Abstract
Fourier theory says that any periodic signal can be created by adding together different sinusoids (of varying frequency, amplitude and phase). In many applications, an unknown analog signal is sampled with an A/D converter and a Fast Fourier Transform (FFT) is performed on the sampled data to determine the underlying sinusoids. In this steps a visual approach based on convolution is used to explain basic Digital Signal Processing (DSP) up to the Discrete Fourier Transform (DFT). The DFT is explained instead of the more commonly used FFT because the DFT is much easier to understand. (The DFT is equivalent to the FFT except the DFT is far less computationally efficient.) In particular, convolution is shown to be the key to understanding basic DSP. Also, some of the concepts are far more intuitive in the frequency-domain vs. the more familiar time-domain.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
