ABSTRACT
Fourier analysis is an important tool for extracting significant information of the frequency domain of a signal that is not apparent in its representation in the time domain. It is used for signal analysis, describing the spectral behavior of the signal. Since the spectral information is given within the frequency domain, the Fourier transform domain is called the frequency domain. This chapter discusses the fundamental principles of wavelet transform and shows how the wavelet breaks a signal down into detail signals and an approximation. The discrete wavelet transform convolves the input by the shifts and scales of the wavelet. The Discrete Fourier Transform (DFT) is used for the frequency representation of finite-time signals. The Discrete Fourier Transform (DFT) is an alternative form of the Fourier transform in which the finite length sequences are transformed into other sequences, which represent samples in the frequency domain and are defined by the relations.
