In our framework, the frequency domain filter serves as an auxiliary module, and it is endowed with the capability to directly manipulate the signal's frequency domain. The main idea involves the utilization of the neural network as a filter within the frequency domain, facilitated by the Fourier transform. This approach is commonly referred to as Fourier neural networks.
According to the Convolution Theorem, the convolution of two time-domain data is equivalent to the inner product in their Fourier transform domain. Such that, a frequency filter employs a linear operation to filter the signal within the frequency domain, thereby substituting the convolution operation in the time domain.
Consequently, it is reasonable to utilize a fully-connected neural network for the implementation of the frequency filter. Subsequently, the envelope is defined as the absolute value of z(n), and the ES is the Fourier frequency spectrum of the envelope.
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