基于希尔伯特黄变换的癫痫自动检测

希尔伯特黄变换是由经验模态分解和希尔伯特变换所组成的,在非线性、非稳态信号处理方面具有独特的优势。本文首先对脑电波信号进行模态分解,然后根据希尔伯特变换求得各本征模态函数的瞬时频率并依此计算出均值、方差及其核心频率区间等特征,并选取若干个本征模态函数的频率特征组成一个长的特征向量,称之为希尔伯特黄频率特征环。根据该特征向量,本文进一步采用支持向量机对癫痫和非癫痫脑电波信号进行学习和分类,并采用格点搜索的方法来选取支持向量机中的最优参数。通过在典型癫痫脑电波数据集上的5重交叉验证得出本文所提出的新方法在分类准确率上已经超越或接近现有的分类方法。      

关于希尔伯特变换的分析和研究

首先从数学定义上直观地分析希尔伯特变换,接着讨论了离散希尔伯特变换的基本原理,并研究如何利用有限冲激响应滤波器(FIR)设计方案来实现该变换。最后,举例说明希尔伯特变换在数字I—Q下变频器中的应用,以便学生更好地掌握这一概念。     

实现离散Hilbert变换所需阶数的分析

连续信号与离散信号的Hilbert变换之间存在偏差,不利于学生理解。本文从理论上分析了信号的最高频率、采样频率、想要达到的信噪比与离散Hilbert变换项数之间的关系,给出了离散Hilbert变换的特性及适用于实验的项数确定依据。数值仿真表明了相关结论的正确性。     

Cognitive IoT-Cloud Integration for Smart Healthcare: Case Study for Epileptic Seizure Detection and Monitoring

We propose a cognitive Internet of Things (IoT)–cloud-based smart healthcare framework, which communicates with smart devices, sensors, and other stakeholders in the healthcare environment; makes an intelligent decision based on a patient’s state; and provides timely, low-cost, and accessible healthcare services. As a case study, an EEG seizure detection method using deep learning is also proposed to access the feasibility of the cognitive IoT–cloud smart healthcare framework. In the proposed method, we use smart EEG sensors (apart from general healthcare smart sensors) to record and transmit EEG signals from epileptic patients. Thereafter, the cognitive framework makes a real-time decision on future activities and whether to send the data to the deep learning module. The proposed system uses the patient’s movements, gestures, and facial expressions to determine the patient’s state. Signal processing and seizure detection take place in the cloud, while signals are classified as seizure or non-seizure with a probability score. The results are transmitted to medical practitioners or other stakeholders who can monitor the patients and, in critical cases, make the appropriate decisions to help the patient. Experimental results show that the proposed model achieves an accuracy and sensitivity of 99.2 and 93.5%, respectively.     

Statistical Analysis of UWB Channel Correlation Functions

Various performance metrics of impulse-radio (IR) ultrawideband (UWB) receivers are closely connected to the correlation functions of the multipath channel responses to UWB pulses. Interpulse interference is related to the autocorrelation function (ACF) of the received pulse (RP), the RP energy and its fading correspond to the ACF at zero lag, and multiple access interference is connected to the cross-correlation function (CCF) between two channel pulse responses. Each realization of the multipath channel shows different correlation functions due to the ldquorandomnessrdquo of the UWB propagation environment. This paper derives the first- and second-order statistics of the ACF and CCF, capturing this randomness. Such results are useful for incorporating the multipath channel into the performance and design optimization studies of UWB systems. The analysis is based on a model of the received UWB pulse. The model describes the random channel response by two continuous functions of the excess delay time-one expresses the power, the other expresses power variations-and by a prototype pulse shape representing all linear system components including the band limitation of the RP and antenna effects. The analytical results are validated through the analysis of simulated and measured channel responses.     

