Subbhuraam Vinitha Sree

Cognitive Neuroscience · 2011–2013

A researcher in the Science corpus: 3 papers; trusts 10 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Cognitive Neuroscience — 38 citations into it
• Artificial Intelligence — 21 citations into it
• Signal Processing — 20 citations into it
• Molecular Biology — 7 citations into it

Whom Subbhuraam Vinitha Sree trusts overall

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

1. Hasan Ocak
2. Hojjat Adeli
3. Samanwoy Ghosh-Dastidar
4. Abdulhamit Subasi
5. N. Kannathal
6. Ling Guo
7. V. Srinivasan
8. Usha R. Acharya
9. Rajendra Acharya
10. Alexandros T. Tzallas

Who trusts Subbhuraam Vinitha Sree overall

1. Usha R. Acharya

Papers from Subbhuraam Vinitha Sree's perspective

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

1. Analysis of EEG records in an epileptic patient using wavelet transform. (Journal of Neuroscience Methods)
2. 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)
3. A neural-network-based detection of epilepsy (Neurological Research)
4. Entropies for detection of epilepsy in EEG (Comput. Methods Programs Biomed.)
5. EEG signal classification using wavelet feature extraction and a mixture of expert model (Expert systems with applications)
6. Pattern Classification
7. Epileptic seizure detection using multiwavelet transform based approximate entropy and artificial neural networks. (Journal of Neuroscience Methods)
8. Application of Non-Linear and Wavelet Based Features for the Automated Identification of Epileptic EEG signals (International Journal of Neural Systems)
9. Physiological time-series analysis using approximate entropy and sample entropy. (American Journal of Physiology. Heart and Circulatory Physiology)
10. A new supervised learning algorithm for multiple spiking neural networks with application in epilepsy and seizure detection (Neural Networks)

Their papers

• Automated EEG analysis of epilepsy: A review (2013) — 816 citations
• Thermography Based Breast Cancer Detection Using Texture Features and Support Vector Machine (2012) — 296 citations
• Application of Recurrence Quantification Analysis for the Automated Identification of Epileptic EEG Signals (2011) — 317 citations