Marisel Villafane-Delgado

Affiliations:
  • Michigan State University, East Lansing, MI, USA


According to our database1, Marisel Villafane-Delgado authored at least 10 papers between 2014 and 2018.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2018
Assessing Students' Mathematical Challenges in an Introduction to Signal Processing Course and the Effects of Cooperative Learning.
Proceedings of the IEEE Frontiers in Education Conference, 2018

2017
Dynamic Graph Fourier Transform on temporal functional connectivity networks.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

Multi-scale higher order singular value decomposition (MS-HoSVD) for resting-state FMRI compression and analysis.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

2016
A Measure of Multivariate Phase Synchrony Using Hyperdimensional Geometry.
IEEE Trans. Signal Process., 2016

Temporal network tracking based on tensor factor analysis of graph signal spectrum.
Proceedings of the IEEE Statistical Signal Processing Workshop, 2016

Functional connectivity brain network analysis through network to signal transform based on the resistance distance.
Proceedings of the 2016 IEEE International Conference on Acoustics, 2016

Graph information theoretic measures on functional connectivity networks based on graph-to-signal transform.
Proceedings of the 2016 IEEE Global Conference on Signal and Information Processing, 2016

2015
A time-frequency based bivariate synchrony measure for reducing volume conduction effects in EEG.
Proceedings of the 2015 IEEE Global Conference on Signal and Information Processing, 2015

2014
Computation of resting state networks from fMRI through a measure of phase synchrony.
Proceedings of the 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2014

Effective connectivity in FMRI from mutual prediction approach.
Proceedings of the 48th Asilomar Conference on Signals, Systems and Computers, 2014


  Loading...