Detection of outliers using Fouriertransform

Akkuş, Ekin Can
Purutçuoğlu Gazi, Vilda
Ağraz, Melih
10th International Statistics Congress, 6 - 08 December 2017


Detection of hidden patterns in time series data via multiple-time FOD method
Erkuş, Ekin Can; Purutçuoğlu Gazi, Vilda (2019-06-23)
The periodicity in time series data can be detected by several frequency domains’ methods, especially, by the Fourier transform (FT). FT is a non-parametric method to convert the time domain data into the frequency domain and it is used in many engineering and data science applications. Recently this method which has been used to detect outliers in time series observations where the data may also include some systematic patterns is called “outlier detection via Fourier transform” (FOD). From our previous ...
Detection of a sinusoid by the MRAS approach and input design for parallel MRAS.
Tuncay, arzu; Department of Electrical Engineering (1985)
Detection of component composition mismatch with axiomatic design
Toğay, Cengiz; SUNDAR, Gayathri; Doğru, Ali Hikmet (2006-04-02)
This paper presents a software component composition methodology based on Axiomatic Design theory and Design Structure Matrix. The methodology we propose helps overcome anomalies and functional problems such as deadlock. Our approach can be described in two steps. First, we decompose the system to detect coupled components by using the Design Structure Matrix. Secondly, we represent attribute and method dependencies of the coupled components to identify issues during software composition using Design Matrix...
Oguz, Oguzhan; Muenzenmayer, Christian; Wittenberg, Thomas; ÜNER, AYŞEGÜL; ÇETİN, AHMET ENİS; Atalay, Rengül (2015-10-30)
This paper presents a cancer stem cell detection method using region covariance and codifference method. It focuses on detection of Cancer Stem Cell (CSC) in microscopic images which are stained with CD13 marker. Features of CSC images are extracted by using both covariance method and its multiplication free version codifference method and these features are fed into a Support Vector Machine (SVM) for classification. Experimental results are presented.
Detection of DDoS Attacks and Flash Events Using Shannon Entropy, KOAD and Mahalanobis Distance
Daneshgadeh, Salva; Ahmed, Tarem; Kemmerich, Thomas; Baykal, Nazife (2019-01-01)
The growing number of internet based services and applications along with increasing adoption rate of connected wired and wireless devices presents opportunities as well as technical challenges and threads. Distributed Denial of Service (DDoS) attacks have huge devastating effects on internet enabled services. It can be implemented diversely with a variety of tools and codes. Therefore, it is almost impossible to define a single solution to prevent DDoS attacks. The available solutions try to protect intern...
Citation Formats
E. C. Akkuş, V. Purutçuoğlu Gazi, and M. Ağraz, “Detection of outliers using Fouriertransform,” presented at the 10th International Statistics Congress, 6 - 08 December 2017, 2017, Accessed: 00, 2021. [Online]. Available: