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Power cable incipient faults are single phase short circuits with short duration and little effect on system operation primarily, so detection of incipient faults is needed to keep them from developing into permanent faults. The over-current characteristics caused by different disturbances are compared and the over-currents characteristic quantities are extracted by multi-scale wavelet transform....
Wireless sensor network (WSN) is becoming more and more important with the development of Internet-of-things (IoT), it has been widely used to sense and monitor an area of interest in many scenarios. Since sensors in WSN can suffer from drift or errors with the increase of deployment time, the trustworthiness of sensor data will be affected. In this paper, an algorithm is proposed to detect and calibrate...
Error concealment is a receiver-based post-processing technique that deals with the errors occur in a decoded signal during transmission in the packet loss environments, based on data available only at the decoder. In this paper, we propose a novel error concealment algorithm for the multiview images based on sparse reconstruction. Using a simple combination of the wavelet transform prior to transmitting...
The aim of current research is to develop the algorithm for on-line detection of spike-and-wave discharges (SWDs), which are of a peculiar waveform known to appear in epileptic patients' electroencephalogram. In this study, the wavelet transform was used as a backbone of the algorithm. Considering the possibility of applying the magnetic stimulation therapy in the future, 100% specificity was intended...
Given the importance of an accurate wind speed forecasting for efficient utilization of wind farms, and the volatile nature of wind speed data including its non-linear and uncertain nature, the wind speed forecasting has remained an active field of research. In this study, the non-linearity of wind speed is tackled using artificial neural network and its uncertainty by wavelet transform. To avoid...
Nowadays in industry, data acquisition system signals are often compressed by piecewise linear trending. Many authors have indicated that compression with use of a wavelet transform provides better results. In this paper, the threshold selection algorithms, such as VisuShrink, SureShrink, BayesShrink, and NeighCoeffs are compared experimentally using real industrial data from the Damadics benchmark...
Catheter ablation is an effective therapy to treat atrial fibrillation (AF) whenever the proper atrial regions are targeted. Electro-anatomical mapping is commonly used for that purpose, thus facilitating the location of ablation targets. However, reliable mappings acquisition depends on an accurate detection of local activation waves (LAWs) from atrial electrograms (EGMs). This is currently a handmade...
CT-Scanner devices produce three-dimensional images of the internal structure of the body. In this paper, we propose a method that is based on the analysis of sensor noise to identify the CT-Scanner device. For each CT-scanner we built a reference pattern noise and a correlation map from its slices. Finally, we can correlate any test slice with the reference pattern noise of each device according...
The ability for cellular operators to closely predict the network traffic volume at various locations can be very important for their resource management and dynamic network control including offloading. This work investigate the analysis of the spatial-temporal information of cellular traffic flow and the prediction of cell-station traffic volumes. Based on the integration of K-means clustering,...
Image rendering is to construct a large image from several smaller images. It is very important for stereo image generating and light filed image processing. In this paper, we propose several techniques to improve the performance of image rendering. When perform disparity estimation, higher weights are assigned for edge and corner pixels to increase their effects. When perform linear combination,...
This work proposes an efficient texture classification strategy performed in the wavelet domain in order to characterize healthy and pathological speech signals from recurrence plots (RP). The two-dimensional wavelet transform is applied to the recurrence plots at one resolution level. Thirteen Haralick texture features are obtained from each approximation and detail subband coefficients. In classification,...
This paper proposes a Bayesian learning approach to structured sparse image reconstruction. In contrast to conventional paradigms which convert images into high-dimensional vectors and thus are impractical for recovering large-scale images, we formulate columns of image matrices into a multiple-measurement-vector (MMV) model to reduce the problem dimension. Besides, we simultaneously exploit the tree...
A new coding method to exploit intra-subband and inter-subband correlation of the medical images in the transform domain is presented. Subbands corresponding to each direction are combined together and treated as a set of hierarchical trees. If a set of hierarchical trees becomes significant, it is divided into four sets and each set is processed separately. The image is encoded progressively and...
The aim of this paper is to introduce fast and reliable baud duration estimators. This work is concerned with the symbols transitions sequence extraction and the baud duration estimation. The symbols transitions sequence is extracted using one of three methods — the level-crossing method, the derivative method and the wavelet method. Subsequently, the baud duration is estimated by applying the greatest...
Breast cancer has been threatening lives of women around the world. Thus, Computer Aided Diagnosis (CAD) systems play an important role in early detection of breast cancer. In this study, we propose a CAD system based on cyclostationary signal analysis for microcalcifications detection. Spectral correlation is estimated for regions of interests (ROIs) after conversion to 1D vector. The proposed algorithm...
In order to trade-off between computational effects and computational cost of present image encryption algorithm, a novel image encryption algorithm based on lifting-based wavelet transform is proposed in this paper. The image encryption process includes three steps: first the original image was divided into blocks, which were transformed by lifting based wavelet, secondly the wavelet domain coefficients...
Equipped with large scale antenna arrays, massive multiple input multiple output systems are qualified with several benefits including enhanced throughput, power efficiency, and anti-interference ability, etc. The acquisition of such advantages requires adequate channel state information at transmitter. In frequency division duplex multiple input multiple output systems, channel state information...
The Wavelet Transform is not optimal for image compression. The coefficients on the same level of decomposition preserve a residual correlation which may harm the efficiency of the encoding algorithm. In the case of entropic codes, this effect can be reduced by using an appropriate coefficients scanning and long enough contexts for the conditional probabilities. Such an approach needs the knowledge...
This work introduces an alternative video coding approach that exploits the temporal correlation present in video signals by applying a combined wavelet/DCT three-dimensional transform to the input video sequence. As the correlation along the temporal axis is likely lowered when motion is present we first partitioning the input sequence into partitions or groups of similar pictures and then applying...
Modeling of visual attention is a very active research domain which has attracted the attention of researchers over the past years. Several models of saliency detection are now available that have shown successful applications in various fields. In this paper, we initially present three models already existing in the literature, we are talking about Itti's model, Imamoglu's model and Le Moans's model...
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