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19 papers · 1 filter
A non-parametric efficient evaluation of Partial Directed Coherence
Pierre-Olivier Amblard
Studying the flow of information between different areas of the brain can be performed by using the so-called Partial Directed Coherence. This measure is usually evaluated by first…
Fundamental performance limits for ideal decoders in high-dimensional linear inverse problems
Anthony Bourrier, Mike E. Davies, Tomer Peleg +2
This paper focuses on characterizing the fundamental performance limits that can be expected from an ideal decoder given a general model, ie, a general subset of "simple" vectors o…
General entropy-like uncertainty relations in finite dimensions
S. Zozor, G. M. Bosyk, M. Portesi
We revisit entropic formulations of the uncertainty principle for an arbitrary pair of positive operator-valued measures (POVM) and , acting on finite dimensional Hilbert sp…
Visualizing the Effects of a Changing Distance on Data Using Continuous Embeddings
Gina Gruenhage, Manfred Opper, Simon Barthelme
Most Machine Learning (ML) methods, from clustering to classification, rely on a distance function to describe relationships between datapoints. For complex datasets it is hard to…
Optimal Asymmetric Binary Quantization for Estimation Under Symmetrically Distributed Noise
Rodrigo Cabral Farias, Eric Moisan, Jean-Marc Brossier
Estimation of a location parameter based on noisy and binary quantized measurements is considered in this letter. We study the behavior of the Cramer-Rao bound as a function of the…
A New Generation of Brain-Computer Interface Based on Riemannian Geometry
Marco Congedo, Alexandre Barachant, Anton Andreev
Based on the cumulated experience over the past 25 years in the field of Brain-Computer Interface (BCI) we can now envision a new generation of BCI. Such BCIs will not require trai…