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 basics of Functional Reactive Programming, including signal aggregation, fundamental operations, constant and variable signals, and signal interpretation.
Covers the conversion of analog signals to digital, data compression, and signal reconstruction, highlighting the significance of signal processing in communication systems.
Covers the concept of time, discrete time practicality, sampling theorem, digital storage, transmission of signals, and key ideas of digital signal processing.
Covers the theory of numerical methods for frequency estimation on deterministic signals, including Fourier series and transform, Discrete Fourier transform, and the Sampling theorem.