一种基于希尔伯特变换的相位差测量方法

文章研究了一种基于希尔伯特变换的相位差测量方法,利用希尔伯特变换对信号有90度的相移这一特性,再通过简单的数学运算,得出只关于相位角的时间函数,能够检测出两路正弦信号的相位差,分别讨论了信号的A／D最化位数,信噪比,采样频率对测量结果的影响,同时也给出了该方法对随时间变化的相位差的测量结果,结果证明了该方法能够很好的实现相位差的动态测量。     

运用希尔伯特黄变换进行多分量信号的频散分析

基于谱分析原理将希尔伯特黄变换应用于多分量信号的频散分析,通过希尔伯特时频能量谱获得每个单分量信号的能量分布和群速度,通过希尔伯特时频相位谱获得每个单分量信号的相速度.在相速度的计算过程中提出异步相差和校正相差的算法,可以有效避免相位解缠.仿真结果表明,上述方案可以获得较为准确的频散分析结果.     

Channel Error Recovery for Transform Image Coding

A method is presented to automatically inspect the block boundaries of a reconstructed two-dimensional transform coded image, to locate blocks which are most likely to contain errors, to approximate the size and type of error in the block, and to eliminate this estimated error from the picture. This method uses redundancy in the source data to provide channel error correction. No additional channel error protection bits or changes to the transmitter are required. It can be used when channel errors are unexpected prior to reception.     

基于Hilbert变换的BFSK非相干解调

频移键控（FSK）具有易实现、鲁棒性强等优点,在数字通信系统中得到广泛应用。文中对数字正交相乘解调原理进行了简要介绍,针对所设计系统难以准确得到相移π/2的延时信号,采用Hilbert变换实现整个频带内的信号精确的π/2相移。并给出了误码率数值曲线,仿真结果表明：该算法具有较强的鲁棒性,便于用DSP芯片实现等特点,优于传统的非相干BFSK解调器。该算法应用到DSP系统实时解调32路BFSK信号,运行效果良好。     

基于希尔伯特变换的多用户DCSK通信系统性能分析

针对差分混沌移位键控(DCSK)传输速率低的问题,该文提出一种基于希尔伯特变换的多用户DCSK(HMU-DCSK)通信系统。在固定阶数的Walsh码条件下,通过希尔伯特变换将正交基信号集合提高1倍,并确保分配给每个用户的载波信号正交。推导了在Rayleigh衰落信道下的误码率公式并进行仿真。结果表明,相同N值下HMU-DCSK系统的传输速率是传统多用户DCSK系统的2倍;相同传输速率下HMU-DCSK系统的误码性能明显优于传统多用户DCSK系统。     

分数阶希尔伯特变换的复包络分析

分数Hilbert变换,也即传统的Hilbert变换由整数阶向分数阶的推广,由此其应用领域也得到了扩展,譬如在通信中的单边带调制解调系统,图像的边缘提取等领域中得到广泛的应用。首先,文中回顾了利用经典希尔伯特变换的正交性把经典的Hilbert变换的定义形式进行广义化后得到的分数阶Hilbert变换,并讨论了由分数阶Hilbert变换构造的两类复信号,最后讨论了这两类复信号的包络提取并且给出了具体的实例。     

Statistical Analysis of a Mobile-to-Mobile Rician Fading Channel Model

Mobile-to-mobile communication is an important application for intelligent transport systems and mobile ad hoc networks. In these systems, both the transmitter and receiver are in motion, subjecting the signals to Rician fading and different scattering effects. In this paper, we present a double-ring with a line-of-sight (LOS) component scattering model and a sum-of-sinusoids simulation method to characterize the mobile-to-mobile Rician fading channel. The developed model can facilitate the physical-layer simulation for mobile ad hoc communication systems. We also derive the autocorrelation function, level crossing rate (LCR), and average fade duration (AFD) of the mobile-to-mobile Rician fading channel and verify the accuracy by simulations.     

