The Wavelet transform explained

The Wavelet Transform is a type of Time-frequency analysis. The Time-frequency analyses analyze a non stationary signal and indicate both frequencies present in the signal and the time at which those frequencies occur. The Wavelet Transform overcomes the disadvantages of FFT by performing a multi-resolution analysis. Learn more about Wavelet transform in detail in this video.

Why FFT can't do better than Wavelet analysis? It's because FFT compromises between time and frequency. To learn more about time-frequency relation please check out the video.
Time-Frequency resolution:

[loonanC]

One of the clearest explanation of Wavelet transform, well done !

[Mahmoud-pfss]

at 14:10 i believe that there is a mistake the graph shows high time resolution but it's actually the opposite because the block is wide so it's not accurate for time but accurate for frequency and the same thing for frequency it's low frequency resolution. but great video thank you for uploading.

[AhmadRababah-jg]

Thanks that was the best and the simplest

[arash]

Hi,
Are you going to produce videos in more advance wavelet analysis? I can not link the idea of the wavelet analysis with the filtering in discrete wavelet analysis.
Thank you.

[joeyeats]

Great video, this helped me understand the wavelet transform clearly. Do you have any academic sources for this information so I can cite it in my research? Thank you.

[loveforallbxlmannif]

Thanks ! What would be the difference if we replace our wavelet with bandpass filter ? Would the latency be the same ?