Wavelet and Fourier Transform Easy understanding Important features

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We may say that signals as random entities. • • Fourier transformation is suitable for the stationary signal. Whereas, • Wavelet transformation is suitable for the stationary and non-stationary signal. • Fourier transform convert signal from time domain to frequency domain signal. It provides two-dimensional information about any signal that what different frequency component present in a signal and what are their respective amplitudes. • Wavelet transform gives a complete three-dimensional information about any signal that is what different frequency components are present in any signal and what are their respective amplitudes and at time axis where these different frequency components exist. • Fourier transformation has zero-time resolution and very high-frequency resolution. • Wavelet transformation has high time resolution and high-frequency resolution, as well as time and frequency resolution, changed. • #StudyHour • =========================================== • Watch Optimization Techniques on YouTube • • Optimization Techniques • =========================================== • 🙏 LIKE || COMMENT || SUBSCRIBE || SHARE 🙏 • =========================================== • Watch Queuing Theory on YouTube • • Queuing Theory • =========================================== • 🙏 THANK YOU FOR WATCHING 🙏

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