Real-time removal of ocular artifacts from EEG based on independent component analysis and manifold learning

Frequent occurrence of ocular artifacts leads to serious problems in interpreting and analyzing the electroencephalogram (EEG). In the present paper, a novel and robust technique is proposed to eliminate ocular artifacts from EEG signals in real time. Independent Component Analysis (ICA) is used to decompose EEG signals. The features of topography and power spectral density of those components are extracted. Moreover, we introduce manifold learning algorithm, a recently popular dimensionality reduction technique, to reduce the dimensionality of initial features, and then those new features are fed to a classifier to identify ocular artifacts components. A k-nearest neighbor classifier is adopted to classify components because classification results show that manifold learning with the nearest neighbor algorithm works best. Finally, the artifact removal method proposed here is evaluated by the comparisons of EEG data before and after artifact removal. The results indicate that the method proposed could remove ocular artifacts effectively from EEG signals with little distortion of the underlying brain signals and be satisfied the real-time application.     

A gradient-based adaptive error diffusion method with edge enhancement

This paper presents a gradient-based adaptive error diffusion method with edge enhancement effect while preserving the smoothness effect. The proposed method not only can modulate the threshold in halftoning dynamically but also can determine the weights of the error diffusion filter adaptively to diffuse the quantization error to neighboring pixels properly. Under six testing images, experimental results demonstrate that our proposed new error diffusion method has a good compromise between the edge enhancement effect in the halftone image and the image quality effect in the corresponding inverse halftone image when compared to the methods by Floyd–Steinberg, Eschbach and Knox, Hwang et al., Li, and Feng et al., but it has some execution-time degradation.     

Neural network-based sliding mode adaptive control for robot manipulators

This paper addresses the robust trajectory tracking problem for a robot manipulator in the presence of uncertainties and disturbances. First, a neural network-based sliding mode adaptive control (NNSMAC), which is a combination of sliding mode technique, neural network (NN) approximation and adaptive technique, is designed to ensure trajectory tracking by the robot manipulator. It is shown using the Lyapunov theory that the tracking error asymptotically converge to zero. However, the assumption on the availability of the robot manipulator dynamics is not always practical. So, an NN-based adaptive observer is designed to estimate the velocities of the links. Next, based on the observer, a neural network-based sliding mode adaptive output feedback control (NNSMAOFC) is designed. Then it is shown by the Lyapunov theory that the trajectory tracking errors, the observer estimation errors asymptotically converge to zero. The effectiveness of the designed NNSMAC, the NN-based adaptive observer and the NNSMAOFC is illustrated by simulations.     

随机非线性动态系统数值模拟与性态分析

针对具有随机参数非线性系统和随机非线性系统的数值模拟与性态分析问题,提出将蒙特卡罗模拟办法与数值积分法相结合,建立了迭代积分算法求取随机非线性系统在不副随机序列作用下的数值解集,分析了计算误差．其次,利用数值解集的样本值进行解过程性态分析,建立了系统状态的概率分布、均方和矩函数的数值汁箅公式,实现了该类系统数值模拟分析的完整算法和程序流程设计．最后,通过两类典型示例系统的数值仿真结粜验证本文算法与流程的正确性和有效性．     

STBC系统在非同分布Nakagami信道下的一种快速性能评估算法

针对非同分布的Nakagami信道,基于矩生成函数MGF(Moment Generation Function)的分析方法,提出正交空时分组码系统STBC(Space-Time Block Coding)的一种快速性能评估算法,不需要涉及超几何函数积分运算,可在中高信噪比时,快速准确地估计STBC系统的符号错误概率性能。在平坦瑞利衰落信道下的计算机仿真表明,该算法与已有的STBC系统的近似估计算法相比,具有较优的性能。     

Accelerated Manhattan hashing via bit-remapping with location information

Multimedia Tools and Applications - Hashing is a binary-code encoding method which tries to preserve the neighborhood structures in the original feature space, in order to realize efficient...     

RT-Thread的SPI总线驱动结构分析 、移植及应用

介绍了串行外设接口SPI的通信原理,对RT Thread操作系统下的SPI总线驱动结构进行了详细的研究与分析.以STM32F407ZG对W25Q64的读写为例,介绍了硬件SPI总线驱动的移植步骤,并详细介绍了SPI应用程序设计及技术实施细节.最后通过实验,对SPI驱动移植及程序设计的可行性及有效性进行验证,实验结果表明,RT Thread操作系统下的SPI总线驱动结构设计合理,移植方便且应用程序设计简单,本文所介绍的移植与应用方法可行有效.     

Bilayer segmentation of webcam videos using tree-based classifiers

This paper presents an automatic segmentation algorithm for video frames captured by a (monocular) webcam that closely approximates depth segmentation from a stereo camera. The frames are segmented into foreground and background layers that comprise a subject (participant) and other objects and individuals. The algorithm produces correct segmentations even in the presence of large background motion with a nearly stationary foreground. This research makes three key contributions: First, we introduce a novel motion representation, referred to as "motons," inspired by research in object recognition. Second, we propose estimating the segmentation likelihood from the spatial context of motion. The estimation is efficiently learned by random forests. Third, we introduce a general taxonomy of tree-based classifiers that facilitates both theoretical and experimental comparisons of several known classification algorithms and generates new ones. In our bilayer segmentation algorithm, diverse visual cues such as motion, motion context, color, contrast, and spatial priors are fused by means of a conditional random field (CRF) model. Segmentation is then achieved by binary min-cut. Experiments on many sequences of our videochat application demonstrate that our algorithm, which requires no initialization, is effective in a variety of scenes, and the segmentation results are comparable to those obtained by stereo systems.     

LabVIEW应用环境下数据库存储性能测试

针对Access、SQL Server 2000以及LabVIEW自带的TDMS数据库进行了相关存储性能的测试.对前两种数据库分别采用LabSQL和数据库连接工具包所提供的算法进行了比较分析.