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The work in this manuscript proposes to enhance the secrecy level of wireless systems through the use of a jamming technique that uses uncorrelated reciprocal channel estimations from the legitimate channel as a common random source to select discrete jamming signals in both sides of the legitimate link. After that selection, these jamming signals are combined with data at the legitimate transmitter,...
Dynamic texture describes images sequence that continuously demonstrates movement of pixels intensity change patterns in time, for example, smoke, fire, waterfall, sea-waves, foliage, traffic on highway and so on. Motion coherence analysis on dynamic textures is usually observed through their motion vector fields. We implement strategic motion coherence analysis to evaluate the coherent motion on...
In this paper, we address the problems of frequency and timing synchronization for OFDM/OQAM systems in additive white Gaussian noise (AWGN) channel. A two step preamble based approach for carrier frequency offset (CFO) and timing offset (TO) estimation is proposed. The first step is joint coarse CFO and TO estimation and the second step is fine CFO (FCFO) estimation. We derive the Cramer-Rao lower...
Noise estimation plays an essential role in enhancing the performance of non-coherent spectrum sensors such as energy detectors. If the noise energy is misestimated, detector performance may deteriorate. In this paper, we present an energy detector based on the behavior that Empirical Mode Decomposition (EMD) has on noise-only channels. EMD decomposes time-series signals into a finite set of components...
The performance of stereophonic acoustic echo cancelers is highly dependent on the coherence between the loudspeaker signals. If this is high, convergence is slow, during which audible residual echoes remain. Residual echoes can be reduced by applying a residual echo suppressor to the canceler's output. Yet, in order to obtain the post-filter gains, it is necessary to estimate the residual echoes...
The development of new speech enhancement techniques is a continuous progress to combat the impairment of speech signals by various acoustical environmental influences. In this contribution we propose a new two-stage speech enhancement algorithm, exploiting the source-filter model to decompose a denoised target signal, and specifically we manipulate the excitation signal in the cepstral domain. The...
The paper presents the methods for improving the accuracy of impedance measurements to the root system of plants and the ambient temperature. The proposed methods are based on the digital data processing using the maximum likelihood approach, which helps reduce the cost of the measurement devices. A comparison of the achieved measurements accuracy was carried out using the simulation technique.
This paper investigates the problem of automatic target detection in a Pareto background under multiple target situations. The number of interfering targets is assumed to be unknown. We derive the Enhanced Variability Index Automatic Selection and Detection Constant False Alarm Rate (EVI-ASD-CFAR) Processor. This latter selects and matches dynamically the suitable detector among the Geometric Mean...
We consider stochastic optimization problems in decentralized settings, where a network of agents aims to learn decision variables which are optimal in terms of a global objective which depends on possibly heterogeneous streaming observations received at each node. Consensus optimization techniques implicitly operate on the hypothesis that each node aims to learn a common parameter vector, which is...
One of the considerations for the security of searchable symmetric encryption is leakage, defined as the amount of information regarding stored data known to the adversary. Recently, some papers showed that information extracted from leakages, combined with some prior knowledge, enables practical attacks. In this work, we argue in favour on the security of multiserver block-based SSE to resist such...
In multi-player games with imperfect information, e.g., Poker and Mahjong, they have imperfect information differing from Shogi and Reversi. Therefore, it is difficult to decide optimal movements. In Mahjong, fold is very important, and it is necessary to check predominance between a player's hand and other players' hands. To this end, it is required to estimate the rate arriving at a winning hand...
We present a framework for optimal Bayesian feature selection and missing value estimation. Based on this framework, we derive optimal algorithms under an independent Gaussian model, and provide fast sub-optimal methods with superb performance for a dependent Gaussian model.
In the field of phonetics, voice onset time (VOT) is a major parameter of human speech defining linguistic contrasts in voicing. In this article, a landmark-based method of automatic VOT estimation in acoustic signals is presented. The proposed technique is based on a combination of two landmark detection procedures for release burst onset and glottal activity detection. Robust release burst detection...
In this paper, we propose a simple and effective depth upsampling technique using self-guided residual interpolation. The original residual interpolation requires guidance information such as high-resolution RGB color image. However, self-guided residual interpolation requires only a single depth map. In the proposed algorithm, a tentative estimation of a high-resolution depth map is first generated...
We propose a method to estimate the artistic quality of Haiku (Japanese style short poem) texts using a machine learning approach. Based on the assumption that the artistry of a text stems from its sound factors as well as its meanings, we first constructed two types of vector models, a word-based model and a syllable-based model, converted from Haiku texts. Next, we conducted machine learning for...
Rich information could be extracted from the high dimensional light field (LF) data, and one of the most fundamental output is scene depth. State-of-the-art depth calculation methods produce noisy calculations especially over texture-less regions. Based on Super-pixel segmentation, we propose to incorporate multi-level disparity information into a Bayesian Particle Filtering framework. Each pixels'...
Knowledge of the noise distributions is typically key for reliable state estimation. However, in many applications only the measurement noise can be determined a priori, since only this correspond to measurable quantities. Moreover, modeling of physical systems often leads to nonlinear state-space models with dependent noise sources. Here, we design a computationally-efficient marginalized particle...
In combinatorial optimization, the goal is to find the optimal object from a finite set. Since such problems are hard to be solved, usually some metaheuristics is applied. One of the most successful techniques for a number of classes of problems is Ant Colony Optimization (ACO). Some start strategies can be applied, to the ACO algorithms, to improve their performance. Here, the InterCriteria Analysis...
In this paper, we introduce a novel framework for semi-parametric estimation of an unknown number of signals, each parametrized by a group of components. Via a reformulation of the covariance fitting criteria, we formulate a convex optimization problem over a grid of candidate representations, promoting solutions with only a few active groups. Utilizing the covariance fitting allows for a hyperparameter-free...
Network operators use the reported attainable netdata-rate (AttNDR) of vectored very high speed digital subscriber line 2 (VDSL2) to qualify an upgrade of customers to higher service rates. Unfortunately, the reported AttNDR is only calculated based on reported signal-to-noise ratio (SNR) values on used subcarriers and it may lead to a pessimistic qualification. Instead we calculate the missing SNR...
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