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Adaptive networks (ANs) rely on local adaptive filters (AFs) and a cooperation protocol to achieve a common goal, e.g., estimating a set of parameters. This protocol fuses the information from the rest of the network based on local combiners whose design impacts directly the network performance. Indeed, although diffusion schemes improve network performance on average, heterogeneity in signal statistics...
We devise novel techniques to obtain the downlink power inducing a given load in long-term evolution (LTE) systems, where we define load as the fraction of resource blocks in the time-frequency grid being requested by users from a given base station. These techniques are particularly important because previous studies have proved that the data rate requirement of users can be satisfied with lower...
We address the problem of Compressed Sensing (CS) with side information. Namely, when reconstructing a target CS signal, we assume access to a similar signal. This additional knowledge, the side information, is integrated into CS via ℓ1-ℓ1 and ℓ1-ℓ2 minimization. We then provide lower bounds on the number of measurements that these problems require for successful reconstruction of the target signal...
This paper presents a new method for texture based image retrieval. The proposed algorithm uses a periodically extended variant of the curvelet transform. The sum of the absolute value of differences in the mean and standard deviation between curvelet wedges representing the query image and the test image is used as the distance index. Performance improvement is demonstrated using the CUReT database,...
In this work, we propose four sketch attacks on H.264/AVC encrypted-compressed video. First, we briefly describe the notion of sketch attack, then deploy the conventional sketch attacks, which are designed for still image, to sketch the frames of H.264/AVC compressed video. Next, we propose four sketch attacks to generate outline of the original frame by using partially decoded information of the...
With the development of communications and network technologies, video streaming service is becoming increasingly important. However, in the transmission of high compressed video, bit-stream is easily damaged by channel errors which will lead to the decline of the video sequence. Error concealment is an effective approach to reduce the influence in error-prone network and notably improve the video...
This work presents a user's authentication system for computational environments based on keystroke dynamics. The methodology proposed is low-cost, non-intrusive and can be applied in areas of monitored access software to increase the level of data security. The algorithm works by monitoring the typing of the user in real time, capturing split times in which the key was pressed and released. Five...
This paper presents a novel method for visualizing vectors of fuzzy numbers. The proposed approach is an extension of the standard polar area diagram and can be applied to a single uncertain vector or a fuzzy weighted graph with vectors of fuzzy attributes on the vertices and/or edges. The resulting diagrams are intuitive to understand and do not require an extensive background in fuzzy set theory...
Particle Swarm Optimization uses noisy historical information to select potentially optimal function samples. Though information-theoretic principles suggest that less noise indicates greater certainty, PSO's momentum term is usually both the least informed and the most deterministic. This dichotomy suggests that while momentum has a profound impact on swarm diversity, it would benefit from a more...
Ranking objects is an essential problem in recommendation systems. Since comparing two objects is the simplest type of queries in order to measure the relevance of objects, the problem of aggregating pair wise comparisons to obtain a global ranking has been widely studied. In order to learn a ranking model, a training set of queries as well as their correct labels are supplied and a machine learning...
Many research works have been developed for stereo image compression purpose by focusing on the disparity compensation technique. For this reason, a great attention should be paid to the generation of the disparity-compensated residual image. Generally, the residual image is computed through a simple substruction of the disparity-compensated reference image from the target one. In this paper, we investigate...
Standard Symbolic Aggregation Approximation (SAX) is at the core of many effective time series data mining algorithms. Its combination with Bag-of-Patterns (BoP) has become the standard approach with state-of-the-art performance on standard datasets. However, standard SAX with the BoP representation might neglect internal temporal correlation embedded in the raw data. In this paper, we proposed time...
Reactive power dispatch (RPD) is a non-linear, mixed integer optimization problem which optimizes grid congestion by minimizing the real power losses and voltage deviation for a fixed economic power dispatch. This paper proposes an efficient and reliable soft-computing technique based on differential evolution (DE) method to solve the RPD problem. Classical DE sometimes suffers from the problem of...
Classification and decision systems in data analysis are mostly based on accuracy optimization. This criterion is only a conditional informative value if the data are imbalanced or false positive/negative decisions cause different costs. Therefore more sophisticated statistical quality measures are favored in medicine, like precision, recall etc‥ Otherwise, most classification approaches in machine...
Walking triangle representations for real optimization are linear representations drawn from the group that acts on simplices of Euclidean space. The representation encodes a series of modifications to an initial simplex, evaluating the quality of the point at its center of mass for the function being optimized. Different operations available in the representation permits easy tailoring of the degree...
Recently, randomized partition trees have been theoretically shown to be very effective in performing high dimensional nearest neighbor search. In this paper, we introduce a variant of randomized partition trees for high dimensional nearest neighbor search problem and provide theoretical justification for its choice. Experiments on various real-life datasets show that performance of this new variant...
A new modified differential evolution algorithm DE-BEA, is proposed to improve the reliability of the standard DE/current-to-rand/1/bin by implementing a new mutation scheme inspired by the bacterial evolutionary algorithm (BEA). The crossover and the selection schemes of the DE method are also modified to fit the new DE-BEA mechanism. The new scheme diversifies the population by applying to all the...
Recently the inverted generational distance (IGD) measure has been frequently used for performance evaluation of evolutionary multi-objective optimization (EMO) algorithms on many-objective problems. When the IGD measure is used to evaluate an obtained solution set of a many-objective problem, we have to specify a set of reference points as an approximation of the Pareto front. The IGD measure is...
Deep architectures have been used in transfer learning applications, with the aim of improving the performance of networks designed for a given problem by reusing knowledge from another problem. In this work we addressed the transfer of knowledge between deep networks used as classifiers of digit and shape images, considering cases where only the set of class labels, or only the data distribution,...
We consider a new variant of successive cancellation decoder (SCD) for polar codes based on the concept of folding, which was proposed in [1], [2] as technique to reduce the decoding latency at the cost of a higher computational complexity. In this paper, we first formally define the multiple folding operation (iterated κ times), which decomposes the original encoding graph into a number of smaller...
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