SSUM: Signals and Systems Using MATLAB
by Bob L. Sturm and Dr. Jerry Gibson
The SSUM package is a collection of demonstrations and exploratory applications programmed in MATLAB to illustrate important, insightful, and inspiring concepts of media signal processing, using audio, image, and video. SSUM is best for short signals and smaller images, rather than processing large signals. Several test signals and images are located in the 'data' directory that comes with SSUM.
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To use SSUM start MATLAB, change to the SSUM directory, and type ssum. You will see the menu below, which contains all the available applications.
The following is a list of all the applications and their explanations.
|Additive Synthesis Forest||Synthesized bird song using additive synthesis.|
|Audio Aliasing Explorer||Explore aliasing and folding for sound signals. Downsample with or without anti-aliasing filters.|
|Catastochastic Additive Synthesis Composition Machine||Random music generator with variable partials and envelopes.|
|Communication Models Explorer||Explore different methods of modeling communication systems.|
|Complex Number Explorer||Visualize complex numbers and phasors.|
|Convolution Explorer||Visualize linear and circular convolution with different signals.|
|Cross-Synthesis Explorer||Cross-synthesize two sounds using convolution, amplitude enveloping, or LPC.|
|Finite Difference Equation Explorer||Type in a finite difference equation and see its frequency and impulse responses.|
|FIR Filter Explorer||Create FIR filter and apply to a sound.|
|IIR Filter Explorer||Create IIR filter and apply to a sound.|
|Formant Explorer||Drag window across sound and watch the formant, auto-correlation, and cepstrum change.|
|Fourier Explorer||Drag window across sound and watch the spectrum change.|
|Fourier Series Explorer||Observe the Fourier series of a periodic step signal.|
|Image Aliasing Explorer||Explore downsampling images with and without anti-aliasing filter.|
|Image Analysis/Construction||Spectral analysis of image and resynthesis. Ability to swap magnitudes and phases of other images.|
|Image Filter Explorer||Apply different filters to images.|
|Image Spectrum Explorer||Explore the spatial frequencies in images.|
|LPC Explorer||Use linear prediction to resynthesize a signal using numerous excitations.|
|Modulation Explorer||Modulate one signal by another and see changes in spectrum and waveform.|
|Pole-Zero Explorer||Drag poles and zeros around a unit circle to watch frequency response change.|
|Pole-Zero Filter Explorer||Create filter using pole-zero plot and apply it to sound.|
|Sampling Explorer||Demonstrate sampling, quantization, and interpolation.|
|Signal Feature Explorer||Explore the statistics of a signal, such as RMS, and spectral centroid.|
|Sinewave Speech Synthesis Explorer||Use LPC to reduce sounds to four sine waves.|
|Sinusoidal Explorer||Basic parameters of sine waves; add and multiply two sine waves.|
|Sonogram Explorer||Explore the STFT of a signal; trace partials with mouse clicks.|
|Sound Analysis/Synthesis||Spectral analysis of sound and resynthesis. Ability to swap magnitudes and phases of other sounds.|
|Waveform Explorer||Generate waveforms from 15 sinusoidal components.|
|Denoising Explorer||Use median and average filtering to remove noise from audio signal.|
|Dynamic Time Alignment Explorer||Explore dynamic time alignment of a test and reference speech file.|
|Endpoint Explorer||See how speech endpoints can be detected using spectral magnitudes and zero crossings.|
|Reverberation Explorer||Use allpass and comb filters to simulate reverberation impulse responses.|
|String Explorer||See d'Alembert's solution to the one-dimensional wave equation using two sample delay lines|
|Karplus-Strong String Explorer||Using two sample delay lines simulate the vibrational acoustics of a string using ideal, or lossy models. Apply musical instrument and room impulse responses to the sound to make more realistic. Synthesis a MIDI file using plucked or struck strings.|
|Vector Quantization Explorer||Explore vector quantization of cepstral coefficients and LPC parameters for a given speech file.|
|Quantization Explorer||Explore scalar quantization.|
|Companding Explorer||Explore uniform quantization with compression.|
SSUM was inspired first by the need of students in MAT to grasp the difficult concepts inherent in media signal signal processing. The design of SSUM owes much to the MATLAB Auditory Demonstrations (MAD) toolkit developed by the Speech and Hearing Group at the University of Sheffield, UK. These web-help pages are also constructed in a manner similar to theirs.
Produced by Bob L. Sturm and Dr. Jerry Gibson.
Release date: September 2, 2004
Copyright 2004 University of California, Santa Barbara