Lower Bounds on Mutual Information [PDF]
, 2010 We correct claims about lower bounds on mutual information (MI) between real-valued random variables made in A. Kraskov {\it et al.}, Phys. Rev. E {\bf 69}, 066138 (2004). We show that non-trivial lower bounds on MI in terms of linear correlations depend
David V. Foster +4 more
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Achievable information rate optimization in C-band optical fiber communication system
Frontiers of Optoelectronics, 2023 Optical fiber communication networks play an important role in the global telecommunication network. However, nonlinear effects in the optical fiber and transceiver noise greatly limit the performance of fiber communication systems.
Zheng Liu +5 more
doaj +1 more source
Reply to "Comment on `Performance of different synchronization measures in real data: A case study on electroencephalographic signals'" [PDF]
, 2005 We agree with the Comment by Nicolaou and Nasuto about the utility of mutual information (MI) when properly estimated and we also concur with their view that the estimation based on k nearest neighbors gives optimal results.
Grassberger, P. +2 more
core +1 more source
Energy and Information Fluxes at Upper Ocean Density Fronts
Fluids, 2023 We present large eddy simulations of a midlatitude open ocean front using a modified state-of-the-art computational fluid dynamics code. We investigate the energy and information fluxes at the submesoscale/small-scale range in the absence of any ...
Pablo Cornejo, Adolfo Bahamonde
doaj +1 more source
Improved Lower Bounds on Mutual Information Accounting for Nonlinear Signal-Noise Interaction [PDF]
, 2018 In fiber-optic communications, evaluation of mutual information (MI) is still an open issue due to the unavailability of an exact and mathematically tractable channel model.
Agrell, Erik +4 more
core +2 more sources
Conditional Rényi Divergence Saddlepoint and the Maximization of α-Mutual Information
Entropy, 2019 Rényi-type generalizations of entropy, relative entropy and mutual information have found numerous applications throughout information theory and beyond. While there is consensus that the ways A.
Changxiao Cai, Sergio Verdú
doaj +1 more source
Entropy-Based Image Fusion with Joint Sparse Representation and Rolling Guidance Filter
Entropy, 2020 Image fusion is a very practical technology that can be applied in many fields, such as medicine, remote sensing and surveillance. An image fusion method using multi-scale decomposition and joint sparse representation is introduced in this paper.
Yudan Liu +5 more
doaj +1 more source
A Novel Nonparametric Feature Selection Approach Based on Mutual Information Transfer Network
Entropy, 2022 The filter feature selection algorithm is habitually used as an effective way to reduce the computational cost of data analysis by selecting and implementing only a subset of original features into the study.
Kunmei Li, Nasser Fard
doaj +1 more source
Exploiting Multiple Sensory Modalities in Brain-Machine Interfaces [PDF]
, 2009 Recent improvements in cortically-controlled brain-machine interfaces (BMIs) have raised hopes that such technologies may improve the quality of life of severely motor-disabled patients.
Hatsopoulos, Nicholas G. +2 more
core +2 more sources
Organ-focused mutual information for nonrigid multimodal registration of liver CT and Gd–EOB–DTPA-enhanced MRI [PDF]
, 2014 Accurate detection of liver lesions is of great importance in hepatic surgery planning. Recent studies have shown that the detection rate of liver lesions is significantly higher in gadoxetic acid-enhanced magnetic resonance imaging (Gd–EOB–DTPA-enhanced
Acosta +74 more
core +2 more sources