共查询到20条相似文献，搜索用时 31 毫秒
1.
To retrieve the information from the serious distorted received signal is the key challenge of communication signal processing. The chaotic baseband communication promises theoretically to eliminate the inter-symbol interference (ISI), however, it needs complicated calculation, if it is not impossible. In this paper, a genetic algorithm support vector machine (GA-SVM) based symbol detection method is proposed for chaotic baseband wireless communication system (CBWCS), by this way, treating the problem from a different viewpoint, the symbol decoding process is converted to be a binary classification through GA-SVM model. A trained GA-SVM model is used to decode the symbols directly at the receiver, so as to improve the bit error rate (BER) performance of the CBWCS and simplify the symbol detection process by removing the channel identification and the threshold calculation process as compared to that using the calculated threshold to decode symbol in the traditional methods. The simulation results show that the proposed method has better BER performance in both the static and time-varying wireless channels. The experimental results, based on the wireless open-access research platform, indicate that the BER of the proposed GA-SVM based symbol detection approach is superior to the other counterparts under a practical wireless multipath channel. 相似文献
2.
混沌序列具有类随机性、对初始条件极度敏感性、遍历性和非周期性等特点,展现出优良的密码学性能。该加密算法通过Logistic映射产生混沌序列,并将混沌序列映射为64位二进制序列,结合DNA序列变迁重组算法和DES算法对64位明文分组进行加密,DES初始密钥处于动态变化中,能有效地抵御穷举攻击和选择密文攻击等多种攻击手段。 相似文献
3.
Hui Liu Xiaohua Li Xiaoping Liu Huanqing Wang 《Journal of The Franklin Institute》2019,356(15):8049-8079
In this paper, a novel decentralized adaptive neural control approach based on the backstepping technique is proposed to design a decentralized H∞ adaptive neural controller for a class of stochastic large-scale nonlinear systems with external disturbances and unknown nonlinear functions. RBF neural networks are utilized to approximate the packaged unknown nonlinearities. A novel concept with regard to bounded-H∞ performance is proposed. It can be applied to solve an H∞ control problem for a class of stochastic nonlinear systems. The constant terms appeared in stability analysis are dealt with by using Gronwall inequality, so that H∞ performance criterion is satisfied. The assumption that the approximation errors of neural networks must be square-integrable in some literature can be eliminated. The design process for decentralized bounded-H∞ controllers is given. The proposed control scheme guarantees that all the signals in the resulting closed-loop large-scale system are uniformly ultimately bounded in probability, and each subsystem possesses disturbance attenuation performance for external disturbances. Finally, the simulation results are provided to illustrate the effectiveness and feasibility of the proposed approach. 相似文献
4.
《Information processing & management》2022,59(3):102927
Due to the harmful impact of fabricated information on social media, many rumor verification techniques have been introduced in recent years. Advanced techniques like multi-task learning (MTL), shared-private models suffer from many strategic limitations that restrict their capability of veracity identification on social media. These models are often reliant on multiple tasks for the primary targeted objective. Even the most recent deep neural network (DNN) models like VRoC, Hierarchical-PSV, StA-HiTPLAN etc. based on VAE, GCN, Transformer respectively with improved modification are able to perform good on veracity identification task but with the help of additional auxiliary information, mostly. However, their rise is still not substantial with respect to the proposed model even though the proposed model is not using any additional information. To come up with an improved DNN model architecture, we introduce globally Discrete Attention Representations from Transformers (gDART). Discrete-Attention mechanism in gDART is capable of capturing multifarious correlations veiled among the sequence of words which existing DNN models including Transformer often overlook. Our proposed framework uses a Branch-CoRR Attention Network to extract highly informative features in branches, and employs Feature Fusion Network Component to identify deep embedded features and use them to make enhanced identification of veracity of an unverified claim. Moreover, to achieve its goal, gDART is not dependent on any costly auxiliary resource but on an unsupervised learning process. Extensive experiments reveal that gDART marks a considerable performance gain in veracity identification task over state-of-the-art models on two real world rumor datasets. gDART reports a gain of 36.76%, 40.85% on standard benchmark metrics. 相似文献
5.
