Musa Peker

Orcid: 0000-0002-6495-9187

According to our database1, Musa Peker authored at least 15 papers between 2014 and 2021.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2021
Classification of hyperspectral imagery using a fully complex-valued wavelet neural network with deep convolutional features.
Expert Syst. Appl., 2021

2020
Classification of sonar echo signals in their reduced sparse forms using complex-valued wavelet neural network.
Neural Comput. Appl., 2020

2018
Image classification using manifold learning based non-linear dimensionality reduction.
Proceedings of the 26th Signal Processing and Communications Applications Conference, 2018

2017
Signal detection based on empirical mode decomposition and Teager-Kaiser energy operator and its application to P and S wave arrival time detection in seismic signal analysis.
Neural Comput. Appl., 2017

2016
A Novel Method for Automated Diagnosis of Epilepsy Using Complex-Valued Classifiers.
IEEE J. Biomed. Health Informatics, 2016

A decision support system to improve medical diagnosis using a combination of k-medoids clustering based attribute weighting and SVM.
J. Medical Syst., 2016

An efficient sleep scoring system based on EEG signal using complex-valued machine learning algorithms.
Neurocomputing, 2016

A new approach for automatic sleep scoring: Combining Taguchi based complex-valued neural network and complex wavelet transform.
Comput. Methods Programs Biomed., 2016

2015
Rapid Automated Classification of Anesthetic Depth Levels using GPU Based Parallelization of Neural Networks.
J. Medical Syst., 2015

Determining the Appropriate Amount of Anesthetic Gas Using DWT and EMD Combined with Neural Network.
J. Medical Syst., 2015

A software tool for complex-valued neural network: CV-ANN.
Proceedings of the 2015 23nd Signal Processing and Communications Applications Conference (SIU), 2015

A novel hybrid method for determining the depth of anesthesia level: Combining ReliefF feature selection and random forest algorithm (ReliefF+RF).
Proceedings of the International Symposium on Innovations in Intelligent SysTems and Applications, 2015

A comparison of different classification algorithms for determining the depth of anesthesia level on a new set of attributes.
Proceedings of the International Symposium on Innovations in Intelligent SysTems and Applications, 2015

2014
EEG sinyallerinden anomali tespiti (Anomaly detection in EEG signals)
PhD thesis, 2014

A Comparative Study on Classification of Sleep Stage Based on EEG Signals Using Feature Selection and Classification Algorithms.
J. Medical Syst., 2014


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