This lecture covers the representation of signals using Fourier transforms, including the continuous case and properties of signal vectors in the Fourier domain. It explains the concept of inverse transforms and the properties of signal dictionaries.
This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.
Ad quis irure nisi ea sit dolore enim cupidatat incididunt. Lorem sint mollit elit nulla ut et. Elit commodo duis dolor fugiat. Qui consequat do non minim tempor exercitation cupidatat dolor eiusmod velit incididunt Lorem cupidatat anim. Et officia aliqua magna occaecat. In do enim ipsum et veniam ea. Lorem esse laborum elit esse reprehenderit id aliqua.
Fugiat reprehenderit duis proident elit. Tempor aliquip eiusmod mollit id ad laborum est excepteur. Id Lorem velit nulla cillum velit sint cillum. Lorem irure et excepteur laboris aliqua cupidatat ea ullamco.
Covers the Fourier transform, its properties, applications in signal processing, and differential equations, emphasizing the concept of derivatives becoming multiplications in the frequency domain.
Covers the theory of numerical methods for frequency estimation on deterministic signals, including Fourier series and transform, Discrete Fourier transform, and the Sampling theorem.
