Electrical - Electronic Engineering / Elektrik - Elektronik Mühendisliği

Permanent URI for this collectionhttps://hdl.handle.net/11147/11

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Institution Author: search.filters.institutionAuthor.Savacı, Ferit AcarWoS Q: search.filters.wosQuartile.Q3

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Now showing 1 - 4 of 4
  • Article
    Citation - WoS: 1
    Citation - Scopus: 2
    Blind Recognition of Alpha-Stable Random Carrier Signals by an Eavesdropper in Random Communication Systems
    (Institution of Engineering and Technology, 2019) Ahmed, Areeb; Savacı, Ferit Acar
    Invisibility of alpha-stable (alpha -stable) noise as carrier signals, in the presence of additive white Gaussian noise (AWGN) as channel noise, is a key factor to ensure covert transmission by employing random communication systems (RCSs). This study introduces a novel blind recognition method for an eavesdropper to detect the presence of real-valued symmetric and skewed alpha -stable random carrier signals in the presence of AWGN. The introduced method is based on the proposed random carrier signal recogniser (RCSR), which consists of fractional lower-order auto-covariance block, threshold control block and the random carrier signal recognition indicator. The proposed RCSR first detects the possible presence of alpha -stable random carrier signals and then recognises the impulsiveness and skewness parameters, exploited by the transmitter and the intended receiver, to extract covertly conveyed binary information. However, the determined covert range can be adopted to perform secure transmission by RCSs. The simulation results reflect the simplicity of the proposed method as it is capable of performing effectively in real time by utilising extremely less number of observed samples.
  • Article
    Citation - WoS: 5
    Citation - Scopus: 5
    Inverse System Approach To Design Alpha-Stable Noise Driven Random Communication System
    (Institution of Engineering and Technology, 2020) Savacı, Ferit Acar; Ahmed, Areeb
    In the proposed random communication system (RCS), the alpha-stable (alpha-stable) noise as a random carrier drives the transmitter which is modelled by the linear dynamical system and the skewness parameter of the random carrier encodes the binary messages. By selecting the receiver as the inverse system of the transmitter, the output of the receiver is ensured to be alpha-stable noise whose skewness parameters are then estimated to decode the binary messages. The response of a linear system to an alpha-stable process is again alpha-stable process, however, the skewness parameters of the response differs from that of the input which can only be recovered at the output of the inverse system. Hence, estimation of skewness parameter by an eavesdropper, without using the inverse system, will not reveal the true binary messages while the intended receiver truly decodes the binary messages. The proposed inverse system based RCS provides efficient performance which is shown by comparing the bit error rate of the intended receiver and an eavesdropper where the enhancement in covertness is shown by evaluating the covertness values of the proposed RCS.
  • Article
    Citation - WoS: 9
    Citation - Scopus: 13
    Synchronisation of Alpha-Stable Levy Noisebased Random Communication System
    (Institution of Engineering and Technology, 2018) Ahmed, Areeb; Savacı, Ferit Acar
    In this study, the pilot-assisted synchronisation method for a random communication system (RCS) has been proposed. The pilot symbol, which has alpha-stable distribution, has been used to establish synchronisation and to maintain covertness in the RCS. The introduced synchronisation block (SB) consists of fractional lower-order covariance-based correlators (FLOCCs), threshold detectors (TDs) and the synchronisation control block. To measure the performance of the proposed SB, the performance criterion, i.e. confidence ratio (CR), has been proposed. The reliability of the proposed SB can be enhanced by altering the CR and the achieved CR by using the FLOCCs and TDs in SB.
  • Article
    Skewed Alpha-Stable Distributions for Modeling and Classification of Musical Instruments
    (Türkiye Klinikleri Journal of Medical Sciences, 2012) Özbek, Mehmet Erdal; Çek, Mehmet Emre; Savacı, Ferit Acar
    Music information retrieval and particularly musical instrument classification has become a very popular research area for the last few decades. Although in the literature many feature sets have been proposed to represent the musical instrument sounds, there is still need to find a superior feature set to achieve better classification performance. In this paper, we propose to use the parameters of skewed alpha-stable distribution of sub-band wavelet coefficients of musical sounds as features and show the effectiveness of this new feature set for musical instrument classification. We compare the classification performance with the features constructed from the parameters of generalized Gaussian density and some of the state-of-the-art features using support vector machine classifiers.