ABSTRACT
The Dilation Wavelet Transforms (DWT) decomposes the signal into a set of different frequency components like Fourier transform but having non-uniform bandwidths for the decomposed components. The DWT can be implemented using filter bank with the help of low-pass and high-pass filters. DWT decomposes the approximation spaces only to construct the orthogonal subspaces. On the other hand, Wavelet Packet Transform (WPT) decomposes both the approximation space and detail space to construct new bases. The FAWT is also known as an analytic wavelet transform with a flexible time-frequency covering. The Flexible Analytic Wavelet Transform (FAWT) can be implemented with the iterative filter bank approach. In FBSE-Flexible Analytic Wavelet Transform (FAWT) method, the FBSE spectrum is used for the implementation of FAWT instead of Fourier spectrum. The FAWT performs filtering in frequency-domain by multiplying the filter response with the Fourier transform-based spectrum of the signal.
