The importance of the analysis and understanding of the network traffic has constantly been increasing due to insights that this provides towards determination of user behaviour and resource usage. The data analyses i...
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The importance of the analysis and understanding of the network traffic has constantly been increasing due to insights that this provides towards determination of user behaviour and resource usage. The data analyses in order to determine the related parameters are performed by selection of a small subset of the complete flow data due to data privacy and heavy computational/memory load issues. That is, sampling is required in order to detect the properties of the complete data set. In this work, four distinct sampling schemes, namely the packet based uniform sampling, time-slot based uniform sampling, packet based random sampling and time-slot based random sampling are investigated from which packet flow length distributions are estimated and compared with the actual data. No major differences are observed amongst the strategies based on the analysed data.
The high azimuth angular resolution problem of real-beam scanning radar is significant to targets detection and location. ML iterative adaptive approach(ML-IAA) has been used in array signalprocessing to realize high...
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ISBN:
(纸本)9781479920365
The high azimuth angular resolution problem of real-beam scanning radar is significant to targets detection and location. ML iterative adaptive approach(ML-IAA) has been used in array signalprocessing to realize high angular resolution. In order to improve the azimuth angular resolution of real-beam scanning radar, we introduce this algorithm to real-beam radar system, called real-beam ML iterative superresolution approach(RML-ISA). This method established the likelihood function by utilizing the statistical property of real beam data. Applying this method to the real-beam radar system only needs few scanning echo to obtain effective results. Simulations illustrate the performance of our algorithm.
Current spam detection algorithms have poor generalization ability as given small samples and less priority knowledge. This paper proposed a spam filtering detection protocol based on Kernel principal-component analys...
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Current spam detection algorithms have poor generalization ability as given small samples and less priority knowledge. This paper proposed a spam filtering detection protocol based on Kernel principal-component analysis (KPCA) and C-Support Vector Machines (C-SVM) which can solve and implement the mentioned problem. Compared with the traditional algorithms this method can achieve higher detection rate and improve detection efficiency, and be easily generalized in practice. At last the experiment on data set shows the effectiveness and excellent performance of this method.
The reverberation time or RT60 is an essential acoustic parameter of a room. In many situations, the room impulse response (RIR) is not available and the RT60 must be blindly estimated from a speech or music signal. C...
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ISBN:
(纸本)9781479928941
The reverberation time or RT60 is an essential acoustic parameter of a room. In many situations, the room impulse response (RIR) is not available and the RT60 must be blindly estimated from a speech or music signal. Current methods often implicitly assume that reverberation dominates direct sound, which restricts their applicability to relatively small rooms or distant sound sources. This paper features two contributions. Firstly, we propose a blind RT60 estimation method that is independent of the room size and the source distance by preprocessing the input signal using a beamformer to cancel direct sound and early echoes. Secondly, we perform the largest experimental evaluation to our knowledge using a set of 342 RIRs. We show that the estimation error is significantly reduced even in the case when reverberation dominates.
With the dramatic increase of mobile data traffic in the foreseeable future, small cells are set to play an important role in expanding the target capacity of wireless networks. At the same time, to balance the load a...
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With the dramatic increase of mobile data traffic in the foreseeable future, small cells are set to play an important role in expanding the target capacity of wireless networks. At the same time, to balance the load among all the small cell base stations (SBSs) becomes more and more important. We consider this problem in a user-centric way, where users are able to make decision to choose their SBSs for service. We use congestion penalty and switch penalty to help users make the decision. We give sufficient conditions to guarantee the convergence of the load in each cell. It is proved that the choice of each user will converge to an equilibrium point as well. To analyze the load in a single small cell, we introduce the concept of equivalent cell. Moreover, a second order differential equation is formulated to describe the load fluctuation of a single small cell. Convergence rate is analyzed and it can be controlled by the proposed two penalties. Finally, simulation results validate the proposed scheme.
A Multiple-Input-Multiple-Output (MIMO) radar with colocated transmit and receive antennas has a larger virtual aperture compared to the corresponding Single-Input-Single-Output (SIMO) radar. Therefore, it can achieve...