WASMOD模型参数敏感性与相关性分析 总被引：1，自引：1，他引：0
对水文模型参数进行敏感性和相关性分析,可以减少率定参数的数量、提高模型运行效率,并可以为优化和改进模型结构提供依据.本文采用局部分析法和相关系数法讨论了WASMOD模型中的五个参数对目标函数的敏感程度以及参数之间的相关程度.研究发现,在黑河流域上游山区的径流模拟过程中,WASMOD模型中影响降水形态的温度参数a1对目标函数最为敏感;其次是影响地表径流的参数a6和影响融雪过程的温度参数a2;基流参数a5最不敏感.模型参数之间的相关性不是很强,这也说明,模型结构已得到很好的优化;为保证模型的模拟效果,模型参数的数量不能减少. 相似文献
6.
提出了小波自反馈混沌神经网络,分析了小波自反馈对混沌神经网络动力学行为的影响;将该暂态混沌网络模型应用于求解10城市旅行商问题(TSP),分析了小波自反馈对模拟退火的影响,得出了小波的自反馈是模拟退火的有效补充的结论;利用小波自反馈的伸缩平移优化了网络求解TSP的性能;最后研究了网络求解旅行商问题的内部状态的暂态混沌搜索、最大Lyapunov指数、混沌区域以及相空间的散度。实验仿真表明,小波自反馈的暂态混沌神经网络能够实现全局优化并具有较快的收敛速度。 相似文献
7.
《Information processing & management》2022,59(4):102983
Abnormal event detection in videos plays an essential role for public security. However, most weakly supervised learning methods ignore the relationship between the complicated spatial correlations and the dynamical trends of temporal pattern in video data. In this paper, we provide a new perspective, i.e., spatial similarity and temporal consistency are adopted to construct Spatio-Temporal Graph-based CNNs (STGCNs). For the feature extraction, we use Inflated 3D (I3D) convolutional networks to extract features which can better capture appearance and motion dynamics in videos. For the spatio graph and temporal graph, each video segment is regarded as a vertex in the graph, and attention mechanism is introduced to allocate attention for each segment. For the spatial-temporal fusion graph, we propose a self-adapting weighting to fuse them. Finally, we build ranking loss and classification loss to improve the robustness of STGCNs. We evaluate the performance of STGCNs on UCF-Crime datasets (total 128 h) and ShanghaiTech datasets (total 317,398 frames) with the AUC score 84.2% and 92.3%, respectively. The experimental results also show the effectiveness and robustness with other evaluation metrics. 相似文献
8.
分布式水循环模型的参数优化算法比较及应用 总被引：1，自引：0，他引：1
分布式水文模型的优势在于还原水文过程的时空变异性,可以很好地模拟和反映各种水文要素和下垫面因素的时空分布不均匀性。由此也导致模型参数过多,在子流域过多的情况下,人工调节参数繁琐复杂,应用优化算法实现参数自动调节成为首选。本文选取石羊河流域九条岭站1988-2005年实测径流资料,分别应用SCE-UA算法、遗传算法(GA)和粒子群算法(PSO)对分布式水循环模型(时变增益模型)进行参数率定,对比3种算法的收敛速度、所需迭代次数和算法稳定性。结果表明:通过SCE-UA、GA和PSO的优化,模型水平衡系数都控制在0.0左右,而相关系数和效率系数分别能达到0.90和0.84以上,模拟精度较好。但粒子群算法的全局搜索能力和收敛速度优于SCE-UA和遗传算法,所需迭代次数最少,初值敏感性小,更适合时变增益模型的参数寻优,有很高的扩展性和改进潜力。 相似文献
9.
逐日太阳辐射是作物模型的关键输入变量,被广泛用于计算太阳辐射的Ångström-Prescott模型（A-P公式）校正工作主要建立在月尺度数据上,开展不同区域日尺度及更大时间尺度校正及参数适用性研究有助于提高太阳辐射计算和作物模型模拟准确性,指导区域农业生产。本文基于中国九大农业区划和104个辐射站点的1981—2016年逐日太阳辐射实测资料,分析了中国年太阳辐射时空分布特征;在此基础上,分别在日尺度和月尺度校正A-P公式,并对其校正参数（as和bs）的适用性进行检验评价。结果表明：①中国年太阳辐射在1990年前后经历了由“变暗”到“变亮”的转变,总体呈增加趋势（7.32±30.31 MJ/m2/a）,空间上呈西高东低的分布特征;②日尺度A-P公式校正拟合效果优于月尺度,且月尺度的校正参数存在明显的空间异质性;参数as的空间分布存在地带性,呈东南低西北高的特征,而bs与海拔正相关;③日尺度和月尺度校正参数可互换,但在年尺度上线性A-P公式不再适用。本文对提高太阳辐射计算精度和指导区域农业生产具有一定的参考价值。 相似文献
10.
