A fairly large number of signal processing applications are represented in this library.

- AdaptFilter
- An LMS adaptive filter converges so that its transfer function matches that of a fixed FIR filter.
- AllPole
- Two realizations of an all-pole filter are shown to be equivalent. One uses an FIR filter in a feedback path, the other uses the
`AllPoleVar`primitive. - AnimatedLMS
- An LMS adaptive filter is configured as in the
`AdaptFilter`demo, but this time the filter taps are displayed as they adapt. - AnimatedLMSCx
- A complex LMS adaptive filter is configured as in the
`AdaptFilter`demo, but in addition, user-controlled noise is added to the feedback loop using an on-screen slider to control the amount of noise. The filter taps are displayed as they adapt. - cep
- Given the coefficients of any polynomial, this demo uses the cepstrum to find a minimum-phase polynomial. Thus, given the coefficients of the denominator polynomial of an unstable filter, this demo will compute the coefficients of a stable denominator polynomial that has the same magnitude frequency response.
- chaos
- This is a simple demonstration of chaos, in which the phase-space plot of the famous Henon map is given.
- convolve
- Convolve two rectangular pulses in order to demonstrate the Convolve primitive.
- dft
- Compute a discrete Fourier transform of a finite signal using the
`FFTCx`primitive. The magnitude and phase (unwrapped) are plotted. - doppler
- A sine wave is subjected to four successive amounts of doppler shift. The doppler shift is accomplished by the
`phaseShift`module, which forms an analytic signal (using a Hilbert transform) that modulates a complex exponential. - dtft
- Demonstrate the
`DTFTCx`primitive, showing how it is different from the`FFTCx`primitive. Specifically, the range, number, and spacing of frequency samples is arbitrary. - freqsample
- This system designs FIR filters using the frequency sampling method. Samples of the frequency response are converted into FIR filter coefficients.
- iirDemo
- Two equivalent implementations of IIR filtering.
- LatticeDemo
- Demonstrate the use of lattice filters to synthesize an auto-regressive (AR) random process.
- latticeDesign
- Use of Levinson-Durbin algorithm to design a lattice filter with a specified transfer function.
- LevinsonDurbin
- Use the Levinson-Durbin algorithm to estimate the parameters of an AR process.
- linearPrediction
- Perform linear prediction on a test signal consisting of three sinusoids in colored, Gaussian noise. Two mechanisms (Burg's algorithm and an LMS adaptive filter) for linear prediction are compared.
- OverlapAddFFT
- Convolution is implemented in the frequency domain using overlap and add.
- phasedArray
- Simulate a plane wave approaching a phased array with four sensors. The plane wave approaches from angles starting from head on and slowly rotating 360 degrees. The response of the antenna is plotted as a function of direction of arrival in polar form.
- powerSpectrum
- Compare three methods for estimating a power spectrum of a signal with three sinusoids plus colored noise. The three methods are the periodogram method, the autocorrelation method, and Burg's method.
- timeVarSpec
- A time-varying spectrum is computed using the autocorrelation method and displayed using a waterfall plot.
- window
- Generate and display four window functions and the magnitude of their Fourier transforms. The windows displayed are the Hanning, Hamming, Blackman, and steep Blackman.