基于ADS1298与FPGA的高性能脑电信号采集系统

高性能的便携式脑电信号的采集设备对临床医学和认知科学研究领域具有重要意义,设计了基于ADS1298和FPGA的高性能脑电信号采集系统。给出了脑电信号采集系统的总体设计,重点阐述了ADS1298的特点和工作原理,在此基础上讨论了系统的外围电路以及FPGA接口电路设计,最后给出内部信号处理控制模块设计。设计的脑电信号采集系统具有低功耗、高精度和小型化的特点,具有很好的应用前景。     

基于脑功能网络和样本熵的脑电信号特征提取

针对脑-机接口(BCI)研究中采用单一特征对运动想象脑电信号(EEG)识别率不高的问题,该文提出一种结合脑功能网络和样本熵的特征提取方法。根据事件相关同步/去同步(ERS/ERD)现象以及皮层与肢体运动想象间的对侧映射机制,选取小波包变换消噪重构后的\begin{document}$ \mu$\end{document}节律脑电信号,用左侧27个通道、右侧27个通道分别对左半球脑区和右半球脑区构建脑功能网络,计算网络的平均节点度和平均聚集系数作为运动想象的脑功能网络特征,并结合C3, C4通道节律的样本熵构筑分布性和指向性相结合的特征向量。选用支持向量机(SVM)对左右手运动想象脑电信号进行分类,结果表明基于脑功能网络和样本熵的特征提取方法能够实现更优的分类效果,分类准确率最高可达90.27%。     

基于脑功能网络和样本熵的脑电信号特征提取

针对脑-机接口(BCI)研究中采用单一特征对运动想象脑电信号(EEG)识别率不高的问题,该文提出一种结合脑功能网络和样本熵的特征提取方法.根据事件相关同步/去同步(ERS/ERD)现象以及皮层与肢体运动想象间的对侧映射机制,选取小波包变换消噪重构后的μ节律脑电信号,用左侧27个通道、右侧27个通道分别对左半球脑区和右半球脑区构建脑功能网络,计算网络的平均节点度和平均聚集系数作为运动想象的脑功能网络特征,并结合C3,C4通道μ节律的样本熵构筑分布性和指向性相结合的特征向量.选用支持向量机(SVM)对左右手运动想象脑电信号进行分类,结果表明基于脑功能网络和样本熵的特征提取方法能够实现更优的分类效果,分类准确率最高可达90.27％.     

脑电信号反馈控制装置的设计

本文研究设计了专用于治疗神经系统脑部疾病的智能化离电信号反馈控制装置。在分析人体脑电信号的基础上，将脑电生物反馈与电磁反馈有机结合，能有效地调节脑神经细胞的电活动。临床研究表明，该装置对神经系统一些脑部疾病有显著疗效。     

脑机接口技术研究综述

脑机接口技术(brain computer interface,BCI)不依赖于常规大脑信息输出通路,该技术建立了一种直接的信息交流和控制通道,为人脑和外界之间提供了一种全新的交互方式。简要介绍了BCI技术的定义和基本组成及发展现状,并对皮层慢电位、视觉诱发电位、眼动产生的α波、P300电位和基于运动想象的μ节律及β波5种脑机接口技术的研究方向作了简要阐述,最后指出目前BCI研究面临的挑战及未来的应用前景。     

脑机接口技术研究概述

脑机接口(Brain-Computer Interface, BCI)是在人脑和外界之间建立不依赖于常规大脑信息输出通路(外周神经和肌肉组织)的一种通讯系统.本文概述了基于脑电信号(EEG)的BCI技术的基本原理、研究方法、类型、研究现状,并分析了目前存在的问题与应用前景.     

