Compress a speech signal using the discrete cosine transform (DCT).
The hilbert function finds the exact analytic signal for a finite block of data. You can also generate the analytic signal by using an FIR Hilbert transformer filter to compute an
The chirp Z-transform (CZT) is useful in evaluating the Z-transform along contours other than the unit circle. The chirp Z-transform is also more efficient than the DFT algorithm for the
The discrete Fourier transform, or DFT, is the primary tool of digital signal processing. The foundation of the product is the fast Fourier transform (FFT), a method for computing the DFT
Use the Goertzel function to implement a DFT-based DTMF detection algorithm.
Determine the analytic signal. The example also demonstrates that the imaginary part of the analytic signal corresponding to a cosine is a sine with the same frequency. If the cosine has a
Extract the signal envelope using the analytic signal.
Estimate a speaker's fundamental frequency using the complex cepstrum. The example also estimates the fundamental frequency using a zero-crossing method and compares the results.
Cepstrum analysis is a nonlinear signal processing technique with a variety of applications in areas such as speech and image processing.
The Hilbert transform facilitates the formation of the analytic signal. The analytic signal is useful in the area of communications, particularly in bandpass signal processing. The
The discrete cosine transform (DCT) is closely related to the discrete Fourier transform (DFT). The DFT is actually one step in the computation of the DCT for a sequence. The DCT, however, has
Use the Hilbert transform to carry out single-sideband (SSB) amplitude modulation (AM) of a signal. Single-sideband AM signals have less bandwidth than normal AM signals.
Use the discrete Hilbert Transform to implement Single Sideband Modulation.
Use the Walsh-Hadamard transform (WHT) and some of its properties by showcasing two applications: communications using spread spectrum and processing of ECG signals.