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This paper proposes an observer based adaptive tracking control strategy for a class of uncertain nonlinear systems with delay in state as well as in input. Self recurrent wavelet neural network (SRWNN) is used to approximate the uncertainties present in the system as well as to identify and compensate the dynamic nonlinearities. The architecture of the SRWNN is a modified model of the wavelet neural...
In this work an adaptive tracking control strategy for a class of non affine delayed systems subjected to actuator saturation is proposed. Self recurrent wavelet neural network (SRWNN) is used to approximate the uncertainties present in the system as well as to identify and compensate the nonlinearities introduced in the system due to actuator saturation. By using suitable transformation the system...
In the visual inspection with the machine system, the prerequisite for the detection success is to get a clear and stable image with high signal to noise ratio. For the current lack of quality assessment on the collected images, an experimental evaluation method is proposed for the quality of the collected image based on the image sharpness parameters and the illumination factor of the CCD target...
An adaptive wavelet neural network (AWNN)-based method has been proposed to determine dynamic available transfer capability (DATC) in the electricity markets, having bilateral as well as multilateral contracts. Mexican hat wavelet basis function has been used as the activation function in the hidden layer of the network. Wavelet parameters, that is, translations and dilations of the AWNN, have been...
Noise in MR images is an important concern that undermine their diagnostic accuracy. Wavelet based noise removal has been used in past studies to remove noise without introducing a significant image distortion which is associated with other denoising methods. Wavelet based method involves the selection of a few parameters for optimum denoising. Usually, this selection process is based on human observation...
In the field of signal processing, there is a need to quickly and efficiently detect and extract information from signals, One type of signal feature that is difficult to process is a discontinuous singularity and chaotic structure, In this paper, We have presented that models by adaptively computing wavelet parameters using Optimum Wavelet Receiver.
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