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In this study we investigate coding artifacts in H.264 baseline profile. A psychophysical experiment was conducted that collected data about the subjectively perceived annoyance of short video sequences as well as the perceived strength of three coding artifacts. The data provided by 52 subjects is analyzed with respect to bitrate and intra period of the encoded sequences. A new data analysis method...
Mathematical/statistical modeling of biological systems is a desired goal for many years. It aims to be able to accurately predict the operation of such systems under various scenarios using computer simulations. In this paper we revisit Gillespie's Stochastic Simulation Algorithm for biochemical systems and we suggest an equivalent Markov Model for it. We show that under certain conditions it is...
Convergences and divergences among related organisms (S.cerevisiae and C.albicans for example) or same organisms (healthy and disease tissues for example) can often be traced to the differential expression of specific group of genes. Yet, algorithms to characterize such differences and similarities using gene expression data are not well developed. Given two related organisms A and B, we introduce...
Matching aerial images with map data is an important task in several remote sensing applications such as autonomous navigation, cartography, oceanography. The unique and distinctive shapes of coastlines can be effectively utilized to solve this problem. In this study a completely automatic scheme is proposed to detect coastlines using multi-resolution texture analysis and to match the detected coastlines...
Fast RLS algorithms are known to present numerical instability and this instability is originated in the forward prediction parameters. In this paper, A simplified FTF-Type algorithm for adaptive filtering is presented. The basic idea behind the proposed algorithm is to avoid using the backward variables. The algorithm obtained is less complex than the existing numerically stable fast FTF and shows...
A pseudo-2D Hidden Markov Model-based face identification system employing the edge-based feature representation has been developed. In the HMM-based face recognition algorithms, 2D discrete cosine transform (DCT) is often used for generating feature vectors. However, DCT-based feature representations are not robust against the variation in illumination changes. In order to enhance the robustness...
This paper presents a low-complexity shot detection method for real-time, low bitrate video coding. Aimed at compression efficiency instead of frame indexing or other purposes, it is based on the macroblock intra/inter decision and the use of two thresholds. The first threshold is fixed and the second one is adaptive, providing robust scene change detection on almost all conditions (camera motion,...
In this paper, we address the problem of blind parameter estimation and multiuser detection for impulse radio ultra-wide band (UWB) systems under frequency selective fading. We consider unknown ambient and impulsive noise parameters as well as an unknown UWB channel characterized by a large number of taps, and propose a blind Bayesian multiuser detector based on Gibbs sampling. Because Gibbs sampler...
We address the phase noise and the superresolution problem in Toeplitz matrix-based spectral estimates. The Toeplitz autocorrelation (AC) matrix approach in spectral estimation brings in an order of magnitude computational advantage while the price paid is the phase noise that becomes effective at high signal-to-noise ratios (SNR). This noise can be mitigated with windowing the data though some concomitant...
The aim of this paper is robust identification of a lightly damped flexible beam model with parametric and non-parametric uncertainties. We examined two main approaches for robust identification which are based on deterministic and stochastic assumptions on uncertainties. In the first case uncertainties are assumed to be unknown but bounded which is known as “Set Membership” method (SM), while stochastic...
Multiple antennas at the transmitter and the receiver have the potential to either increase the data rate through spatial multiplexing or enhance the quality of transmission through exploitation of diversity. In this paper, we address the problem of multi-user multiplexing using spatial diversity techniques so that a base station could serve multiple users in the same frequency band making huge saving...
The present contribution deals with the statistical tool of Independent Component Analysis (ICA). The focus is on the deflation approach, whereby the independent components are extracted one after another. The kurtosis-based FastICA is arguably one of the most widespread methods of this kind. However, its features, particularly its speed, have not been thoroughly evaluated or compared, so that its...
We propose to extend block-based video-coding by an adaptive color space transform. The presented technique enables an encoder to switch between several given color space representations with the objective to maximize the overall rate-distortion gain. Simulations based on the current draft of the H.264/MPEG4-AVC 4∶4∶4 extensions demonstrate that our technique provides a rate-distortion performance...
The problem of signal detection and trajectory estimation of a dynamic system when a variable number of measurements can be taken is here considered. A sequential probability ratio test (SPRT) when the parameter space has infinite cardinality is proposed for the detection problem while trajectory estimation relies upon a maximum-a-posteriori (MAP) estimate. The computational costs of the proposed...
Audio watermarking, or embedding information in a host signal was originally used for digital copyright protection purposes. As audio coding, watermarking is progressively brought in audio processing applications.
This paper introduces a multi-pronged approach for segmentation of color images of man-made structures like cargo containers, buildings etc. A combination of vector angle computation of the RGB data and the absolute difference between the intensity pixels is used to segment the image. This method has the advantage of removing intensity based edges that occur where the saturation is high, while preserving...
The objective of this paper is to propose a signal processing scheme that employs subspace-based spectral analysis for the purpose of formant estimation of speech signals. Specifically, the scheme is based on decimative spectral estimation that uses Eigenanalysis and SVD (Singular Value Decomposition). The underlying model assumes a decomposition of the processed signal into complex damped sinusoids...
This paper addresses the problem of classifying digital modulations in a Rayleigh fading environment. The first step of the proposed classifier consists of estimating the parameters unknown by the receiver, i.e., the fading amplitude, phase offset, and residual carrier frequency. These unknown parameters appearing in the class conditional densities are then replaced by their estimates, resulting in...
In this paper we present a streamlined framework for adaptive filters within which all major adaptive filter algorithms can be seen as special cases. The framework involves three ingredients: 1) A preconditioned Wiener Hopf Equation, 2) Its simplest possible iterative solution through the Richardson iteration, and 3) An estimation strategy for the autocorrelation matrix, the cross correlation vector...
It is generally believed that the external noise added to speech signal corrupts speech spectrum and so speech features. This feature corruption degrades speech recognition systems performance. One solution to cope with the speech feature corruption is reducing the noise effects on the speech spectrum. In this paper, we propose to filter speech spectrum in order to enhance its spectral peaks in presence...
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