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In this paper a new approach is presented to develop the subspace-based speech enhancement for non-stationary noise cases. The new method updates the noise correlation matrix segment-by-segment assuming that only the eigenvalues of the matrix are varying with time. In other words, the characteristic of varying loudness of noise signals is just considered, as it is observed in the modulated white noise...
Image denoising is a classical linear inverse prob- lem with applications in remote sensing, medical imaging, astronomy and surveillance. This article addresses the image denoising problem using a non-local noise estimation based on the spatial redundancy offered by natural images. A low dimensional signal subspace is estimated using the statisti- cal strength of singular value decomposition (SVD),...
In electron microscope tomography, the alignment of tilt series images is a major determining factor of resolution in the 3D reconstruction. One method of tilt alignment uses gold beads deposited on or in the specimen as the fiducial markers. This paper describes an "auto pick" software system which can pick markers automatically. It uses a cross correlation function to find out the shift...
Content-based image retrieval systems typically rely on a similarity measure between image vector representations, such as in bag-of-words, to rank the database images in decreasing order of expected relevance to the query. However, the inherent asymmetry of k-nearest neighborhoods is not properly accounted for by traditional similarity measures, possibly leading to a loss of retrieval accuracy. This...
Rating and ranking of items are important parts of modern electronic commerce. As a result, dishonest business owners are spamming the ecosystems in return for favorable product rankings, while consumers can be misled to purchase low quality products. To protect the interests of consumers, it is a critical task to spot spamming activities and maintain the ecosystems health. Existing spam detection...
This paper studies the problem of tracking with wireless sensor networks (WSNs) using received signal strength (RSS) measurements. The log-normal shadowing associated with RSS measurements from a mobile terminal is correlated both in space and time. We propose a particle filter that exploits the temporal and spatial correlation and estimates the covariance matrix of the measurement noise using the...
Mining users'= topics of interest is one of the most important tasks for social media services. Given known topic associations for some fraction of the users in an online microblogging platform, our goal is to infer the topics of interest for the remaining users in the same site. Specifically, we proposed a novel bi-relational graph model to capture the interactions among users and their shared topics...
To protect computer networks from attacks and hackers, an intrusion detection system (IDS) should be integrated in the security architecture. Although the detection of intrusions and attacks is the ultimate goal, IDSs generate a huge amount of false alerts which cannot be properly managed by the administrator, along with many noisy alerts or outliers. Many research works were conducted to improve...
Electroencephalogram (EEG) signals are of very low amplitude and are easily contaminated by different types of noises like environmental and of non-cerebral in nature. Thus signal pre-processing is a major challenge while dealing with applications involving EEG signals. The scenario becomes much more complex while using commercially available, low resolution devices as they have fewer electrodes....
This paper1 examines two approaches to deal with internal logic upsets inside correlation process used in the tracking process of GPS receivers. These upsets can be produced due to process/voltage and temperature variations coupled with increased advancement of CMOS technology. If any upset occurs when computing the correlation function during each 10 ms, then errors are propagated in tracking loops,...
We have extended the method for modeling the stochastic EM near-field which has already been described in [5, 13] for stationary stochastic fields to the case of cyclostationary fields. Areas of application are the modeling of the electromagnetic interference radiated by digital circuitry inside the system and also into the environment, where the period of the cyclostationary EMI is given by the clock...
This paper presents a measurement technique for the noise figure of differential amplifiers using commercially-available 2-port network analyzers. It is based on the measurement of the noise wave correlation at the output ports of the differential amplifier. A simple measurement setup is used as neither couplers nor calibrated noise sources are required. Measurement results of a radio-frequency low-noise...
In this paper, the Positive constrained Least Absolute Shrinkage and Selection Operator (P-LASSO) is studied for sparse support recovery using the correlation information in Compressive sensing (CS). A structural constraint is obtained for selecting the regularization parameter in the case of additive Gaussian noise. Since the measurements are finite in practice, the probability of successful recovering...
The Hirschfeld-Gebelein-Rényi maximal correlation is a well-known measure of statistical dependence between two (possibly categorical) random variables. In inference problems, the maximal correlation functions can be viewed as so called features of observed data that carry the largest amount of information about some latent variables. These features are in general non-linear functions, and are particularly...
This paper presents an Sparsity Update Subspace Pursuit (SUSP) algorithm for compressed sparse signal reconstruction with unknown sparsity. From practical point of view, the sparsity information is usually unavailable in many applications. In particular, the compressed spectrum sensing application is considered in this paper . The proposed SUSP algorithm begins with sparsity estimation and iteratively...
In this paper, exact performance analyses of the noncoherent ultra-wideband differential transmitted reference systems are evaluated in the correlated Nakagami-m fading channels via applying the characteristic function (CF) method, where the correlated channel model is derived from the bivariate Nakagami-m distribution. Moreover, the independent Nakagami-m fading channel is considered as a special...
Objective measures are favored and widely used by many researchers in evaluating the quality of noise-suppressed speech. A good and reliable objective measure should have property that it could evaluate speech quality in consistent and well correlated with subjective ratings. In this paper, several widely used objective measures are applied to the speech signals with the Chinese languages including...
We investigate the geometric quantum discord of coupling superconducting qubits in Fock state. In the non-Markovian noisy channel, the geometric quantum discord exhibits typical sudden change. The quantum correlation effect between qubits can be enhanced greatly and the initial disappearance time of entanglement can be delayed under certain circumstance through linearly modulating the coupling coefficient...
In this paper, we propose to address the moving average (MA) parameters estimation issue based only on noisy observations and without any knowledge on the variance of the additive stationary white Gaussian measurement noise. For this purpose, the MA process is approximated by a high-order AR process and its parameters are estimated by using an errors-in-variables (EIV) approach, which also makes it...
The method of instrumental variables has been successfully applied to pseudolinear estimation for angle-of-arrival target motion analysis (TMA). The objective of instrumental variables is to modify the normal equations of a biased least-squares estimator to make it asymptotically unbiased. The instrumental variable (IV) matrix, used in the modified normal equations, is required to be strongly correlated...
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