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ISBN:
(纸本)9781479920365
A Multiple-Input-Multiple-Output (MIMO) radar with colocated transmit and receive antennas has a larger virtual aperture compared to the corresponding Single-Input-Single-Output (SIMO) radar. Therefore, it can achieve a more accurate Direction of Arrival (DOA) estimation. Due to the Doppler effect, a target moving relative to the radar system results in an additional phase shift of the baseband signal. In general, this leads to a decrease in the DOA estimation accuracy. We consider time division multiplexed (TDM) MIMO radars and derive the Cramer-Rao Bound (CRB) for the DOA and Doppler frequency estimation of two moving targets. This is done for general TDM schemes. This enables to compare the achievable accuracy for different TDM MIMO radars. We derive conditions for TDM schemes which lead to a decoupling of the Doppler frequencies and DOAs in the CRB. Hence a CRB of DOAs can be achieved which is as small as if the Doppler frequencies are known a priori. We define a statistical resolution limit to separate both targets with the help of the CRB and compare the resolution of a TDM MIMO radar to that of a SIMO radar.
Video and Image processing applications are notably time consuming, especially for large number of small image files and huge video files. Cloud computing gives a new processing method for such requirement, but almost...
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Video and Image processing applications are notably time consuming, especially for large number of small image files and huge video files. Cloud computing gives a new processing method for such requirement, but almost all of the cloud computing platforms are based on super computers. In this paper, we propose a new method for one big image file's and large number of small image files' processing based on MapReduce and give a new idea of constructing the cloud computing platform based on heterogeneous embedded multi-core processors. From the experiment results, it can be seen that the proposed method is feasible and after analysis, we find the problems of embedded cloud computing platform based on Hadoop with MapReduce, and conclude the future research direction.
In this paper, we propose a reversible data hiding method based on pixel difference histogram shifting and ripple strategy. Because the local area has similar pixel value distribution in the natural image, the pixel d...
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In this paper, we propose a reversible data hiding method based on pixel difference histogram shifting and ripple strategy. Because the local area has similar pixel value distribution in the natural image, the pixel differences will be narrowed down within a small range. The ripple strategy is used to calculate the pixel difference using the pixels in the outer ripple to subtract the pixels in the inner ripples. Also, we found that the three highest pixel difference bins occure most frequently at -1, 0, and 1, thus the proposed method need not remember the peak-point and zero-point information for secret extraction and image recovering. The experimental results show that the proposed method has better performance than Huang and Chang's method in terms of the embedding capacity.
In this study, a method that aims at detecting small and faint objects in noisy hyperspectral astrophysical images is presented. The particularity of the hyperspectral images that we are interested in is the high dyna...
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ISBN:
(纸本)9781479928941
In this study, a method that aims at detecting small and faint objects in noisy hyperspectral astrophysical images is presented. The particularity of the hyperspectral images that we are interested in is the high dynamics between object intensities. Detection of the smallest and faintest objects is challenging, because their signal-to-noise ratio is low, and if the brightest objects are not well reconstructed, their residuals can be more energetic than faint objects. This paper proposes a marked point process within a nonparametric Bayesian framework for the detection of galaxies in hyperspectral data. The efficiency of the method is demonstrated on synthetic images, and it provides good results for very faint objects in quasi-real astrophysical hyperspectral data.
The existing spectrum sensing schemes based on free probability theory (FPT) have a high sensing performance especially in cases of low signal to noise ratio (SNR) and a small number of samples. However they all based...
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ISBN:
(纸本)9781479973408
The existing spectrum sensing schemes based on free probability theory (FPT) have a high sensing performance especially in cases of low signal to noise ratio (SNR) and a small number of samples. However they all based on data fusion rule when performing cooperative spectrum sensing. The secondary users (SUs), in this case, have to transmit large amounts of sensing data to a fusion center (FC). It may cause the FC overloaded, which is considered as an extreme challenge to the practical application. In this paper, a new cooperative FPT-based spectrum sensing scheme is proposed, which utilizes the OR decision fusion rule to overcome the aforementioned shortcomings of such an algorithm. Simulation results over MIMO rayleigh fading channel demonstrate that, with decision fusion, the performance of our proposed scheme is much higher than that of the eigenvalue-based detector, even though the latter uses data fusion rule. Therefore, the proposed scheme is more effective and practical on the overall performance.
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