurate harmonic...
In this paper a controller design is proposed to get obstacle free trajectories in a three dimensional urban environment for unmanned air vehicles (UAVs). The controller has a two-layer architecture. In the upper layer, vision-inspired Grossberg neural network is proposed to get the shortest distance paths. In the bottom layer, a model predictive control (MPC) based controller is used to obtain dynamically...
This paper addresses the design problem of linear-phase finite-impulse response (FIR) notch filters based on a neural networks optimization technique. The main idea is to minimize the weighted square-error function in the frequency-domain. The convergence theorem of the neural networks algorithm is proved to illustrate the proposed algorithm stable, and the implementation of the approach is also described...
A novel linear-phase finite-impulse response (FIR) digital filters design approach based on neural networks optimization technique was proposed in this paper. The main idea is to minimize the weighted square-error function in the frequency-domain. The convergence theorem of the neural networks algorithm was presented and proved to illustrate the proposed algorithm stable, and the implementation of...
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