Kemal Gurkan Toker

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K-nearest neighbour (K-NN) is a supervised classification technique that is widely used in many fields of study to classify unknown queries based on some known information about the dataset. K-NN is known to be robust and simple to implement when dealing with data of small size. However its performance is slow when data is large and has high dimensions.(More)
In this paper, canonical correlation analysis is introduced for linear system identification. By taking into account the structural similarities between difference equation representation of a linear discrete time system and canonical correlation analysis, it is shown that canonical correlation analysis can be used for system identification. The proposed(More)
In this paper, online signature recognition is examined by using K Nearest Neighborhood (KNN) method. The signatures are collected by an Android application which can extract the dynamic and spatial information of the signatures. In this frame, a signature database is consisting of a total of 120 signatures taken from 12 different person. The purpose of(More)
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