Howtosignalprocessing
![CWT matlab function [closed]](https://howtosignalprocessing.com/storage/img/images_2/cwt_matlab_function_closed.jpg)
- How to use CWT in Matlab?
- What is the difference between CWT and DWT?
- How to use discrete wavelet transform in Matlab?
- How does discrete wavelet transform work?
How to use CWT in Matlab?
wt = cwt( x , wname ) uses the analytic wavelet specified by wname to compute the CWT. [ wt , f ] = cwt(___, fs ) specifies the sampling frequency, fs , in hertz, and returns the scale-to-frequency conversions f in hertz. If you do not specify a sampling frequency, cwt returns f in cycles per sample.
What is the difference between CWT and DWT?
To summarize: The CWT and the discrete wavelet transforms differ in how they discretize the scale parameter. The CWT typically uses exponential scales with a base smaller than 2, for example 21/12 . The discrete wavelet transform always uses exponential scales with the base equal to 2.
How to use discrete wavelet transform in Matlab?
[ cA , cH , cV , cD ] = dwt2( X , wname ) computes the single-level 2-D discrete wavelet transform (DWT) of the input data X using the wname wavelet. dwt2 returns the approximation coefficients matrix cA and detail coefficients matrices cH , cV , and cD (horizontal, vertical, and diagonal, respectively).
How does discrete wavelet transform work?
A discrete wavelet transform (DWT) is a transform that decomposes a given signal into a number of sets, where each set is a time series of coefficients describing the time evolution of the signal in the corresponding frequency band.
