Howtosignalprocessing
- What does a continuous wavelet transform do?
- What is the difference between CWT and DWT?
- What is wavelet power?
- What is the output of wavelet transform?
What does a continuous wavelet transform do?
In mathematics, the continuous wavelet transform (CWT) is a formal (i.e., non-numerical) tool that provides an overcomplete representation of a signal by letting the translation and scale parameter of the wavelets vary continuously.
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.
What is wavelet power?
While the (single) wavelet power spectrum describes the evolution of the variance of a time series at the different frequencies, with periods of large variance associated with periods of large power at the different scales, the cross-wavelet power of two time series describes the local covariance between the time ...
What is the output of wavelet transform?
The outputs A and D are the reconstruction wavelet coefficients: A: The approximation output, which is the low frequency content of the input signal component. D: The multidimensional output, which gives the details, or the high frequency components, of the input signal at various levels (up to level 6)