《Journal of The Franklin Institute》2021,358(13):6897-6921
This paper presents a novel switching predefined-time parameter identification algorithm with a relaxed excitation condition based on the dynamic regressor extension and mixing (DREM) method. DREM often requires the persistent excitation (PE) of the extended square regressor's determinant to ensure exponential parameter convergence. Unlike the classical DREM method, a new parameter identification algorithm configured with a two-layer filter technique is proposed under a relaxed initial excitation (IE) condition, rather than strict PE. A key point in choosing IE instead of PE is the introduction of a smooth switching function that dominates the pure integral action and filter behavior of the extended square regressor. The proposed algorithm relies on the predefined-time stability theorem and the settling-time of the identification algorithm is set a priori as a system parameter. The contributions of this paper are a novel switching predefined-time parameter estimation algorithm that 1) relaxes the stringent PE condition, 2) achieves predefined-time convergence, and 3) guarantees the monotonicity of each element of the parameter error inherited from the classical DREM method. Comparative simulation results are presented to illustrate the effectiveness of the proposed algorithm. 相似文献
11.
《Information processing & management》2022,59(5):103033
When cybercriminals communicate with their customers in underground markets, they tend to use secure and customizable instant messaging (IM) software, i.e. Telegram. It is a popular IM software with over 700 million monthly active users (MAU) up to June 2022. In recent years, more and more dark jargons (i.e. an innocent-looking replacement of sensitive terms) appear frequently on Telegram. Therefore, jargons identification is one of the most significant research perspectives to track online underground markets and cybercrimes. This paper proposes a novel Chinese Jargons Identification Framework (CJI-Framework) to identify dark jargons. Firstly, we collect chat history from Telegram groups that are related to the underground market and construct the corpus TUMCC (Telegram Underground Market Chinese Corpus), which is the first Chinese corpus in jargons identification research field. Secondly, we extract seven brand-new features which can be classified into three categories: Vectors-based Features (VF), Lexical analysis-based Features (LF), and Dictionary analysis-based Features (DF), to identify Chinese dark jargons from commonly-used words. Based on these features, we then run a statistical outlier detection to decide whether a word is a jargon. Furthermore, we employ a word vector projection method and a transfer learning method to improve the effect of the framework. Experimental results show that CJI-Framework achieves a remarkable performance with an F1-score of 89.66%. After adaptation for English, it performs better than state-of-the-art English jargons identification method as well. Our built corpus and code have been publicly released to facilitate the reproduction and extension of our work. 相似文献
12.
通过对ｌ１模指标的平滑处理，构造了平滑近似指标下的递推辨识算法，这种算法实时计算负担小，且具有良好算法性质，数值仿真结果表明，它仍蕴含原指标意义下的鲁棒估计性质。 相似文献
13.
14.
15.
《Information processing & management》2020,57(3):102205
Recently, a massive amount of position-annotated data is being generated in a stream fashion. Also, massive amounts of static data including spatial features are collected and made available. In the Internet of Things (IoT) environments, various applications can get benefits by utilizing spatial data streams and static data. Therefore, IoT applications typically require stream processing and reasoning capabilities that extract information from low-level data. Particularly for sophisticated stream processing and reasoning, spatiotemporal relationship (SR) generation from spatial data streams and static data must be preceded. However, existing techniques mostly focus solely on direct processing of sensing data or generation of spatial relationships from static data. In this paper, we first address the importance of SRs between spatial data streams and static data and then propose an efficient approach of deriving SRs in real-time. We design a novel R-tree-based index with Representative Rectangles (RRs) called R3 index and devise an algorithm that leverages relationships and distances between RRs to generate SRs. To verify the effectiveness and efficiency of the proposed approach, we performed experiments using real-world datasets. Through the results of the experiments, we confirmed the superiority of the proposed approach. 相似文献
16.
