Additive synthesis creates complex sounds by adding together individual sinusoidal signals called partials. A partial's frequency and amplitude are each time-varying functions, so a partial is a more flexible version of the harmonic associated with a Fourier series decomposition of a periodic waveform. In this module you will learn about partials, how to model the timbre of natural instruments, various sources of control information for partials, and how to make a sinusoidal oscillator with an instantaneous frequency that varies with time.

Additive synthesis creates complex sounds by adding together individual sinusoidal signals called "partials." In this module you will learn how to synthesize audio waveforms by designing the frequency and amplitude trajectories of the partials. LabVIEW programming techniques for additive synthesis will also be introduced in two examples.

Amplitude modulation (AM) creates interesting special effects when applied to music and speech signals. The mathematics of the modulation property of the Fourier transform are presented as the basis for understanding the AM effect, and several audio demonstrations illustrate the AM effect when applied to simple signals (sinusoids) and speech signals. The audio demonstration is implemented by a LabVIEW VI using an event structure as the basis for real-time interactive parameter control.

Learn about analog synthesizer modules, the foundation for synthesizers based on analog electronics technology. While analog synthesis has largely been replaced by digital techniques, the concepts associated with analog modular synthesis (oscillators, amplifiers, envelope generators, and patches) still form the basis for many digital synthesis algorithms.

Learn how to create and manipulate arrays, perform mathematical operations on them, and use spreadsheets to read and write arrays to the file system.

Learn how to play an audio signal (1-D array) using your computer's soundcard.

Learn how to use the 'Sine Wave' subVI from the Signal Processing palette as an audio source.

Subtractive synthesis techniques often require a wideband excitation source such as a pulse train to drive a time-varying digital filter. Traditional rectangular pulses have theoretically infinite bandwidth, and therefore always introduce aliasing noise into the input signal. A band-limited pulse (BLP) source is free of aliasing problems, and is more suitable for subtractive synthesis algorithms. The mathematics of the band-limited pulse is presented, and a LabVIEW VI is developed to implement the BLP source. An audio demonstration is included.

Linear algebra, vector space methods, and functional analysis are a powerful setting for many topics in engineering, science (including social sciences), and business. This collection starts with the simple idea of a matrix times a vector and develops tools and interpretations for many signal processing and system analysis and design methods.

Students are to implement and optimize a pseudo-noise (PN) sequence generator and a binary phase shift keying (BPSK) transmitter.

This interdisciplinary course provides a hands-on approach to students in the topics of bioinformatics and proteomics. Lectures and labs cover sequence analysis, microarray expression analysis, Bayesian methods, control theory, scale-free networks, and biotechnology applications. Designed for those with a computational and/or engineering background, it will include current real-world examples, actual implementations, and engineering design issues. Where applicable, engineering issues from signal processing, network theory, machine learning, robotics and other domains will be expounded upon.

This course presents the fundamentals of digital signal processing with particular emphasis on problems in biomedical research and clinical medicine. It covers principles and algorithms for processing both deterministic and random signals. Topics include data acquisition, imaging, filtering, coding, feature extraction, and modeling. The focus of the course is a series of labs that provide practical experience in processing physiological data, with examples from cardiology, speech processing, and medical imaging. The labs are done on the MIT Server in MATLAB® during weekly lab sessions that take place in an electronic classroom. Lectures cover signal processing topics relevant to the lab exercises, as well as background on the biological signals processed in the labs.

Description of a MATLAB GUI that identifies bird calls within audio wave files.

Birdcall Identification Project for Rice University Elec 301 class.

This module details the implementation of a blind source separation system using fast ICA.

This module describes applications of blind source separation in signal processing.

Are you interested in building and testing your own imaging radar system? MIT Lincoln Laboratory offers this 3-week course in the design, fabrication, and test of a laptop-based radar sensor capable of measuring Doppler, range, and forming synthetic aperture radar (SAR) images. You do not have to be a radar engineer but it helps if you are interested in any of the following; electronics, amateur radio, physics, or electromagnetics. It is recommended that you have some familiarity with MATLAB®. Teams of three students will receive a radar kit and will attend a total of 5 sessions spanning topics from the fundamentals of radar to SAR imaging. Experiments will be performed each week as the radar kit is implemented. You will bring your radar kit into the field and perform additional experiments such as measuring the speed of passing cars or plotting the range of moving targets. A final SAR imaging contest will test your ability to form a SAR image of a target scene of your choice from around campus; the most detailed and most creative image wins.

Implement several different Chowning FM instruments (bell, wood drum, brass, clarinet, and bassoon) and compare them to the sounds of physical instruments. Develop code to model the Chowning algorithms as LabVIEW "virtual musical instruments" (VMIs) to be "played" by a MIDI file within MIDI JamSession.

John Chowning pioneered frequency modulation (FM) synthesis in the 1970s, and demonstrated how the technique could simulate a diversity of instruments such as brass, woodwinds, and percussion. FM synthesis produces rich spectra from only two sinusoidal oscillators, and more interesting sounds can be produced by using a time-varying modulation index to alter the effective bandwidth and sideband amplitudes over time. A LabVIEW VI is developed to implement the sound of a clarinet, and the VI can be easily modified to simulate the sounds of many other instruments.