一种适用于无线多媒体传感器网络的节点不相交多路径路由协议

设计了一种适用于无线多媒体传感器网络的高效节点不相交多路径路由协议.以源路由的方式建立多路径,中间节点通过有选择的转发RREQs,降低路由建立开销.将链路质量量化为数据接收率,利用数据接收率、节点能量及路径跳数等,定义了路径效率模型,将路径效率模型引入到路由建立过程中.仿真结果表明,与SMR及TinyONDMR协议相比,新协议建立路由的开销更低,所建路径上节点能量分布更理想,进行数据传输时的能量效率更高,同时不会显著增加路径的传输时延.     

波形信道的建模与仿真

通信系统总体性能受到失真,噪声和通信信道产生的干扰的显著影响。这严重影响了通信效果。为了评估通信系统的性能,设计和优化发射机的信号处理操作,我们需要对通信信道进行建模和仿真。该文重点介绍了波形信道的建模与仿真中的多径衰落信道的仿真,波形级信道根据噪声,干扰,和其他扰动与被传输信号的结合,在接收机输入端产生一个失真和带噪声的波形信号来定义信道的。     

一种基于能量感知无线传感器网络多路径路由机制

目前,无线传感器网络在智能环境检测,灾难控制,战场侦察,安全监视方面取得了日益广泛的应用,引起人们日益关注,在分析无线传感器网络能量消耗特征的基础上,基于Markov模型提出了无线传感器网络节点能量消耗模型,改进了无线传感器网络多路径路由协议。仿真结果表明,与传统的多路径路由机制相比,能够有效地降低无线传感器网络节点能量消耗,提高网络生存时间。     

一种基于（部分）广播通道的秘密共享方案

在传统的秘密共享方案中,秘密分发者通过秘密通道分发秘密份额给一组参与者.结合Rei方案和Amos方案,提出仅需一个秘密通道的秘密共享方案.在该方案的秘密分发阶段,秘密分发者与参与者之间使用部分广播通道进行通信,秘密分发者与秘密合并者之间使用一个秘密通道进行通信;在秘密重构阶段,参与者与秘密合并者之间使用广播通道进行通信.通过对该方案进行分析可知,该方案的通道数和总的通信量比已知的两个方案具有明显的优势.     

基于带有随机时滞的多通信通道的网络控制系统镇定

基于带有随机时滞的多通信通道,建立了离散时间网络控制系统模型．利用缓存对丢包进行补偿,并设计了状态反馈控制器,使系统达到随机稳定．采用锥型补偿线性化（ＣＣＬ）算法得到了控制器增益的全局最优解．最后通过倒立摆系统的仿真例子验证了所提出方法的可行性．     

基于group-based模型的无线传感器网络密钥管理方案

由于无线传感器网络受电源、计算能力、内存容量等方面的限制,传统的基于公钥和可信任的密钥管理方式不再适用.为了进一步提高无线传感器网络的安全连通性,在分析DU Wen-liang等人的group-based节点投放模型的基础上,提出了一种改进的密钥管理方案:多密钥空间与多路径增强相结合的随机密钥预分配方案.结果分析表明,该方案需要较少的内存存储空间,不仅提高了系统的连通性,还降低了节点的被捕获概率.     

部分信道交叠多跳无线网络容量渐近估计

无线多跳网络的基本问题是信道交叠情形下系统容量上限的估计以及最大容量的获取.建立有实效参数的容量渐近估计模型,不仅可以准确、深入描述部分交叠信道的竞争性与互助性对系统容量的影响,而且可以为系统容量优化提供重要理论参考依据.该模型揭示,无论是单播还是广播业务,网络容量峰值的达到是可用中继节点数与发送概率的匹配,更具体地说是归一化节点密度与节点数的乘积同节点发送概率的匹配.     

The research on channel estimation and signal-noise ratio estimation based on minimum error entropy kalman filter for single carrier frequency domain equalization system

In this paper, the channel estimation and signal-to-noise ratio (SNR) estimation technique of single-carrier frequency domain equalization (SC-FDE) system under low SNR in aeronautical multipath channel are studied, a SNR estimation algorithm which is easy to implement in engineering and an improved LS channel estimation algorithm based on Kalman filter using minimum error entropy (MEE-KF) are proposed. This paper first introduces the SC-FDE system and introduces the principle of MEE-KF, and then, the channel estimation flow based on MEE-KF is obtained by combining it with the traditional LS channel estimation algorithm, which makes the estimation results perform better. Simulation results show that after getting more accurate noise variance, the channel estimation results can better follow the changes of the channel after MEE-KF processing, so as to resist the doppler frequency offset effect and make the channel estimation results more accurate, that is the channel response results of the data part can be closer to the real situation, so that the communication performance of SC-FDE system has also been greatly improved.     

An Artificial Autonomic Nervous System That Implements Heart and Pupil as Controlled by Artificial Sympathetic and Parasympathetic Nerves

The autonomic nervous system maintains homeostasis in organisms through complex neural pathways and responds adaptively to changes in the external and internal environment. The fabrication of an artificial autonomic nervous system is reported that replicates combined effects of sympathetic and parasympathetic nerves on cardiac activity and pupillary control, to mimic the regulation of autonomic nervous system to external changes. The artificial autonomic nerve-controlled pupil contraction and relaxation, modulating the rate of heartbeats for normal cardiac rhythm and arrhythmia as reflected by blink rates of a signal indicator. These functions are switched by using a parallel-channeled synaptic transistor with a special n-i-p heterostructure that has a 2D h-BN insulator in the middle to provide barrier against ion injection into the 2D MoS₂ bottom n-channel and enable short-term plasticity as induced by acetylcholine, and the electrochemical doping reaction occurred at the P3HT nanowire p-channels on top to enable relatively long-term plasticity as induced by noradrenaline. Low-energy consumption down to femtojoule and an ultrahigh paired-pulse facilitation index up to ≈455% are demonstrated. An artificial neural network based on device characteristics achieves a high recognition accuracy for electrocardiogram patterns. This study extends insights into artificial nerves-inspired biological signal processing and recognition.