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    Diagnosis of congestive heart failure using Poincare map plot
    (2012) Yayik, Apdullah; Kutlu, Yakup
    In this study, in order to diagnose congestive heart failure patients (CHF), Poincare map obtained from raw ECG data is used. CHF and normal ECG data, which are distributed freely via internet, are analyzed. Poincare map is divided into equal rectangle cells and points in all of the cells are determined. These values are used for knn (k-nearest neighbour) classification. At the result of this study, it is considered that CHF patients and normal people can be separated each other using features obtained from Poincare map of Raw ECG record. © 2012 IEEE.
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    Improving Pseudo Random Number Generator Using Artificial Neural Networks
    (Ieee, 2013) Yayik, Apdullah; Kutlu, Yakup
    Pseudo-random number generators generate sequent of digits that cannot be expected before. Random number generators are used in lots of studies especially physical and statical implementations. In this paper; by using Multi-Layer Perceptron Neural Network, a traditional random number generator is strengthened. In the end of the study; both of random number generators are tested by some randomness tests of National Institute of Standard Technology test suite. As a result, it is learned that Neural Networks can generate good random numbers.
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    NEURAL NETWORK BASED CRYPTOGRAPHY
    (Acad Sciences Czech Republic, Inst Computer Science, 2014) Yayik, Apdullah; Kutlu, Yakup
    In this paper, neural network based cryptology is performed. The system consists of two stages. In the first stage, neural network-based pseudo-random numbers (NPRNGs) are generated and the results are tested for randomness using National Institute of Standard Technology (NIST) randomness tests. In the second stage, a neural network-based cryptosystem is designed using NPRNGs. In this cryptosystem, data, which is encrypted by non-linear techniques, is subject to decryption attempts by means of two identical artificial neural networks (ANNs). With the first neural network, non-linear encryption is modeled using relation-building functionality. The encrypted data is decrypted with the second neural network using decision-making functionality.
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    Topographic Analysis and Diagnosis of Congestive Heart Failure Using Second-Order Difference Plot
    (Ieee, 2014) Yayik, Apdullah; Kutlu, Yakup
    In this study, in order to diagnose congestive heart failure (CHI) patients, second-order difference map (SDOP) features obtained from raw electrocardiogram (EEG) data is used CHF and normal patients' electrocardiogram data which are distributed freely via internet, is analyzed By U-matrix presentation of Self-Organized Maps, distances between groups and clusters are examined 1x16 Axed SODP features of raw EEG data obtained from normal and CHF patients can successfully be classified using U-matrix presentation of SOM. As a classifier Neural Network based classifier is applied and %99.9 over all accuracy performance is reached