A new filter named the maximum likelihood-based iterated divided difference filter (MLIDDF) is developed to improve the low state estimation accuracy of nonlinear state estimation due to large initial estimation errors and nonlinearity of measurement equations. The MLIDDF algorithm is derivative-free and implemented only by calculating the functional evaluations. The MLIDDF algorithm involves t...

A decision feedback equalizer (DFE) containing a feedback filter with both poles and zeroes i s proposed for high-speed digital communications over the subscriber loop. The feedback filter is composed of two sections: a relatively short finite impulse response (FIR) filter that cancels the initial part of the channel impulse response, which may contain rapid variations due to bridge taps; and a...

An adaptively regularized kernel-based fuzzy C-means clustering framework is proposed for segmentation of brain magnetic resonance images. The framework can be in the form of three algorithms for the local average grayscale being replaced by the grayscale of the average filter, median filter, and devised weighted images, respectively. The algorithms employ the heterogeneity of grayscales in the...

Lung cancer disease is one of the dreaded diseases in the developing and developed countries. The pre-diagnosis is an important stage of identifying the target group of persons who can undergo diagnosis stage. Here in this study, prediction of lung cancer is attempted based on symptoms and risk factors. Data collected from the confirmed case of the patients is pre-processed based on multi filte...

In this paper, we present both a methodology and a rationale for designing filters based on spatial smoothness and accuracy criteria. Frequency based methods have been used to design function and derivative reconstruction filters especially in image and signal processing. Desired filter characteristics are specified in terms of spectral properties. However, for visualization and image synthesis...

Radio Frequency (RF) interference is inherent in all wireless systems and is one of the most significant design parameters of cellular and other mobile systems. In this paper, it is shown that how a non-linear adaptive Volterra filter (Polynomial filter where input and output signals are related through Volterra series) helps track the statistics of the input data and dynamics of a direct seque...

Acting as the complementary tool to the mean-line based filtration techniques, e.g. the Gaussian filter, morphological filters are function oriented and relevant to geometrical features of surfaces. This paper aims to present an introduction to morphological filters in surface metrology. By introducing mathematical morphology, morphological filters offer more capabilities than the early envelop...

Fusion algorithms for optimal estimation of dynamical systems are presented. The two algorithms presented, focus on fusion in the presence of asynchronous measurements that are obtained at differing sampling instances and rates. First of these Kalman filter based schemes is based on multiple measurement model switching. The second scheme essentially propagates all the measurements until the upd...

Noise reduction in ECG signal is an important task of biomedical science.Adaptive filtering algorithms are evolving rapidly in biomedical science to remove the noise by an appreciable amount.In this paper, noise of ECG signal has been reduced by using adaptive filter based on RLS algorithm.The RLS algorithm performs well irrespective of the nature of signal and noise and its convergence rate is...