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Due to the highly complex dynamics of hydraulic generator unit, it is hard to develop an accurate analytical expression of the dynamic model, a new adaptive control algorithm based on the learning characteristic of neural network and the function approximation ability of the wavelet is presented in this paper. The control system consists of two wavelet networks, one realizes active identification...
The MRS metabolites quantification procedure has attracted the scientific interest of the engineering community, regarding the development of noninvasive and computationally efficient methodologies. Significant contributions based on Artificial Intelligence (AI) tools, such as Neural Networks (NNs), with good results have been presented lately but showing several drawbacks already discussed by the...
This paper studies the feasibility of using adaptive pulse shaping CP-OFDM in remote sensing satellites. A set of pulse shapes were generated using genetic algorithm that minimizes the mean square error of the timing offset estimator. These pulse shapes were used to train function approximation neural networks. Such neural networks make the use of adaptive pulse shaping in OFDM systems feasible. Results...
This paper presents an experiment of using neuronal networks as a pulse shape generator for CP-OFDM. A set of pulse shapes were generated using genetic algorithm that minimizes the mean square error of the timing offset estimator. These pulse shapes were used to train function approximation neural networks. Such neural networks make the use of adaptive pulse shaping in OFDM systems feasible. Results...
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