Estimation problems with bounded, uniformly distributed noise arise naturally in reconstruction problems from over complete linear expansions with subtractive dithered quantization. We present a simple recursive algorithm for such bounded-noise estimation problems. The mean-square error (MSE) of the algorithm is “almost” (1 ), where is the number of samples. This rate is faster than the (1 ) MS...

localizing the optic disc (od) in retinal fundus images is of critical importance, since it is very similar to hard exudates (found in pathology) in color and brightness. because of the importance of od localization in clinical applications, many techniques have been developed. in this paper, we present the results obtained from two methods, correlation and least square, to approximate the opti...

The simultaneous recording of electroencephalogram (EEG) and functional magnetic resonance image (fMRI) is a promising tool that is capable of providing high spatiotemporal brain mapping, with each modality supplying complementary information. One of the major barriers to obtain high-quality simultaneous EEG/fMRI data is that pulsatile activity due to the heartbeat induces significant artifacts...

Abstract— In this paper, Recursive least square (RLS) based complex Adaptive notch filter (ANF) using Steiglitz-McBride (SM) method is proposed to suppress the Radio frequency interference (RFI) in very-highspeed digital subscriber line (VDSL) systems. The proposed RLS-SM ANF converges fast and requires less computational complexity than the existing direct form constrained ANF using recursive ...

The intelligent fuzzy input estimator is used to estimate the input force of the rigid bar structural system in this study. The fuzzy Kalman filter without the input term and the fuzzy weighting recursive least square estimator are two main portions of this method. The practicability and accuracy of the proposed method were verified with numerical simulations from which the input forces of a ri...

Givens rotation is the most commonly used method in performing the QR decomposition (QRD) updating. The generic formula for these rotations requires explicit square-root (sqrt) computations which constitute a computational bottleneck and are quite undesirable from the practical VLSI circuit design point of view. So far, there has been more than ten known sqrt-free algorithms. In this correspond...

This paper addresses the QR decomposition and UD factorization based square-root algorithms of the recursive least-squares (RLS) Wiener fixed-point smoother and filter. In the RLS Wiener estimators, the Riccati-type difference equations for the auto-variance function of the filtering estimate are included. Hence, by the roundoff errors, in the case of the small value of the observation noise va...

A new multichannel filtered-x recursive least square algorithm for active noise control systems is proposed. It is shown that the use of the filtered-x structure, instead of the commonly used modified filtered-x structure lead to a more efficient implementation and similar convergence performance and stability. The paper is also focused on examining the benefits of auxiliary normal equations so...

Noise problems in signals have gained huge attention due to the need of noise-free output signal in numerous communication systems. The principal of adaptive noise cancellation is to acquire an estimation of the unwanted interfering signal and subtract it from the corrupted signal. Noise cancellation operation is controlled adaptively with the target of achieving improved signal to noise ratio....

Although online boosting algorithm has received an increasing amount of interest in visual tracking, it is susceptible to class-label noise. Slight inaccuracies in the tracker can result in incorrectly labeled examples, which degrade the classifier and cause drift. This paper proposes a kernel regression based online boosting method for robust visual tracking. A nonlinear recursive least square...