基于过时信道状态信息的放大转发中继选择协议性能分析(英文)

The impact of outdated Channel State Information(CSI) on the performance of relay selections,including the partial relay selection and the best relay selection,is studied,with respect to Amplify-and-Forward(AF) mode cooperative systems.The proposed method is analysed by deriving the asymptotic closedform expressions for some figures of merit such as the outage probability and the Symbol Error Probability(SEP).Moreover,the validity of the proposed theoretical analysis is proven via simulations.Numerical results prove that the performance of the proposed scheme is impacted considerably by various parameters such as the number of candidate relays and the end-to-end Signal-to-Noise Ratio(SNR).In the presence of cooperative networks with outdated CSI feedback,a performance improvement of more than 3 dB in terms of either outage probability or SEP can be observed by utilizing the Source-to-Destination(S D) link rather than the method of simply increasing the number of relays.     

基于傅里叶变换的雷达通道均衡算法性能分析及改进

本文研究了基于傅里叶变换的雷达通道均衡算法的性能,对工程应用中影响算法性能的因素进行了详细分析,这些因素包括信噪比、信号带宽与采样率的关系及群延迟等,给出了针对上述因素的解决方案.其中针对群延迟的影响,根据循环卷积的原理,提出了一种实现非因果均衡器的方法.以上分析都是在实验数据的基础上进行的.分析结果表明,避免几种因素的影响后,改进算法可以获得较好的均衡性能.     

A Statistical Prediction Interval for Availability

A statistical prediction interval and predictor are presented for the availability of a repairable unit during future failure and repair cycles where there are data from previous cycles. These results are based on the assumption that times to failure and times to repair are all statistically independent and exponentially distributed.     

过采样技术和Hilbert变换在数字AM广播中的应用

根据DRM（数字无线电组织）标准,介绍了过采样技术和Hilbert变换的原理,研究了两者在数字AM（调幅）广播中的应用。通过MATLAB仿真,比较了两种方法在AWGN（加性高斯白噪声）信道和Rice衰落信道下的性能。通过比较得到：在AWGN信道和Rice衰落信道下,过采样方法和Hilbert变换法性能完全一样,只是Hilbert变换法要增加一个变换的计算过程,对采样率无特殊要求,FFT（快速傅里叶变换）的点数可以任取,只要满足采样定理即可。     

基于希尔伯特边际谱和极限学习机的癫痫脑电信号分类

提出了一种基于希尔伯特边际谱和极限学习机相结合的癫痫脑电信号分类方法.首先将脑电信号进行经验模态分解,对前5个本征模态函数进行希尔伯特变换,得到其希尔伯特边际谱;然后将希尔伯特边际谱的Shannon熵、Renyi熵和Tsallis熵,以及5个不同频段节律信号的能量作为有效特征输入极限学习机进行分类.实验结果表明,本文方...     

Empirical Statistical Model for LTE Downlink Channel Occupancy

This paper develops an empirical statistical channel occupancy model for downlink long-term evolution (LTE) cellular systems. The model is based on statistical distributions mixtures for the holding times of the channels. Moreover, statistical distribution of the time when the channels are free is also considered. The data is obtained through an extensive measurement campaign performed in Stockholm, Sweden. Two types of mixtures are considered, namely, exponential and log-normal distributions to fit the measurement findings. The log-likelihood of both mixtures is used as a quantitative measure of the goodness of fit. Moreover, finding the optimal number of linearly combined distributions using the Akaike information criterion is investigated. The results show that good fitting can be obtained by using either exponential or log-normal distributions mixture. Even though, the fitting is done for a representative case with a tempo-spatial consideration, the model is yet applicable in general for LTE and other cellular systems in a wider sense.

     

线性正交分集变换（LDRT）在莱斯衰落信道中的性能分析

线性正交分集变换（ＬＤＲＴ）是近来提出的一种有效的抗衰落技术,本文对线性分集变换在莱斯衰落信道中的性能进行了分析研究,当信号调制选用ＱＰＳＫ时,计算机仿真结果：在误码率为１０＾－４条件下,信道参数Ｋ等于０ｄＢ时,ＬＤＲＴ处理增中达２１ｄＢ;随着Ｋ的增大,相应的处理增益减小,当Ｋ＝１０ｄＢ时,经过ＬＤＲＴ后的性能对高斯信道的性能只相关１ｄＢ,另外对分集矩阵的阶数Ｌ对系统误比特性能的影响进行了分析讨论