Florian Losch

Cognitive Neuroscience · 2006–2008

A researcher in the Science corpus: 3 papers; trusts 7 researchers and is trusted by 14 researchers here, as inferred from the citation graph.

Subfields

Whom Florian Losch trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

  1. Benjamin Blankertz
  2. K. Müller
  3. R. Golden
  4. Herbert Ramoser
  5. Jonathan R. Wolpaw
  6. Gert Pfurtscheller
  7. Christoph Guger

Who trusts Florian Losch overall

  1. Benjamin Blankertz
  2. Luis F. Nicolás-Alonso
  3. Kai Keng Ang
  4. Fabien Lotte
  5. Carmen Vidaurre
  6. Brendan Z. Allison
  7. K. Müller
  8. Jaime Gómez Gil

Papers from Florian Losch's perspective

Ordered by how strongly the researchers Florian Losch trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Optimal spatial filtering of single trial EEG during imagined hand movement. (IEEE transactions on rehabilitation engineering)
  2. Brain-computer interfaces for communication and control. (Clinical Neurophysiology)
  3. Real-time EEG analysis with subject-specific spatial patterns for a brain-computer interface (BCI). (IEEE transactions on rehabilitation engineering)
  4. Boosting bit rates in noninvasive EEG single-trial classifications by feature combination and multiclass paradigms (IEEE Transactions on Biomedical Engineering)
  5. Control of a two-dimensional movement signal by a noninvasive brain-computer interface in humans. (Proceedings of the National Academy of Sciences of the United States of America)
  6. Design and implementation of a brain-computer interface with high transfer rates (IEEE Transactions on Biomedical Engineering)
  7. How many people are able to operate an EEG-based brain-computer interface (BCI)? (IEEE transactions on neural systems and rehabilitation engineering)
  8. Classifying Single Trial EEG: Towards Brain Computer Interfacing (Neural Information Processing Systems)
  9. Optimizing Spatial filters for Robust EEG Single-Trial Analysis
  10. Learning to control brain activity: a review of the production and control of EEG components for driving brain-computer interface (BCI) systems. (Brain and Cognition)

Their papers