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Model scoring in latent factor models is essential for a broad spectrum of applications such as clustering, change point detection or model order estimation. In a Bayesian setting, model selection is achieved via computation of the marginal likelihood. However, this is a typically challenging task as it involves calculation of a multidimensional integral over all the latent variables. In this paper,...
When the number of receivers p is large compared to the sample size n, it has been widely observed that standard inference solutions are no longer efficient. In this paper, we address such high-dimensional issues related to the estimation of the noise variance. Several authors have reported that the classical maximum likelihood estimator of the noise variance tends to have a downward bias and this...
In this paper, a mixture noise model, which is a sum of symmetric Cauchy and zero-mean Gaussian random variables in time domain, is studied. The Cauchy and Gaussian distributions are characterized by the unknown median γ and variance σ2, respectively. The probability density function (PDF) and characteristic function (CF) of the mixture are also investigated which are calculated by the convolution...
Random projection is a tried-and-true technique in signal processing for reducing sensing complexity while maintaining acceptable performance of downstream processing tasks. In this paper, we investigate random linear projection of point clouds followed by topo-logical data analysis for computing persistence diagrams and Betti numbers. In this first empirical study of its kind in the literature, we...
In signal enhancement applications, a reference signal which provides information about interferences and noise is desired. It can be obtained via a multichannel filter that performs a spatial null in the target position, a so-called target-cancelation filter. The filter must adapt to the target position, which is difficult when noise is active. When the target location is confined to a small area,...
In this paper, we propose a formal methodology for tuning the parameters of a single-microphone speech enhancement system for hands-free devices. The tuning problem is formulated as a large-scale nonlinear programming problem that is solved by a genetic algorithm to determine the global solution. A conversational speech database is automatically generated by modeling the interactivity in telephone...
In this paper, we study the capacity of multiple-input multiple-output (MIMO) systems under the constraint that amplitude-limited inputs are employed. We compute the channel capacity for the special case of multiple-input singleo-utput (MISO) channels, while we are only able to provide upper and lower bounds on the capacity of the general MIMO case. The bounds are derived by considering an equivalent...
The power-line communications channel (PLC) is one of the harsh and challenging channels due to heavy load and noise impairments. Sending and/or receiving of data bits over the PLC channel can be easily affected; therefore, several investigations have been conducted to illustrate interference effects over PLC where intermittent noise plays a major role in this type of communications channel. The in-building...
In this paper, an empirical evaluation of acoustical signals for leakage detection and quantification in underground plastic pipes for main water distribution networks is presented. Several experiments have been carried out to collect acoustic signals generated from various leakage volumes. Upon signals analysis, it is noticed that the acquired signals are so weak and they are buried in the background...
This paper presents a comparison between fractional order controllers and integer order controllers. The well-known PID is the integer order controller chosen whereas the generalized PID and the CRONE (“Commande Robuste d'Ordre Non Entier” which stands for fractional order robust controller) are the fractional order controllers studied. Another big difference between these controllers is that the...
Finding roots of words is widely used in document classification and text mining. Computational methods of text similarity are intensely utilized on the English words and successful outcomes are obtained. On the other hand, applying the aforementioned methods on the Turkish words did not give the similar success. In this study, a novel similarity computation algorithm is developed. By using this algorithm...
The world population is in the midst of a unique and irreversible process of aging. Fall, which is one of the major health threats and obstacles to independent living of elders, will aggravate the global pressure in elders' health care and injury rescue. Thus, automatic fall detection is highly in need. Current proposed fall detection systems either need hardware installation or disrupt people's daily...
We study the effect of language orthographic characteristics on the performance of digital word recognition in degraded documents such as historical documents. We provide a rigorous scheme for quantifying the influence of the orthographic characteristics on the quality of word recognition in such documents. We study and compare several orthographic characteristics for four natural languages and measure...
Adding noise to inputs of some suboptimal detectors or estimators can improve their performance under certain conditions. In this study, a noise enhanced joint detection and estimation system is investigated. Maximization of the system performance is defined as an optimization problem. Statistical characterization of the optimal additive noise distribution is determined. A condition under which performance...
In this study, a new robust distributed detection scheme that operates under non Guassian noise with unknown parameters is developed. Particle filters are utilized for the estimation of unkown noise parameters and the threshold values for the distibuted detection is optimized using particle swarm optimization, leading to a scheme based on particle filtering methods. The probability of error values...
In multisensor data analysis, scene details can be extracted via subspace methods without any prior information on the scene. In these decomposition techniques, data is projected into a new space so that the information in the data is highlighted. In this study, Principal Component Analysis, Independent Component Analysis and Minumum Noise Fractions method are applied to a multi-sensor data composed...
In this study, a method is presented for the removal of electrooculogram (EOG) noise from electroencephalography (EEG) recordings by using recently proposed data driven approach called Empirical Mode Decomposition (EMD). The EMD represents the signal as a combination of Intrinsic Mode Functions (IMFs). It is an important problem to determine which IMFs belong to signal and noise in multi-component...
This paper deals with a steeper approach profile to increase altitude of the aircraft during approach. To allow a standard 3° landing and thus a higher rate of applicability the vertical approach profile is divided into 2 segments. It starts at about 8000ft AGL with a 4,5° slope. At about 1500 ft AGL the approach slope transitions into a standard 3° slope, intercepting the glide slope from above....
This research studies robust uncoded video transmission over wireless fast fading channel, where only statistical channel state information (CSI) is available at the transmitter. We observe that increasing channel diversity for high priority (HP) data is essential to improving the robustness of video transmission in fading channels. By utilizing the noise and loss resilient nature of video, we find...
Edge detection is most popular problem in image analysis. To develop an edge detection method that has efficient computation time, sensing to noise as minimum level and extracting meaningful edges from the image, so that many crowded edge detection algorithms have emerged in this area. The different derivative operators and possible different scales are needed in order to properly determine all meaningful...
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