Browsing by Subject "Digital filters"

Now showing 1 - 9 of 9

Open Access
Adaptive filtering approaches for non-Gaussian stable processes
(IEEE, 1995-05) Arıkan, Orhan; Belge, Murat; Çetin, A. Enis; Erzin, Engin
A large class of physical phenomenon observed in practice exhibit non-Gaussian behavior. In this paper, α-stable distributions, which have heavier tails than Gaussian distribution, are considered to model non-Gaussian signals. Adaptive signal processing in the presence of such kind of noise is a requirement of many practical problems. Since, direct application of commonly used adaptation techniques fail in these applications, new approaches for adaptive filtering for α-stable random processes are introduced.
Open Access
Adaptive filtering for non-gaussian stable processes
(IEEE, 1994) Arıkan, Orhan; Çetin, A. Enis; Erzin, E.
A large class of physical phenomenon observed in practice exhibit non-Gaussian behavior. In this letter, a-stable distributions, which have heavier tails than Gaussian distribution, are considered to model non-Gaussian signals. Adaptive signal processing in the presence of such a noise is a requirement of many practical problems. Since direct application of commonly used adaptation techniques fail in these applications, new algorithms for adaptive filtering for α-stable random processes are introduced.
Open Access
Cumulant based identification approaches for nonminimum phase FIR systems
(IEEE, 1993) Alshebeili, S. A.; Venetsanopoulos, A. N.; Çetin, A. Enis
In this paper, recursive and least squares methods for identification of nonminimum phase linear time-invariant (NMP-LTI) FIR systems are developed. The methods utilize the second- and third-order cumulants of the output of the FIR system whose input is an independent, identically distributed (i.i.d.) non-Gaussian process. Since knowledge of the system order is of utmost importance to many system identification algorithms, new procedures for determining the order of an FIR system using only the output cumulants are also presented. To illustrate the effectiveness of our methods, various simulation examples are presented.
Open Access
Equiripple FIR filter design by the FFT algorithm
(Institute of Electrical and Electronics Engineers, 1997-03) Çetin, A. Enis; Gerek, Ö. N.; Yardımcı, Y.
The fast Fourier transform (FFT) algorithm has been used in a variety of applications in signal and image processing. In this article, a simple procedure for designing finite-extent impulse response (FIR) discrete-time filters using the FFT algorithm is described. The zero-phase (or linear phase) FIR filter design problem is formulated to alternately satisfy the frequency domain constraints on the magnitude response bounds and time domain constraints on the impulse response support. The design scheme is iterative in which each iteration requires two FFT computations. The resultant filter is an equiripple approximation to the desired frequency response. The main advantage of the FFT-based design method is its implementational simplicity and versatility. Furthermore, the way the algorithm works is intuitive and any additional constraint can be incorporated in the iterations, as long as the convexity property of the overall operations is preserved. In one-dimensional cases, the most widely used equiripple FIR filter design algorithm is the Parks-McClellan algorithm (1972). This algorithm is based on linear programming, and it is computationally efficient. However, it cannot be generalized to higher dimensions. Extension of our design method to higher dimensions is straightforward. In this case two multidimensional FFT computations are needed in each iteration.
Open Access
Morphological subband decomposition structure using GF(N) arithmetic
(IEEE, 1996-09) Gürcan, Metin Nafi; Çetin, A. Enis; Gerek, Ömer, N.
Linear filter banks with critical subsampling and perfect reconstruction (PR) property have received much interest and found numerous applications in signal and image processing. Recently, nonlinear filter bank structures with PR and critical subsampling have been proposed and used in image coding. In this paper, it is shown that PR nonlinear subband decomposition can be performed using the Gallois Field (GF) arithmetic. The result of the decomposition of an n-ary (e.g. 256-ary) input signal is still n-ary at different resolutions. This decomposition structure can be utilized for binary and 2k (k is an integer) level signal decompositions. Simulation studies are presented.
Open Access
Optimal filtering in fractional Fourier domains
(Institute of Electrical and Electronics Engineers, 1997-05) Kutay, M. A.; Özaktaş, Haldun M.; Arıkan, Orhan
For time-invariant degradation models and stationary signals and noise, the classical Fourier domain Wiener filter, which can be implemented in O(N log N) time, gives the minimum mean-square-error estimate of the original undistorted signal. For time-varying degradations and nonstationary processes, however, the optimal linear estimate requires O(N/sup 2/) time for implementation. We consider filtering in fractional Fourier domains, which enables significant reduction of the error compared with ordinary Fourier domain filtering for certain types of degradation and noise (especially of chirped nature), while requiring only O(N log N) implementation time. Thus, improved performance is achieved at no additional cost. Expressions for the optimal filter functions in fractional domains are derived, and several illustrative examples are given in which significant reduction of the error (by a factor of 50) is obtained.
Open Access
Reducing the dispersion errors of the finite-difference time-domain method for multifrequency plane-wave excitations
(Taylor & Francis, 2003) Oğuz, U.; Gürel, Levent
We demonstrate the applications of discrete-time signal-processing (SP) techniques for the purpose of generating accurate plane waves in the finite-difference time-domain (FDTD) method. The SP techniques are used either to reduce the high-frequency content of the source excitation or to compute more precise incident-field values in the computational domain. The effects of smoothing windows of various lengths, digital lowpass filters of various bandwidths and characteristics, and polynomial interpolation schemes of various orders are investigated. Arbitrary signals with multifrequency content are considered.
Open Access
Signal-processing techniques to reduce the sinusoidal steady-state error in the FDTD method
(IEEE, 2000-04) Gürel, Levent; Uğur, O.
Techniques to improve the accuracy of the finite-difference time-domain (FDTD) solutions employing sinusoidal excitations are developed. The FDTD computational domain is considered as a sampled system and analyzed with respect to the aliasing error using the Nyquist sampling theorem. After a careful examination of how the high-frequency components in the excitation cause sinusoidal steady-state errors in the FDTD solutions, the use of smoothing windows and digital low-pass filters is suggested to reduce the error. The reduction in the error is demonstrated for various cases.
Open Access
Teager energy based feature parameters for speech recognition in car noise
(Institute of Electrical and Electronics Engineers, 1999-10) Jabloun, F.; Çetin, A. Enis; Erzin, E.
In this letter, a new set of speech feature parameters based on multirate signal processing and the Teager energy operator is introduced. The speech signal is first divided into nonuniform subbands in mel-scale using a multirate filterbank, then the Teager energies of the subsignals are estimated. Finally, the feature vector is constructed by log-compression and inverse discrete cosine transform (DCT) computation. The new feature parameters have robust speech recognition performance in the presence of car engine noise.