一种基于CPK数字签名的阈下信道

阈下信道是一种信息隐藏技术,能够在数字签名的过程中传输秘密信息,这为认证、防伪等方面的应用提供了一种实现平台。在CPK数字签名的基础上提出一种阈下信道,加大CPK体制的应用。     

基于存储区域网络的数据备份技术研究

从数据备份系统结构的角度,研究了传统数据备份技术的优缺点,针对现有备份技术的存在的问题,通过在存储区域网络中引入网络数据管理协议,使得存储区域网络环境下的数据备份极大减轻了网络负载量,同时业务服务器最大限度地从数据备份过程中解脱出来,从而提高了整个备份系统的性能;同时对基于存储区域网络数据备份技术研究的特点、存在的问题、研究热点和应用情况等进行了分析。     

体导电信道分析与研究

为了降低植入器件的功耗和有效控制植入器件,提高通信效率,提出了一种基于体导电的低功耗数字通信模型。当体导电流的工作频率在kHz级,生物背景信号干扰是微不足道的,体导电信道可近似为加性高斯白噪声信道。从香农信息论出发,推导出二维凋制下的信道容量公式,从而得到推论：在极低信噪比时采用两电平调制就能相当有效地利用信道容量,在高信噪比时,为了充分利用信道容量必须采用多电平调制。利用SystemView对信道进行仿真,证明体导电数字通信的可行性,并得出采取调制方式的必要性,以及误码率和信噪比的关系。     

基于OPNET的EPON自适应双时序算法研究与仿真

EPON上行业务的QoS保证是实际应用中的关键问题。通过提出一种新颖的双时序自适应动态算法,既保证EF高优先级业务,又支持突发大的BE数据业务,有效控制轻负载恶化现象,能最大极限的提高EPON网络效率。采用OPNET仿真模型验证了算法的可行性和改进性能。     

A constant-time dynamic storage allocator for real-time systems

Dynamic memory allocation has been used for decades. However, it has seldom been used in real-time systems since the worst case of spatial and temporal requirements for allocation and deallocation operations is either unbounded or bounded but with a very large bound. In this paper, a new allocator called TLSF (Two Level Segregated Fit) is presented. TLSF is designed and implemented to accommodate real-time constraints. The proposed allocator exhibits time-bounded behaviour, O(1), and maintains a very good execution time. This paper describes in detail the data structures and functions provided by TLSF. We also compare TLSF with a representative set of allocators regarding their temporal cost and fragmentation. Although the paper is mainly focused on timing analysis, a brief study and comparative analysis of fragmentation incurred by the allocators has been also included in order to provide a global view of the behaviour of the allocators. The temporal and spatial results showed that TLSF is also a fast allocator and produces a fragmentation close to that caused by the best existing allocators.

无人机OFDM数据链路中信道估计算法研究

针对无人机信道的特点,以及采用正交频分复用技术进行无人机数据链路传输的优点.在对OFDM关键技术信道估计进行研究时,要确保接收端能够准确的检测出由于无线信道变化造成的码间干扰,准确的解调出原信号.根据系统需要设计了梳状导频和块状导频联合的导频插入方式,该方式可以在数据传输和信道估计性能上做到折中,并对常用的信道估计算法进行分析研究提出了改进的最小均方误差信道估计算法,最后建立频率选择性信道模型对不同的信道估计算法进行仿真,分析仿真结果可以看出该导频插入方式和信道估计算法具有较低的复杂度,而且又具有良好的信道估计性能,适合在实际系统中应用.     

一种基于零空间的再分配伪逆算法

由于伪逆法不考虑执行器的位置和速率的限制,因此利用伪逆法设计出的分配器会产生操纵面过早进入饱和的现象,从而使分配器对转矩可达集的分配效率较低.在伪逆法的分配基础上利用控制效率矩阵零空间的特性对分配结果进行二次调节,使伪逆解重新落入执行器的控制子空间,从而避免了分配器过早进入饱和的现象.并提高了分配效率.利用某飞机的数据进行仿真验证,结果显示与伪逆法相比,控制性能有明显改善,提高了分配器的分配效率,且可以对转矩可达集内的转矩实施有效的分配.     

Global attention retinex network for low light image enhancement

Most low-light image enhancement methods only adjust the brightness, contrast and noise reduction of low-light images, making it difficult to recover the lost information in darker areas of the image, and even cause color distortion and blurring. To solve the above problems, a global attention-based Retinex network (GARN) for low-light image enhancement is proposed in this paper. We propose a novel global attention module which computes multiple dimensional information in the channel attention module to help facilitate inference learning. Then the global attention module is embedded into different layers of the network to extract richer shallow texture features and deep semantic features. This means that the rich features are more conducive to learning the mapping relationship between low-light images to normal-light images, so that the detail recovery of dark regions is enhanced in low-light images. We also collected a low/normal light image dataset with multiple scenes, in which the images paired as training set can succeed to be applied to low-light image enhancement under different lighting conditions. Experimental results on publicly available datasets show that our method has better effectiveness and generality than the state-of-the-art methods in terms of evaluations metrics such as PSNR, SSIM, NIQE, Entropy.     

CCNet: CNN model with channel attention and convolutional pooling mechanism for spatial image steganalysis

Image steganalysis based on convolutional neural networks(CNN) has attracted great attention. However, existing networks lack attention to regional features with complex texture, which makes the ability of discrimination learning miss in network. In this paper, we described a new CNN designed to focus on useful features and improve detection accuracy for spatial-domain steganalysis. The proposed model consists of three modules: noise extraction module, noise analysis module and classification module. A channel attention mechanism is used in the noise extraction module and analysis module, which is realized by embedding the SE(Squeeze-and-Excitation) module into the residual block. Then, we use convolutional pooling instead of average pooling to aggregate features. The experimental results show that detection accuracy of the proposed model is significantly better than those of the existing models such as SRNet, Zhu-Net and GBRAS-Net. Compared with these models, our model has better generalization ability, which is critical for practical application.     

Using honeynodes for defense against jamming attacks in wireless infrastructure-based networks

The advent of wireless networks has brought a new set of security issues with it. One of the most feared of these is the jamming-based attacks. In this paper, we propose a pre-emptive detection strategy using honeynodes and a response mechanism based on the existing Channel Surfing Algorithm [Xu W, Trappe W, Zhang Y, Wood T. Channel surfing and spatial retreats: defenses against wireless denial of service. ACM Wireless Security 2004;80-9] to protect wireless nodes from a jammer. Honeynodes generate dummy communication at a frequency close to the actual frequency of operation, and pre-emptively alert authentic nodes of imminent attacks, so that the authentic nodes can jump to another frequency even before a jammer starts scanning that frequency. The next frequency is selected using a novel approach which uses a hybrid of reactive and proactive channel selection procedures. We have simulated the proposed approach using NS-2. The experimental results further prove a marked improvement in the performance of the proposed system over the Channel Surfing Algorithm in terms of the packet delivery ratio, the jammed duration, control message overhead and the number of channel re-configurations.