Online prediction of EEG based on KRLST algorithm

Kernel adaptive algorithm is an extension of adaptive algorithm in nonlinear,and widely used in the field of non-stationary signal processing.But the distribution of classic data sets seems relatively regular and simple in time series.The distribution of the electroencephalograph(EEG)signal is more randomness and non-stationarity,so online prediction of EEG signal can further verify the robustness and applicability of kernel adaptive algorithms.What’s more,the purpose of modeling and analyzing the time series of EEG signals is to discover and extract valuable information,and to reveal the internal relations of EEG signals.The time series prediction of EEG plays an important role in EEG time series analysis.In this paper,kernel RLS tracker(KRLST)is presented to online predict the EEG signals of motor imagery and compared with other 13 kernel adaptive algorithms.The experimental results show that KRLST algorithm has the best effect on the brain computer interface(BCI)dataset.

认知无线电网络频谱分配与协作集划分算法

针对协作认知无线电网络中较为复杂的多主用户与多次级用户共存场景,提出联合频谱分配与协作集划分问题,并将该问题形式化描述为整数0-1非线性规划问题,证明其是NP-hard的.首先,设计了集中式的遗传算法CGA(centralized genetic algorithm)对问题求解,对该算法进行齐次有限马尔可夫链建模并对其全局收敛性进行了分析;随后,提出了一种包含两阶段的分布式遗传算法DGA(distributed genetic algorithm),包括基于最小支配集的分簇与频谱预分配阶段和簇间协作集协商与簇内适应值精化阶段.此外,还提出一种快速收敛的DGA算法(fast-convergent DGA,简称FDGA)缩短分布式算法运行时间.仿真实验结果表明,根据能反映出算法性能的适应值结果对各算法进行比较:(1)小规模网络下CGA获得的解平均为通过穷举算法得到的最优值的92%;(2)随着网络规模的扩大,由于CGA搜索空间增大,DGA,FDGA在达到相同停机条件时获得的适应值比CGA提高约20%;(3)与DGA相比,FDGA虽能得到与DGA相近的结果,但却大大缩短了算法收敛的时间,更适应于大规模网络应用.

影响信息特征搜索的凝视/扫视指标与瞳孔变化幅度一致性效应比较

数字化交互界面中的信息呈现方式对操作员信息特征搜索的任务执行效率起着至关重要的作用.文中以信息特征及呈现方式作为变量,展开视觉搜索实验.首先提出搜索不同复杂程度的信息单元、不同形态特征对凝视/扫视及瞳孔幅度呈规律性变化等3个假设,并以核电安注系统为例进行实验设计;其次通过眼动实验数据记录的凝视/扫视时间及路径指标、瞳孔直径进行比较,并讨论信息复杂程度与瞳孔幅度变化、凝视时间与瞳孔幅度的一致性效应.实验结果表明,图标形态和信息呈现方式对视觉搜索均具有显著性影响,凝视/扫视时间及路径能够反映图标形态的复杂程度及信息呈现的难易程度;瞳孔变化幅度与凝视/扫视指标相同,也可作为视觉认知绩效的灵敏指标,单一图标-形态组B到信息块形态组A呈线性递增趋势,具有一致性效应.该结论揭示了信息特征搜索的影响因素,瞳孔幅度变化与凝视/扫视指标的一致性效应可作为信息呈现方式的重要指标应用于未来界面优化设计中.

数字化监控任务界面中信息特征的视觉搜索实验

针对信息特征的视觉搜索过程,从凝视-扫视的浏览路径分析操作员搜索信息的注意资源分配,展开眼动跟踪实验.实验结果表明,搜索路径受任务驱动影响,在不同任务下反应时与眼动数据均有显著性差异;不同监控区域的信息分布注意捕获亦有显著性差异.凝视/扫视比表明,实验材料中监控任务布局的信息搜索较低;信息方位与信息特征容易被捕获.由此得到了认知信息处理与任务的关系、信息搜索与监控区域的关系以及信息特征的集簇关系.该结论能够有效指导监控任务界面的改良设计,从而提高操作员任务执行的认知绩效.

Winter wheat identification by integrating spectral and temporal information derived from multi-resolution remote sensing data