LMD算法与运动想象脑电信号的时频分析

脑电信号是极其复杂的非平稳信号,为了精确处理运动想象脑电信号,采用LMD(局域均值分解)方法对其进行时频分析。首先给出仿真信号的LMD分解及时频分布,而后对左右手运动想象脑电信号进行LMD时频分析。研究结果表明,LMD具有较强的时频刻画能力,能够精确描述脑电信号的非线性时变特性,是对脑电信号进行时频分析的有效方法。     

基于TGAM模块的脑电信息沟通系统设计与实现

本文设计与实现了一种基于TGAM模块的脑电信息沟通系统。该系统采用美国神念科技的TGAM芯片,基于SSVEP-BCI脑电范式,完成了从脑电信号采集,到脑电信号处理分析,以及脑电信号运用的一整套脑波控制的标准化流程,实现了将脑波意念转化为他人可直观解读的个人需求信息或意愿信息的目的。     

基于相位延迟指数的脑功能网络及测谎研究

在脑认知科学领域,越来越多的研究开始专注于利用不同导联脑电信号之间的相互依赖关系来研究大脑整体认知功能.相位延迟指数可有效减少由容积导体引起的误差,该方法已被广泛应用.而基于图论的脑网络研究方法在测谎方面还少见报道.本文通过对30名（诚实和说谎）受试者的脑电信号进行网络拓扑分析,将网络参数作为判别指标,使用支持向量机对实验数据进行分类.研究发现,两组受试者的小世界指标表现出显著的统计学差异,且得到较高的测谎准确率,结果证明了利用相位延迟指数方法进行图论分析的测谎有效性.     

脑电信号识别方法的研究

人类对大脑的探索已进入了数字化时代,随着脑信号检测技术的日益成熟以及人工智能算法的研究进展,脑信号的解读研究也展现出越来越多的成果.本文首先介绍当下大脑信号获取的医学方法,而后简述脑电信号的特征提取以及分类识别方法,接着列举脑电识别的前沿研究,最后对脑电信号识别的数据应用领域进行展望.     

Modeling and analysis of anti-worm in P2P networks

Anti-worm is an effective way to fight against malicious worm and has been followed closely by malicious worm researchers recently.However,active and passive confronting technologies in peer-to-peer (P...     

Modeling and performance analysis of multihop packet radio networks

The design of packet radio networks involves a large number of issues which interact in a very complex fashion. Many of these pertain to the RF channel and its use, others pertain to the operational protocols. Clearly, no single model can be formulated which incorporates all the necessary parameters and leads to the optimum solution. The one essential element which complicates matters is that, contrary to point-to-point networks in which each channel is utilized by a single pair of nodes, the radio channel in packet radio networks is a multiaccess broadcast resource: i) in a given locality determined by radio connectivity, the channel is shared by many contending users, hence the need for channel access protocols; ii) radio is a broadcast medium and thus the action taken by a node has an effect on the actions taken by neighboring nodes and their outcome. Despite the complexity of the problem, there has been significant progress worth reporting on. The work accomplished so far has been either the analysis of specific examples of networks or an attempt to create models that would be useful in the design of general networks. The purpose of this paper is to survey the various modeling techniques that have been used for the performance analysis of packet radio networks, and to discuss the assumptions underlying these models, their scope of applicability, and some of the results obtained.     

Modeling and analysis of power distribution networks for Gigabit applications

As the operating frequency of digital systems increases and voltage swing decreases, it becomes very important to characterize and analyze power distribution networks (PDNs) accurately. This paper presents the modeling, simulation, and characterization of the PDN in a high-speed printed circuit board (PCB) designed for chip-to-chip communication at a data rate of 3.2 Gbps. The test board consists of transmitter and receiver chips wirebonded onto plastic ball grid array (PGBA) packages on a PCB. In this paper, a hybrid method has been applied for analysis, which consists of the transmission matrix method (TMM) in the frequency domain and macromodeling method in the time domain. As an initial step, power/ground planes have been modeled using TMM. Then, the macromodel of the power/ground planes has been generated at the desired ports using macromodeling. Finally, the macromodel of the planes, transmission lines, and nonlinear drivers have been simulated in standard SPICE-based circuit simulators for computing power supply noise. In addition to noise computation, the self and transfer impedances of power/ground planes have been computed and the effect of decoupling capacitors on power supply noise has been analyzed. The methods discussed have been validated using hardware measurements.     

