By Topic

Using Python for Signal Processing and Visualization

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)

The Python programming language provides a development environment suitable to both computational and visualization tasks. One of Python's key advantages is that it lets developers use packages that extend the language to provide advanced capabilities, such as array and matrix manipulation, image processing, digital signal processing, and visualization. Several popular data exploration and visualization tools have been built in Python, including Visit (www.llnl. gov/visit), Paraview (www.paraview. org), climate data analysis tools (CDAT;, and VisTrails (www.vistrails .org). In our work, we use VisTrails; however, nearly any Python-enabled application can produce similar results. The neuroscience field often uses bothmultimodal data and computationally complex algorithms to analyze data collected from study participants. Here, we investigate a study in which magnetic resonance imaging (MRI) is combined with electroencephalography (EEG) data to examine working memory.

Published in:

Computing in Science & Engineering  (Volume:12 ,  Issue: 4 )