Timely crop acreage and distribution information are the basic data which drive many agriculture related applications.For identifying crop types based on remote sensing,methods using only a single image type have significant limitations.Current research that integrates fine and coarser spatial resolution images,using techniques such as unmixing methods,regression models,and others,usually results in coarse resolution abundance without sufficient detail within pixels,and limited attention has been paid to the spatial relationship between the pixels from these two kinds of images.Here we propose a new solution to identify winter wheat by integrating spectral and temporal information derived from multi-resolution remote sensing data and determine the spatial distribution of sub-pixels within the coarse resolution pixels.Firstly,the membership of pixels which belong to winter wheat is calculated using a 25-m resolution resampled Landsat Thematic Mapper(TM)image based on the Bayesian equation.Then,the winter wheat abundance(acreage fraction in a pixel)is assessed by using a multiple regression model based on the unique temporal change features from moderate resolution imaging spectroradiometer(MODIS)time series data.Finally,winter wheat is identified by the proposed Abundance-Membership(AM)model based on the spatial relationship between the two types of pixels.Specifically,winter wheat is identified by comparing the spatially corresponding 10×10 membership pixels of each abundance pixel.In other words,this method takes advantage of the relative size of membership in a local space,rather than the absolute size in the entire study area.This method is tested in the major agricultural area of Yiluo Basin,China,and the results show that acreage accuracy(Aa)is 93.01%and sampling accuracy(As)is 91.40%.Confusion matrix shows that overall accuracy(OA)is 91.4%and the kappa coefficient(Kappa)is 0.755.These values are significantly improved compared to the traditional Maximum Likelihood classification(MLC)and Random Forest classification(RFC)which rely on spectral features.The results demonstrate that the identification accuracy can be improved by integrating spectral and temporal information.Since the identification of winter wheat is performed in the space corresponding to each MODIS pixel,the influence of differences of environmental conditions is greatly reduced.This advantage allows the proposed method to be effectively applied in other places.

Cognitive mechanism related to line drawings and its applications in intelligent process of visual media： a survey

Line drawings, as a concise form, can be recognized by infants and even chimpanzees. Recently, how the visual system processes line-drawings attracts more and more attention from psychology, cognitive science and computer science. The neuroscientific studies revealed that line drawings generate similar neural actions as color photographs, which give insights on how to efficiently process big media data. In this paper, we present a comprehensive survey on line drawing studies, including cognitive mechanism of visual perception, computational models in computer vision and intelligent process in diverse media applications. Major debates, challenges and solutions that have been addressed over the years are discussed. Finally some of the ensuing challenges in line drawing studies are outlined.

Revocable Ring Signature

Group signature allows the anonymity of a real signer in a group to be revoked by a trusted party called group manager. It also gives the group manager the absolute power of controlling the formation of the group. Ring signature, on the other hand, does not allow anyone to revoke the signer anonymity, while allowing the real signer to form a group （also known as a ring） arbitrarily without being controlled by any other party. In this paper, we propose a new variant for ring signature, called Revocable Ring Signature. The signature allows a real signer to form a ring arbitrarily while allowing a set of authorities to revoke the anonymity of the real signer. This new variant inherits the desirable properties from both group signature and ring signature in such a way that the real signer will be responsible for what it has signed as the anonymity is revocable by authorities while the real signer still has the freedom on ring formation. We provide a formal security model for revocable ring signature and propose an efficient construction which is proven secure under our security model.

Remote monitoring cost minimization for an unreliable sensor network with guaranteed network throughput

In this paper we consider a link-unreliable remote monitoring scenario where the monitoring center is geographically located far away from the region of the deployed sensor network,and sensing data by the sensors in the network will be transferred to the remote monitoring center through a third party telecommunication service.A cost associated with this service will be incurred,which will be determined by the number of gateways employed and the cumulative volume of data successfully received within a specified monitoring period.For this scenario,we first formulate a novel constrained optimization problem with an objective to minimize the service cost while a pre-defined network throughput is guaranteed.We refer to this problem as the throughput guaranteed service cost minimization problem and prove that it is NP-complete.We then propose a heuristic for it.The key ingredients of the heuristic include identifying gateways and finding an energy-efficient forest of routing trees rooted at the gateways.We also perform theoretical analysis on the solution obtained.Finally,we conduct experiments by simulations to evaluate the performance of the proposed algorithm.Experimental results demonstrate the proposed algorithm outperforms other algorithms in terms of both the service cost and the network lifetime.

Fundamental functional differences between gyri and sulci: implications for brain function, cognition, and behavior

Folding of the cerebral cortex is a prominent characteristic of mammalian brains.Alterations or deficits in cortical folding are strongly correlated with abnormal brain function,cognition,and behavior.Therefore,a precise mapping between the anatomy and function of the brain is critical to our understanding of the mechanisms of brain structural architecture in both health and diseases.Gyri and sulci,the standard nomenclature for cortical anatomy,serve as building blocks to make up complex folding patterns,providing a window to decipher cortical anatomy and its relation with brain functions.Huge efforts have been devoted to this research topic from a variety of disciplines including genetics,cell biology,anatomy,neuroimaging,and neurology,as well as involving computational approaches based on machine learning and artificial intelligence algorithms.However,despite increasing progress,our understanding of the functional anatomy of gyro-sulcal patterns is still in its infancy.In this review,we present the current state of this field and provide our perspectives of the methodologies and conclusions concerning functional differentiation between gyri and sulci,as well as the supporting information from genetic,cell biology,and brain structure research.In particular,we will further present a proposed framework for attempting to interpret the dynamic mechanisms of the functional interplay between gyri and sulci.Hopefully,this review will provide a comprehensive summary of anatomo-functional relationships in the cortical gyro-sulcal system together with a consideration of how these contribute to brain function,cognition,and behavior,as well as to mental disorders.