Sequential Bayesian filters in non-linear dynamic systems require the recursive estimation of predictive and posterior probability density function (pdf). This paper introduces a filter called adaptive kernel Kalman (AKKF). The AKKF approximates arbitrary pdf hidden states using mean embedding (KME) reproducing Hilbert space (RKHS). In parallel with KME, some particles data are used to capture ...

In this paper, we introduce the concepts of right, left and product stabilizers on hoops and study some properties and the relation between them.  And we try to find that how they can be equal and investigate that under what condition they can be filter, implicative filter, fantastic and positive implicative filter. Also, we prove that  right and product stabilizers are filters and if they are ...

An edge detection scheme is developed robust enough to perform well over a wide range of signal-to-noise ratios. It is based upon the detection of zero crossings in the output image of a nonlinear Laplace filter. Specific characterizations of the nonlinear Laplacian are its adaptive orientation to the direction of the gradient and its inherent masks which permit the develop ment of approximatel...

We develop a new filter which combines spatially adaptive noise filtering in the wavelet domain and temporal filtering in the signal domain. For spatial filtering, we propose a new wavelet shrinkage method, which estimates how probable it is that a wavelet coefficient represents a “signal of interest” given its value, given the locally averaged coefficient magnitude and given the global subband...

This paper presents an empirical mode decomposition (EMD) based adaptive filter (AF) for channel estimation in OFDM system.  In this method, length of channel impulse response (CIR) is first approximated using Akaike information criterion (AIC). Then, CIR is estimated using adaptive filter with EMD decomposed IMF of the received OFDM symbol. The correlation and kurtosis measures are used to sel...

In this work we explore direct reconstruction algorithms for Computed Tomography, based on principles of Filtered Back-Projection (FBP). Special attention is given to the problem of image reconstruction in Region Of Interest (ROI) from truncated projections. In the proposed linear reconstruction scheme the ramp filter of FBP is replaced with a statistically trained spatially-variant 2-D convolu...

in this paper, we introduce the concepts of right, left and product stabilizers on hoops and study some properties and the relation between them.  and we try to find that how they can be equal and investigate that under what condition they can be filter, implicative filter, fantastic and positive implicative filter. also, we prove that  right and product stabilizers are filters and if they are ...

unknown noise and artifacts present in medical signals with  non-linear fuzzy filter will be estimate and then removed. an adaptive neuro-fuzzy interference system which has a nonlinear  structure presented  for the noise function prediction by before samples. this paper is about a neuro-fuzzy method to estimate unknown noise of electrocardiogram (ecg) signal. adaptive neural combined with fuzz...

we compare performance of adaptive schemes which are based on radial-basis functions and kalman filters for fast extraction of auditory evoked potentials. moreover, we propose a new method based on evoked potential modeling in the kalman filter framework, which can improve the accuracy compared to the existing methods. simulation results show that adaptive schemes and the kalman method are not ...