Sultan Aldirmaz

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The linear canonical transform (LCT) is a powerful tool for signal processing applications and is also the generalized form of the well-known transforms such as Fourier, fractional Fourier and Fresnel transforms, and some operators such as scaling, chirp multiplication and chirp convolution. The LCT is characterized by a 2 × 2 unit-determinant matrix(More)
We investigate the performance of frequency division multiplexed (FDM) signals, where multiple orthogonal Hermite-Gaussian carriers are used to increase the bandwidth efficiency. Multiple Hermite-Gaussian functions are modulated by a data set as a multicarrier modulation scheme in a single time-frequency region constituting toroidal waveform in a(More)
A novel short-time Fourier transform (STFT)based interference excision algorithm in direct-sequence spread spectrum (DS-SS) communication systems is introduced. The proposed excision algorithm is developed for chirp-type signals that have broadband frequency characteristics. It is based on the time-frequency analysis of received signals. To analyze the(More)
As one of the renewable energy sources, wind energy has received great attention in Turkey as in the rest of the world in the last decade. Despite of this trend, there is an increasing number of assessment reports stating the impact of wind farms on the performance degradation of electromagnetic propagation systems. In this paper, wind turbines' effects on(More)
Compressive sensing is a new technique that allows sampling at very low rates compared to the Nyquist sampling rate, if the signal is sparse. Thus the signal should either be sparse in time domain or we should be able to determine any domain in which the signal is represented sparsely. In the reconstruction process, the signal is reconstructed by using(More)
A novel adaptive filtering technique based on fractional Fourier domains to suppress non-stationary noise is investigated and analyzed in this paper. In case of adapting in fractional Fourier domains, the MSE of ANC systems improved at least twice compared to the time-domain adaptation.