Daniel Rivero

Cognitive Neuroscience · 2010

A researcher in the Science corpus: 2 papers; trusts 13 researchers and is trusted by 11 researchers here, as inferred from the citation graph.

Subfields

• Cognitive Neuroscience — 23 citations into it; #3,333 of 10,852 by trust here, #6,180 by citations
• Signal Processing — 14 citations into it; #2,784 of 7,572 by trust here, #3,673 by citations
• Artificial Intelligence — 13 citations into it

Whom Daniel Rivero trusts overall

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

1. Abdulhamit Subasi
2. Stéphane Mallat
3. Kemal Polat
4. David John Cameron MacKay
5. Ralph G. Andrzejak
6. Inan Güler
7. V. Srinivasan
8. Nihal Fatma Güler
9. Elif Derya Übeyli
10. N. Kannathal

Who trusts Daniel Rivero overall

1. Usha R. Acharya
2. Poomipat Boonyakitanont
3. Varun Bajaj
4. Oliver Faust
5. Ram Bilas Pachori
6. Apiwat Lek-uthai
7. Subbhuraam Vinitha Sree

Papers from Daniel Rivero's perspective

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

1. Indications of nonlinear deterministic and finite-dimensional structures in time series of brain electrical activity: dependence on recording region and brain state. (Physical review. E, Statistical, nonlinear, and soft matter physics)
2. Analysis of EEG records in an epileptic patient using wavelet transform. (Journal of Neuroscience Methods)
3. A neural-network-based detection of epilepsy (Neurological Research)
4. Artificial Neural Network Based Epileptic Detection Using Time-Domain and Frequency-Domain Features (Journal of medical systems)
5. Artificial neural networks: fundamentals, computing, design, and application.
6. Classifying Single Trial EEG: Towards Brain Computer Interfacing (Neural Information Processing Systems)
7. A Practical Bayesian Framework for Backpropagation Networks
8. Recurrent neural networks employing Lyapunov exponents for EEG signals classification (Expert systems with applications)
9. Classification of epileptiform EEG using a hybrid system based on decision tree classifier and fast Fourier transform (Applied Mathematics and Computation)
10. Symmetric–Antisymmetric Orthonormal Multiwavelets and Related Scalar Wavelets☆☆☆

Their papers

• Epileptic seizure detection using multiwavelet transform based approximate entropy and artificial neural networks. (2010) — 415 citations
• Automatic epileptic seizure detection in EEGs based on line length feature and artificial neural networks. (2010) — 447 citations