Signal Processing

 

 


 

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E.g., 2016-12-02
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Dec 6th 2016

How can we use computers to create expressive, compelling music? And how can we write computer software to help us create and organize sounds in new ways? This course provides a hands-on introduction to the field of music technology as both a creative musical practice and an interdisciplinary technical research pursuit. Students will be able to compose music in digital audio workstation software using both audio and symbolic representations; to write code to algorithmically generate music, analyze sound, and design sound; and to describe the essential theory and history behind these activities as well as their connection to cutting-edge computer music research.

Average: 6.3 (4 votes)
Nov 6th 2016

This course provides an introductory overview of audio synthesis and visual programming using Native Instruments' Reaktor Software. Students will receive an in-depth look into various audio synthesis methods, including: additive, subtractive, sampling, wavetable, physical modeling, and granular synthesis, as well as the various types of modulation synthesis.

Average: 6 (4 votes)
Jun 28th 2016

Max is powerful platform that accommodates and connects a wide variety of tools for sound, graphics, music and interactivity using a flexible patching and programming environment. Max allows most computer users to write a simple meaningful program within a few minutes, even with limited programming knowledge.

Average: 10 (1 vote)
Jun 6th 2016

Creative Programming for Audiovisual Art aims to enhance student skills and experience in the development of software for the creation and manipulation of sounds and images, both in real and non-real time. The course explores the intersection and similarities between sound and image signal processing through the exploration of combined audiovisual approaches. As such it is suitable for those with a strong interest in creative technologies from either an engineering or creative arts background.

Average: 10 (1 vote)
Apr 7th 2016

This course provides the basic toolkit for any signal processing application - the abstraction of signals and systems, from the point of view of analysis and characterization. We encounter signals and systems extensively in our day-to-day lives, from making a phone call, listening to a song, editing photos, manipulating audio files, using speech recognition softwares like Siri and Google now, to taking EEGs, ECGs and X-Ray images.

Average: 5.1 (7 votes)
Apr 7th 2016

This course provides the basic toolkit for any signal processing application - the abstraction of signals and systems, from the point of view of analysis and characterisation. We encounter signals and systems extensively in our day-to-day lives, from making a phone call, listening to a song, editing photos, manipulating audio files, using speech recognition softwares like Siri and Google now, to taking EEGs, ECGs and X-Ray images. Each of these involves gathering, storing, transmitting and processing information from the physical world. This course will equip you to deal with these tasks efficiently by learning the basic mathematical framework of signals and systems.

Average: 8.5 (2 votes)
Feb 15th 2016

Le traitement du signal est présent dans tous les domaines de notre vie, que l’on parle de télécommunications, de télévision, de transports ou de médecine. Ce MOOC est une introduction aux principes de base du traitement du signal.

Average: 2 (2 votes)
Mar 18th 2015

Enter the world of signal processing: analyze and extract meaning from the signals around us!

No votes yet
Feb 4th 2015

Enter the world of signal processing: analyze and extract meaning from the signals around us!

Average: 1 (1 vote)
Feb 3rd 2015

A focused view into the theory behind modern discrete-time signal processing systems and applications.

Average: 3 (1 vote)
Self Paced

This is an introductory course to Digital Signal Processing that can be taken at any time. The course deals with the fundamentals in addition to exploring techniques like filtering, correlation and Fourier analysis. There is an emphasis in applying DSP theory to practical problems.

Average: 5 (13 votes)