In order to fully explore and utilize the advantages of droplet-based microfluidics, fast, sensitive, and quantitative measurements are indispensable for the diagnosis of biochemical reactions in microdroplets. Here, we report an optical detection technique using two-photon fluorescence lifetime imaging microscopy, with an aligning-summing and non-fitting division method, to depict two-dimensional (2D) maps of mixing dynamics by chaotic advection in microdroplets with high temporal and spatial resolution. The mixing patterns of two dye solutions inside droplets were quantitatively and accurately measured. The mixing efficiency in a serpentine droplet mixer was also quantified and compared with the simulation data. The mapped chaotic mixing dynamics agree well with the numerical simulation and theoretical prediction. This quantitative characterization is potentially applicable to the real-time kinetic study of biological and chemical reactions in droplet-based microfluidic systems. 相似文献
17.
This paper is concerned with master-slave synchronization for chaotic Lur'e systems subject to aperiodic sampled-data. To reduce the communication burden, an aperiodic event-triggered (APET) transmission scheme is introduced to determine the transmission of the latest sampling synchronization data. In order to reduce the design conservatism, a novel time-dependent Lyapunov functional (TDLF) is constructed to fully use the characteristics about sampling behavior, triggering error, and nonlinear part of the system, simultaneously. A more relaxed constraint criterion is then presented to ensure the positivity of the whole functional between two sampling instants. By partially resorting to the TDLF, the APET-based synchronization criterion depending on the upper and lower bounds of the uncertain sampling period is presented. The synchronization criterion based on aperiodic-sampling mechanism is also provided. Finally, a typical example about neural networks is offered to illustrate the benefit and validity of obtained synchronization methodologies. 相似文献
18.
《Journal of The Franklin Institute》2018,355(18):9224-9244
In this paper a new approach to algebraic parameter identification of the linear SISO systems is proposed. The standard approach to the algebraic parameter identification is based on the algebraic derivatives in Laplace domain as the main tool for algebraic manipulations like elimination of the initial conditions and generation of linearly independent equations. This approach leads to the unstable time-varying state-space realization of the filters for the on-line parameter estimation. In this paper, the finite difference and shift operators in combination with the frequency-shifting property of Laplace transform is applied instead of algebraic derivatives. Resulting state-space realization of the estimator filters is asymptotically stable and doesn’t require switch-of mechanism to prevent overflow of the estimator variables. The proposed method is especially suitable for applications in closed-loop on-line identification where the stable behavior of the estimators is a necessary requirement. The efficiency of the proposed algorithm is illustrated on three simulation examples. 相似文献
19.
《Journal of The Franklin Institute》2018,355(18):9072-9084
The computational complexity of the numerical simulation of fractional chaotic system and its synchronization control is O(N2) compared with O(N) for integer chaotic system, where N is step number and O is the computational complexity. In this paper, we propose optimizing methods to solve fractional chaotic systems, including equal-weight memory principle, improved equal-weight memory principle, chaotic combination and fractional chaotic precomputing operator. Numerical examples show that the combination of these algorithms can simulate fractional chaotic system and synchronize the fractional master and slave systems accurately. The presented algorithms for simulation and synchronization of fractional chaotic system are up to 1.82 and 1.75 times faster than the original implementation respectively. 相似文献
20.
Components within micro-scale engineering systems are often at the limits of commercial miniaturization and this can cause unexpected behavior and variation in performance. As such, modelling and analysis of system robustness plays an important role in product development. Here, schematic bond graphs are used as a front end in a sensitivity analysis based strategy for modelling robustness in multi-physics micro-scale engineering systems. As an example, the analysis is applied to a behind-the-ear (BTE) hearing aid.By using bond graphs to model power flow through components within different physical domains of the hearing aid, a set of differential equations to describe the system dynamics is collated. Based on these equations, sensitivity analysis calculations are used to approximately model the nature and the sources of output uncertainty during system operation. These calculations represent a robustness evaluation of the current hearing aid design and offer a means of identifying potential for improved designs of multiphysics systems by way of key parameter identification. 相似文献