Browsing by Subject "Signal processing algorithms"

Now showing 1 - 4 of 4

Open Access
Approximate computation of DFT without performing any multiplications: application to radar signal processing
(IEEE, 2014) Arslan, Musa Tunç; Bozkurt, Alican; Sevimli, Rasim Akın; Akbaş, Cem Emre; Çetin, A. Enis
In many radar problems it is not necessary to compute the ambiguity function in a perfect manner. In this article a new multiplication free algorithm for approximate computation of the ambiguity function is introduced. All multiplications (a × b) in the ambiguity function are replaced by an operator which computes sign(a × b)(a + b). The new transform is especially useful when the signal processing algorithm requires correlations. Ambiguity function in radar signal processing requires high number of correlations and DFT computations. This new additive operator enables an approximate computation of the ambiguity function without requiring any multiplications. Simulation examples involving passive radars are presented.
Open Access
Effect of fractional Fourier transformation on time-frequency distributions belonging to the Cohen class
(Institute of Electrical and Electronics Engineers, 1996-02) Özaktaş, Haldun M.; Erkaya, N.; Kutay, M. A.
We consider the Cohen (1989) class of time-frequency distributions, which can be obtained from the Wigner distribution by convolving it with a kernel characterizing that distribution. We show that the time-frequency distribution of the fractional Fourier transform of a function is a rotated version of the distribution of the original function, if the kernel is rotationally symmetric. Thus, the fractional Fourier transform corresponds to rotation of a relatively large class of time-frequency representations (phase-space representations), confirming the important role this transform plays in the study of such representations.
Open Access
Signal processing for three-dimensional holographic television displays that use binary spatial light modulators
(IEEE, 2010) Ulusoy, Erdem; Onural, Levent; Özaktaş, Haldun M.
One of the important techniques used for three dimensional television (3DTV) is holography. In holographic 3DTV, spatial light modulators (SLM) are used as the display device. SLMs that provide the most limited modulation are the binary SLMs, since only two different values can be assigned to their pixels. An important signal processing problem arising here is the determination of the binary signal to be written on the SLM among the possible ones such that the desired light field is generated to the best extent. Many of the proposed methods do not produce satisfactory results in terms of error rate, computational performance or light efficiency. We propose an optical setup to be placed in front of the binary SLM and the associated signal processing algorithm. The proposed system uses a 4-f setup and a periodic mask is placed to the Fourier plane. As a result, the binary SLM is convolved with a series of regularly spaced impulse functions and we get a new SLM which is smaller in pixel count compared to binary SLM but which can provide 16-bit full complex modulation. It becomes easier to generate the desired light field with this new SLM. Also, the required computations are carried out in a fast manner to enable real-time operation. ©2010 IEEE.
Open Access
Special Issue on Advances in Channel Coding
(Korean Institute of Communication Sciences, 2015) Arikan, E.; Lentmaier, M.; Montorsi, G.
Since the invention of turbo codes in 1993 there has been an enormous interest and progress in the field of capacity approaching code constructions. Many classical constructions have been replaced by newer, better performing codes with feasible decoding complexity. Most of these modern code constructions, such as turbo codes, Gallager's low-density parity-check (LDPC) codes and their generalizations, can be modeled by sparse graphical models. Spatial coupling of sparse graphical models has in the last years attracted a lot of interest due to the threshold saturation phenomenon, which leads to capacity achieving performance with iterative message passing decoding. Polar codes are a recently discovered class of capacity achieving codes that are formed by an explicit construction based on a phenomenon called channel polarization. These codes, too, have various low-complexity decoding algorithms based on message passing on a sparse graph that has a recursive structure similar to that of fast transforms in signal processing.