Ferran de Cabrera

Orcid: 0000-0001-6949-780X

According to our database1, Ferran de Cabrera authored at least 13 papers between 2017 and 2023.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2023
Regularized Estimation of Information via Canonical Correlation Analysis on a Finite-Dimensional Feature Space.
IEEE Trans. Inf. Theory, August, 2023

On the Estimation of Tsallis Entropy and a Novel Information Measure Based on Its Properties.
IEEE Signal Process. Lett., 2023

Minimum Error Entropy Estimation Under Contaminated Gaussian Noise.
IEEE Signal Process. Lett., 2023

2022
Compression of Multibeam Echosounders Bathymetry and Water Column Data.
Remote. Sens., 2022

2020
Regularized Estimation of Information via High Dimensional Canonical Correlation Analysis.
CoRR, 2020

Estimation of Information in Parallel Gaussian Channels via Model Order Selection.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019
A Proof of de Bruijn Identity based on Generalized Price's Theorem.
Proceedings of the IEEE International Symposium on Information Theory, 2019

Squared-Loss Mutual Information via High-Dimension Coherence Matrix Estimation.
Proceedings of the IEEE International Conference on Acoustics, 2019

Entropy-Based Non-Data-Aided SNR Estimation.
Proceedings of the 53rd Asilomar Conference on Signals, Systems, and Computers, 2019

2018
Multi-Satellite Cycle-Slip Detection and Exclusion Using the Noise Subspace of Residual Dynamics.
Proceedings of the 26th European Signal Processing Conference, 2018

A novel formulation of Independence Detection based on the Sample Characteristic Function.
Proceedings of the 26th European Signal Processing Conference, 2018

2017
Entropy-based covariance determinant estimation.
Proceedings of the 18th IEEE International Workshop on Signal Processing Advances in Wireless Communications, 2017

Robust estimation of the magnitude squared coherence based on kernel signal processing.
Proceedings of the 51st Asilomar Conference on Signals, Systems, and Computers, 2017


  Loading...