采用部分频率复用的小小区网络建模与分析

小小区组网技术被认为是解决迅速增长的移动数据量需求的方法。然而,密集的小小区组网会导致严重的小区间干扰。传统的部分频率复用方法不能完全照搬用在部署不规则的小小区网络内,急需一种合理高效建模采用频率复用小小区网络的方法,对其性能进行评估。利用随机几何理论对小小区网络考虑部分频率复用场景进行建模,推导了考虑部分频率复用的小小区网络下行覆盖概率和网络吞吐量的表达式。数值仿真结果显示：部分频率复用技术可以提高小小区网络下行覆盖概率,但是会降低网络图吞吐量。在满足覆盖概率约束条件下,得到了使得网络吞吐量最大的频率复用因子的表达式。以上结果对未来采用频率复用技术的小小区组网的具体实施具有重要的指导意义。     

Asymptotic performance analysis of amplify-and-forward cooperative networks in a nakagami-m fading environment

This letter analyzes the performance of repetitionbased cooperative wireless networks using amplify-and forward relaying. The network consists of a source, R parallel relays, and a destination, and the channel coefficients are distributed as independent, non-identical, Nakagami-m. The approximated average symbol error rate (SER) is investigated. For sufficiently large SNR, this letter derives a close-form average SER when m is an integer. The simplicity of the asymptotic results provides valuable insights into the performance of cooperative networks and suggests means of optimizing them. We also use simulation to verify the analytical results. Results show that the derived error rates are tight approximations particularly at medium and high SNR.     

Modeling and analysis of multi-type failures in wireless body area networks with semi-Markov model

Network reliability is very important in wireless body area network since the vital human life might be jeopardized, unless managed properly. In this article, a new modeling and analysis of node behaviors in wireless body area networks is presented for increasing reliability in the presence of multi-type failures, while saving energy. First, the nodes are classified into types with regard to their capabilities on relaying and sensing. Then, the node behaviors in the presence of failures such as energy exhaustion and/or malicious attacks have been modeled using a novel semi-Markov process. Finally, simulation has been done to evaluate the performance.     

FAST TCP over optical burst switched networks: Modeling and stability analysis

FAST TCP is important for promoting data-intensive applications since it can cleverly react to both packet loss and delay for detecting network congestion. This paper provides a continuous time model and extensive stability analysis of FAST TCP congestion-control mechanism in bufferless Optical Burst Switched Networks (OBS). The paper first shows that random burst contentions are essential to stabilize the network, but cause throughput degradation in FAST TCP flows when a burst with all the packets from a single round is dropped. Second, it shows that FAST TCP is vulnerable to burst delay and fails to detect network congestion due to the little variation of round-trip time, thus unstable. Finally it shows that introducing extra delays by implementing burst retransmission stabilizes FAST TCP over OBS. The paper proves that FAST TCP is not stable over barebone OBS. However, it is locally, exponentially, and asymptotically stable over OBS with burst retransmission.     

Modeling and sensitivity analysis of circuit parameters for flip-chip interconnects using neural networks

This paper presents a neural network-based technique for modeling and analyzing the electrical performance of flip-chip transitions. A lumped element model using a simple pi equivalent circuit is used to characterize the electrical properties of the flip-chip bond. Statistical experimental design is used to extract the electrical parameters for flip-chip characterization from measurements and full-wave simulations up to 35 GHz. The extracted data is used to train back-propagation neural networks to obtain an accurate model of the pi equivalent circuit components and s-parameters as a function of layout parameters. The prediction error of the models is less than 5%. The models are used to obtain response surfaces for the entire range of variation of layout parameters. The neural network models are subsequently used to perform sensitivity analysis. All electrical parameters are shown to be sensitive to conductor overlap. The inductance and capacitance of the pi equivalent circuit are sensitive to the bump height. However, the return loss (S₁₁) is insensitive to the change in bump height. The coplanar waveguide width has a significant impact on the s-parameters, as it affects the matching of flip-chip transitions