Howtosignalprocessing
- What is inverse wavelet transform?
- What do the coefficients of the wavelet transform mean?
- How do you calculate wavelet coefficients?
- How do you choose a wavelet decomposition level?
What is inverse wavelet transform?
The icwt function implements the inverse CWT. Using icwt requires that you obtain the CWT from cwt . Because the CWT is a redundant transform, there is not a unique way to define the inverse.
What do the coefficients of the wavelet transform mean?
The wavelet transform is the convolution of a function (data) with a wavelet base. The result of this convolution is the wavelet coefficients. Convolution measures the similarity between the wavelet function and the data. If the similarity is high then you will have peaks.
How do you calculate wavelet coefficients?
The wavelet coefficients β j , k = 〈 f , ψ ˜ j , k 〉 , j < J , of a function f ∈ L 2 ( R ) can be calculated using the fast wavelet transform from the coefficients c J , k = 〈 f , φ ˜ J , k 〉 at a fine scale . In practice, however, the coefficients c J , k cannot be calculated exactly.
How do you choose a wavelet decomposition level?
Theoretically, the maximum decomposition level (M) can be calculated as: M = log2 (N), where N is the series length. When conducting a wavelet-based ANN model, it needs to determine the most suitable decomposition level from 1 to M.
