Compared to normal learning algorithms, for example backpropagation, Kalman filter-based algorithm has some better properties, such as faster convergence, although this algorithm is more complex and sensitive to the nature of noises. In this paper, extended Kalman filter is applied to train state-space recurrent neural networks for nonlinear system identification. In order to improve robustness...

This paper assesses the effect of filter spacing on melody recognition by normal-hearing (NH) and cochlear implant (CI) subjects. A new semitone filter spacing is proposed for music. The quality of melodies processed by the various filter spacings is also evaluated. Results from NH listeners showed nearly perfect melody recognition with only four channels of stimulation, and results from CI use...

In this paper, a novel approach is proposed to analyze and minimize fixed-point arithmetic errors for digital filter implementations based on eigenvalue sensitivity measures. First, uncertainties of the filter-parameter caused by roundoff and computational errors are expressed in the function of register length for fixed-point implementations. Sequentially, based on a fixed-point statistical mo...

Sensorineural hearing loss has frequently been shown to result in a loss of frequency selectivity. Less is known about its effects on the level dependence of selectivity that is so prominent a feature of normal hearing. The aim of the present study is to characterize such changes in nonlinearity as manifested in the auditory filter shapes of listeners with mild/moderate hearing impairment. Notc...

Particle filtering is probably the most widely accepted methodology for general nonlinear applications. The performance of a particle filter critically depends on choice proposal distribution. In this paper, we propose using wrapped normal distribution as angular data, i.e. data within finite range (-π,π]. We then use same method to derive density filter, in place standard ...

introduction: the accuracy of analyzing functional mri (fmri) data is usually decreases in the presence of noise and artifact sources. a common solution in for analyzing fmri data having high noise is to use suitable preprocessing methods with the aim of data denoising. some effects of preprocessing methods on the parametric methods such as general linear model (glm) have previously been evalua...

here, we propose an add-drop and a channel drop filter based on two-dimensional photonic crystal all circular ring resonators. these structures are made of a square lattice of silicon rods with the refractive index n1=3.464 surrounded by air (with refractive index n2=1). the broadest photonic band gap occurs at the filling ratio of r/a = 0.17. two linear defect w1 waveguides couple to the ring....

We study the properties and relations of fuzzy pseudo-filters of pseudo-BCK algebras. After we discuss the equivalent conditions of fuzzy normal pseudo-filter of pseudo-BCK algebra (pP), we propose fuzzy implicative pseudo-filter and its relation with fuzzy Boolean filter of (bounded) pseudo-BCK algebras (pP). Then two open problems: “In pseudo-BCK algebra or bounded pseudo-BCK algebra, Is the ...

in this paper we consider several generalizations of the skew t-normal distribution, and some of their properties. also, we represent several theorems for constructing each generalized skew t-normal distribution. next, we illustrate the application of the proposed distribution studying the ratio of two heavy metals, nickel and vanadium, associated with crude oil in shadgan wetland in the south-...

This paper proposes a novel single vehicle tracking algorithm with enhanced reliability for automotive radar systems. The proposed overcomes the weaknesses of probabilistic data association filter (PDAF) in single-target clutter. PDAF is successful normal situations, but may fail to track target owing various factors, such as initialization errors and sudden changes motion. can recover from fai...