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.
In this paper, we propose a method to improve localization algorithm of maximum likelihood estimation;the localization scheme relies on the distance threshold. In order to suppress effectively the effects of received ...
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ISBN:
(纸本)9781509038237;9781509038220
In this paper, we propose a method to improve localization algorithm of maximum likelihood estimation;the localization scheme relies on the distance threshold. In order to suppress effectively the effects of received signal strength error to node localization precision. This paper presents an indoor localization algorithm based on received signal strength to select anchor nodes. Compared with the traditional localization algorithm, this scenario not only improve the localization accuracy, but also reduce the calculation complexity of nodes. The simulation results show that the average error of the proposed method is less than 0.15 m. Moreover, when there are a large number of anchor nodes, the computational complexity is effectively reduced. Verification result verifies the effectiveness and reliability of the algorithm.
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.
The traditional double-threshold endpoint detection method has the phenomenon of missing detection. Therefore, the speech recognition(SR) system based on vector quantization(VQ) in this paper proposes an improved algo...
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ISBN:
(纸本)9781509038237;9781509038220
The traditional double-threshold endpoint detection method has the phenomenon of missing detection. Therefore, the speech recognition(SR) system based on vector quantization(VQ) in this paper proposes an improved algorithm for this phenomenon, which effectively avoids the problem of missing detection. Then, Mel Frequency Cepstral Coefficients(MFCC) is used to extract the characteristic parameters of the speech signal, and the multistage vector quantization is used to quantify the characteristic parameters. Experimental results show that, the proposed algorithm improves the recognition rate of the text-independent speaker recognition system by 8.7%, and it also confirms that the longer the training speech is, the higher the recognition rate will be.
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.
Target detection by a noncooperative illuminator is a topic of general interest in the electronic warfare field. First of all, direct-path interference （DPI） suppression which is the technique of bottleneck of movin...
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Target detection by a noncooperative illuminator is a topic of general interest in the electronic warfare field. First of all, direct-path interference （DPI） suppression which is the technique of bottleneck of moving target detection by a noncooperative frequency modulation（FM） broadcast transmitter is analyzed in this article; Secondly, a space-time-frequency domain synthetic solution to this problem is introduced： Adaptive nulling array processing is considered in the space domain, DPI cancellation based on adaptive fractional delay interpolation （AFDI） technique is used in planned time domain, and long-time coherent integration is utilized in the frequency domain; Finaily, an experimental system is planned by considering FM broadcast transmitter as a noncooperative illuminator, Simulation results by real collected data show that the proposed method has a better performance of moving target detection.
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.
Fourier ptychographic microscopy (FPM) combines the concepts of phase retrieval algorithms and synthetic apertures and can solve the problem in which it is difficult to combine a large field of view with high resoluti...
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Fourier ptychographic microscopy (FPM) combines the concepts of phase retrieval algorithms and synthetic apertures and can solve the problem in which it is difficult to combine a large field of view with high resolution. However, the use of the coherent transfer function in conventional calculations to describe the linear transfer proc-ess of an imaging system can lead to ringing artifacts. In addition, the Gerchberg-Saxton iterative algorithm can cause the phase retrieval part of the FPM algorithm to fall into a local optimum. In this paper, Gaussian apodization coherent transfer function is proposed to describe the imaging process and is combined with an iterative method based on amplitude weighting and phase gradient descent to reduce the presence of ringing artifacts while ensuring the accuracy of the reconstructed results. In simulated experiments, the proposed algorithm is shown to give a smaller mean square error and higher structural similarity, both in the presence and absence of noise. Finally, the proposed algorithm is validated in terms of giving reconstruction results with high accuracy and high resolution, using images acquired with a new microscope system and open-source images. (c) 2023 Optica Publishing Group
Abstractive summarization has made significant progress in recent years, which aims to generate a concise and coherent summary that contains the most important facts from the source document. Current fine-tuning appro...
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Abstractive summarization has made significant progress in recent years, which aims to generate a concise and coherent summary that contains the most important facts from the source document. Current fine-tuning approaches based on pre-training models typically rely on autoregressive and maximum likelihood estimation, which may result in inconsistent historical distributions generated during the training and inference stages, i.e., exposure bias problem. To alleviate this problem, we propose a hybrid fine-tuning model(HyFit), which combines contrastive learning and reinforcement learning in a diverse sampling space. Firstly, we introduce reparameterization and probability-based sampling methods to generate a set of summary candidates called candidates bank, which improves the diversity and quality of the decoding sampling space and incorporates the potential for uncertainty. Secondly, hybrid fine-tuning with sampled candidates bank, upweighting confident summaries and downweighting unconfident ones. Experiments demonstrate that HyFit significantly outperforms the state-of-the-art models on SAMSum and DialogSum. HyFit also shows good performance on low-resource summarization, on DialogSum dataset, using only approximate 8% of the examples exceed the performance of the base model trained on all examples. IEEE
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