Regarding the performance of traditional endpoint detection algorithms degrades as the environment noise level increases, a recursive calculating algorithm for higher-order cu- mulants over a sliding window is propose...
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Regarding the performance of traditional endpoint detection algorithms degrades as the environment noise level increases, a recursive calculating algorithm for higher-order cu- mulants over a sliding window is proposed. Then it is applied to the speech endpoint detection. Furthermore, endpoint detection is carried out with the feature of energy. Experimental results show that both the computational efficiency and the robustness against noise of the proposed algorithm are improved remarkably compared with traditional algorithm. The average prob- ability of correct point detection (Pc-point) of the proposed voice activity detection (VAD) is 6.07% higher than that of G.729b VAD in different noisy at different signal-noise ratios (SNRs) environments.
The multilevel characteristic basis function method(MLCBFM)with the adaptive cross approximation(ACA)algorithm for accelerated solution of electrically large scattering problems is studied in this *** the conventional...
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The multilevel characteristic basis function method(MLCBFM)with the adaptive cross approximation(ACA)algorithm for accelerated solution of electrically large scattering problems is studied in this *** the conventional MLCBFM based on Foldy-Lax multiple scattering equations,the improvement is only made in the generation of characteristic basis functions(CBFs).However,it does not provide a change in impedance matrix filling and reducing matrix calculation procedure,which is *** reality,all the impedance and reduced matrix of each level of the MLCBFM have low-rank property and can be calculated ***,ACA is used for the efficient generation of two-level CBFs and the fast calculation of reduced matrix in this *** results are given to demonstrate the accuracy and efficiency of the method.
In this paper,we consider a wireless ad hoc network consisting of multiple source nodes transmitting to their respective destinations,where an eavesdropper attempts to intercept their *** propose an optimal transmissi...
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In this paper,we consider a wireless ad hoc network consisting of multiple source nodes transmitting to their respective destinations,where an eavesdropper attempts to intercept their *** propose an optimal transmission scheduling scheme to defend against the eavesdropper,where a source node having the highest secrecy rate is scheduled to access the wireless medium for transmitting to its destination in an opportunistic *** be specific,the secrecy rate between a pair of the source and destination in the presence of an eavesdropper varies temporally due to the wireless fading *** proposed optimal transmission scheduling scheme opportunistically selects a source node with the highest secrecy rate to transmit its data for the sake of maximizing the security of the ad hoc network against eavesdropping *** comparison purposes,we also consider the conventional round-robin scheduling as a benchmark,where multiple source nodes take turns in accessing their shared wireless medium for transmitting to their respective *** derive closed-form secrecy outage probability expressions of both the round-robin scheduling and the proposed optimal scheduling schemes over Rayleigh fading *** results show that the proposed transmission scheduling scheme outperforms the conventional round-robin method in terms of its secrecy outage ***,upon increasing the number of source-destination pairs,the secrecy outage probability of the round-robin scheme keeps unchanged,whereas the secrecy outage performance of the proposed transmission scheduling significantly improves,showing the security benefits of exploiting transmission scheduling for protecting wireless ad hoc networks against eavesdropping.
MicroRNAs(miRNAs)are closely related to numerous complex human diseases,therefore,exploring miRNA-disease associations(MDAs)can help people gain a better understanding of complex disease *** increasing number of compu...
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MicroRNAs(miRNAs)are closely related to numerous complex human diseases,therefore,exploring miRNA-disease associations(MDAs)can help people gain a better understanding of complex disease *** increasing number of computational methods have been developed to predict ***,the sparsity of the MDAs may hinder the performance of many *** addition,many methods fail to capture the nonlinear relationships of miRNA-disease network and inadequately leverage the features of network and neighbor *** this study,we propose a deep matrix factorization model with variational autoencoder(DMFVAE)to predict potential *** first decomposes the original association matrix and the enhanced association matrix,in which the enhanced association matrix is enhanced by self-adjusting the nearest neighbor method,to obtain sparse vectors and dense vectors,***,the variational encoder is employed to obtain the nonlinear latent vectors of miRNA and disease for the sparse vectors,and meanwhile,node2vec is used to obtain the network structure embedding vectors of miRNA and disease for the dense ***,sample features are acquired by combining the latent vectors and network structure embedding vectors,and the final prediction is implemented by convolutional neural network with channel *** evaluate the performance of DMFVAE,we conduct five-fold cross validation on the HMDD v2.0 and HMDD v3.2 datasets and the results show that DMFVAE performs ***,case studies on lung neoplasms,colon neoplasms,and esophageal neoplasms confirm the ability of DMFVAE in identifying potential miRNAs for human diseases.
