To overcome these problems, adaptive median filtering is commonly applied where the window size changes adaptively based on impulsive noise content [ , , ]. This is achieved by computing the inner product of the signal with a set of basic functions kernels that serve as the building blocks for representing the signal in the new domain. Generally speaking, as an amplitude-focused approach, envelope analysis offers limited frequency information about the signal. In this case, the signal is sampled at the lowest rate, which still allows for a complete reconstruction of the continuous-time signal, assuming the signal bandwidth is limited to half of the sampling frequency. Hamdan, F.
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