In this paper we introduce a new class of filters, the generalized feedforward structures, that combine attractive properties of the moving average (MA) filters for adaptation (i.e. fast algorithms, trivial stability) with some of the power of autoregressive moving average (ARMA) filters (i.e. decoupling of the length of the impulse response with filter order). Preliminary results show that thi...

The least-mean-square (LMS) estimator is a nonlinear estimator with information dependencies spanning the entire set of data fed into it. The traditional analysis techniques which are used to model this estimator obscure this, restricting the estimator to the finite set of data sufficient to span the length of its filter. The finite Wiener filter is thus often considered a bound on the performa...

A unified linear algebraic approach to adaptive signal processing (ASP) is presented. Starting from just Ax=b, key ASP algorithms are derived in a simple, systematic, and integrated manner without requiring any background knowledge to the field. Algorithms covered are Steepest Descent, LMS, Normalized LMS, Kaczmarz, Affine Projection, RLS, Kalman filter, and MMSE/Least Square Wiener filters. By...

Several adaptive order statistic filters (OSF) are developed and compared for channel characterization and noise suppression in images and 3-D CT data. Emphasis has been put on the situation when a noisefree reference image is not available but instead we can have a sequence of two noisy versions of the same image (or a 3-D data slice). One of the noisy images is used as the reference in the OS...

The accuracy of channel estimation (CE) significantly affects the performance of the coherent rake receiver in DS-CDMA systems. It is desirable to employ a CE scheme that can provide good estimation performance and fast tracking the channel fading with reduced complexity. Such a CE scheme needs to employ a so-called channel estimation filter (CEF) that can effectively reduce the noise effect ac...

Multiplicative speckle noise which is inherently present in medical ultrasound images degrades the important clinical informations and badly affects the quality of the diagnosis. It is necessary to reduce the speckle noise to improve the visual quality of ultrasound images for better diagnoses. In this paper, a wavelet based method for despeckling of the ultrasound images is introduced where a ...

periodic noises are unwished and spurious signals that create repetitive pattern on images and decreased the visual quality. firstly, this paper investigates various methods for reducing the effects of the periodic noise in digital images. then an adaptive optimum notch filter is proposed. in the proposed method, the regions of noise frequencies are determined by analyzing the spectral of noisy...

A new algorithm is proposed for updating the weights of an adaptive filter. The proposed algorithm is a modification of an existing method, namely, the clipped LMS, and uses a three-level quantization (+1, 0,−1) scheme that involves the threshold clipping of the input signals in the filter weight update formula. Mathematical analysis shows the convergence of the filter weights to the optimum Wi...

Mrstract—The notion is exploded that to build a Kalman–Bucy filter, one needs to know tbe whole structure of the signal generating process. It is shown that the filter is constructible knowing precisely those covariwrces required to construct a Wiener filter, and no more, and that the filter is independent of the particular models of the processes generating these covariances. Performance of th...

A pitch-synchronous (PS) auditory feature extraction method based on ZCPA (Zero-Crossings Peak-Amplitudes) was proposed previously and showed more robustness over a conventional ZCPA and MFCC based features. In this paper, firstly, a non-linear adaptive threshold adjustment procedure is introduced into the PS-ZCPA method to get optimal results in noisy conditions with different signal-to-noise ...