A whisper intelligibility enhancement method was proposed based on the Real-valued Discrete Gabor Transform (RDGT) in the joint time frequency domain where the RDGT can change the density of the spectrum through the o...
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Target detection by non-cooperative illuminator is a study hotspot in electronic warfare field, with'four countering' potential advantages for passive radar. One of the major problems in continuous wave bistat...
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Target detection by non-cooperative illuminator is a study hotspot in electronic warfare field, with'four countering' potential advantages for passive radar. One of the major problems in continuous wave bistatic radar is Direct path interference (DPI). Conventional solutions to this problem is the use of an adaptive antenna, steering null towards the interference. Unfortunately the null depth obtained by this technology is not enough for surveillance radar. First of all, DPI appeared in passive radar based on non-cooperative FM broadcast transmitter is analyzed in this paper. Secondly, a DPI cancellation based on Adaptive fractional delay estimation (AFDE) is in detail introduced how to deal with this problem. Finally, a passive radar experimental system based on non-cooperative FM broadcast transmitter is provided, simulation results by real collected data show applying the method proposed in this paper is effective in suppression DPI.
At present, in related image processing field, the fuzzy set theory has also gained more successful applications to some extent. The image processing based on the fuzzy theory is an important research area. The inform...
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At present, in related image processing field, the fuzzy set theory has also gained more successful applications to some extent. The image processing based on the fuzzy theory is an important research area. The information loss brought by 3D object projection in 2D image plane makes the image have the ambiguity exist in essence, thus there exists ambiguity when defining image characteristics such as the border, area and texture, therefore, because of the complexity of the image itself, uncertainty and inaccuracy or ambiguity may occur in the different stages of the processing. The algorithm in this paper improves the degree of membership function to make it suitable for the image fuzzy enhancement. The membership function curve is S-shaped, and at the inflection point, the function value on the left side drops rapidly while the function value on the right side rapidly rises. There is certain symmetry about the inflection point, and the function inflection point position can be decided by changing function parameters, and better enhancement effect can be gained by a small amount of iteration. By the experimental simulation, it is verified that the enhanced color image by adopting the method in this paper is bright in color on the visual effect with moderate increasing proportion of brightness and contrast, and best color maintaining performance and minimum chromaticity change, and also the image information entropy is improved when compared with the original image data.
This paper presents a novel image fusion method based on nonsubsampled shearlet transform (NSST) and block-based random image sampling for infrared and visible images. In the method, the NSST is firstly performed on e...
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This paper presents a novel image fusion method based on nonsubsampled shearlet transform (NSST) and block-based random image sampling for infrared and visible images. In the method, the NSST is firstly performed on each of the source images to obtain their low frequency and high frequency subbands coefficients. Then the low frequency coefficients are fused by combing the block-based random image sampling and the sliding widow technique, while the high frequency coefficients are fused using classical absolute value maximum choosing rule. The fused image is reconstructed though performing the inverse NSST. The experiments are carried out on five pairs of infrared and visible images using five traditional fusion methods to verify the effectiveness and efficiency of the proposed method and by comparing the fused results visually and objectively it is demonstrated that the proposed fusion method is competitive or even superior to the other wellknown methods.
This study presents an efficient multi-resolution method to detect binary object directly. Both intensity and geometry differences are used to measure the similarity between the source object template and target objec...
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Image enhancement, as a means of digital image processing, often is fuzzy. Based on defects of excessive enhancement and insufficient detail enhancement existing in the traditional image enhancement method, this paper...
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Image enhancement, as a means of digital image processing, often is fuzzy. Based on defects of excessive enhancement and insufficient detail enhancement existing in the traditional image enhancement method, this paper proposes a self-adaptive image enhancement method based on variable fuzzy sets, and such method can, according to the image's gray-scale properties, introduce the relative gray-scale level of the pixel as the fuzzy feature, and adopt the improved membership function to conduct the fuzzy enhancement, thus avoiding the loss of a great deal of gray-scale information after the enhancement. The paper also introduces the selection of optimal parameters, ensures the quality of the image enhanced and improves the feasibility and efficiency of this algorithm. This algorithm, on the basis of keeping the image's original brightness, enhances the image details at the same time. Experimental results show that such algorithm can obtain good visual effect and more obvious detail information.
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