异构无线传感网络最优簇首选择机制

针对时间驱动的数据收集方式,考虑在异构无线传感器网络中,不同类型的传感器节点采集数据周期不同,节点初始能量异构的研究背景下,结合模糊逻辑原理,提出了一种新型的最优簇首选择机制OCHS. OCHS算法在选择簇首节点的时候,综合考虑节点采集数据周期不同,节点初始能量异构以及节点的分布密度,通过这些因素采用竞争的方式来选举最优的簇首集.成员节点则采用类勾股定理的方法,选择一条链路能耗最小的路径加入该簇. MATLAB仿真表明, OCHS算法能够有效的均衡网络节点能耗、延长整个网络的生存周期以及提高整个网络的稳定期.     

基于SVD与模糊聚类的协同过滤推荐算法

协同过滤为个性化推荐解决信息过载问题提供了方案,然而也存在着数据的稀疏性、可扩展性等影响推荐质量的关键问题.我们提出了一种基于奇异值分解（SVD）与模糊聚类的协同过滤推荐算法,通过引用物理学上狭义相对论中能量守恒的方法以保留总体特征值的数目,较为准确地确定降维维度,实现对原始数据的降维及其数据填充.另外,再运用模糊聚类的方法将相似用户进行聚类,从而达到减少邻居用户搜索范围的目的.在MovieLens与2013年百度电影推荐系统比赛等不同数据集上的实验结果表明,该算法能够提高推荐质量.     

基于图像受噪程度的改进模糊加权均值滤波

根据高斯噪声密度大、噪声强度的波动范围宽,其污染图像不仅每一个像素灰度级都会受影响,而且即使是同一灰度级受污染的程度也会不同的特点和传统的图像模糊滤波算法在图像细节保护方面上的不足,提出基于图像受噪程度的改进模糊加权均值滤波算法,该算法根据图像各像素点的受噪程度,得到首次滤波图像和原图像估计直方图,根据该直方图确定模糊隶属度函数,然后对首次滤波图像中灰度小于25的像素点进行模糊加权均值滤波,该算法在不需要期望图像和高斯噪声方差的情况下能有效地去除噪声,同时能够很好地保护图像细节信息。     

基于GPU的后置处理运动模糊算法

针对虚拟现实系统中运动模糊的真实感绘制问题,着重研究了一种基于图形处理器（GPU）后置处理的运动模糊改进算法. 该算法通过将场景渲染时前后两帧全分辨率纹理图的深度值存入深度缓存区,使用其深度信息与当前帧的映射矩阵提取物体的世界中心坐标,并获取运动的速度矢量;沿速度矢量进行采样、高斯滤波,最后引入模糊因子,并对线性化采样值进行加权融合,力求实现最真实的运动模糊效果. 实验结果表明：所提算法不仅不会影响大型虚拟现实系统的渲染流畅度,更改善了过分重影或者拖影,具有良好的实时性和真实感.     

Wideband turnstile junction coaxial waveguide orthomode transducer

A wideband turnstile junction coaxial waveguide orthomode transducer (OMT) is presented in this paper, featuring coaxial waveguide input and orthogonal rectangular waveguide outputs. It primarily comprises of a turnstile junction, bending stepped impedance transformers and power combiners. The symmetrical geometry helps achieve wide operating bandwidth and balanced output phases. The OMT covers the whole Ku band from 12 to 18 GHz, which aims at wideband dual‐polarized signal combination and separation within coaxial‐type multi‐band antenna systems. An experimental prototype is manufactured and the measured results confirm that the reflection coefficient is lower than ?15 dB within the whole band, and the port isolation is better than 35 dB. Turnstile junction coaxial waveguide OMTs can be adopted widely in circular/coaxial waveguide hybrid feeding networks for multi‐band satellite communication/remote sensing antenna systems.     

Recursive Stochastic H2/H∞ Control Problem for Delay Systems Involving Continuous and Impulse Controls

In this paper, we discuss the recursive stochastic H₂/H_∞ control problem of delay systems with random coefficients involving both continuous and impulse controls. By virtue of a new type of forward backward stochastic differential equations, a necessary and sufficient condition for the existence of a unique solution to the control problem under consideration is derived. The existence and uniqueness of the forward backward stochastic differential equations are also be proved.     

A procedure for the generation of interval type-2 membership functions from data

This paper proposes a new interval type-2 fuzzy set taking extended π interval type-2 membership function (IT2 MF) as its values, and presents a new procedure for generating a set of extended π IT2 MFs from data for an interval type-2 linguistic variable. An extended π IT2 MF is defined as the min and max of two extended π (type-1 or ordinary) membership functions. The procedure has the following steps: (i) for each interval type-2 linguistic variable, specifying the number of membership functions to be generated, i.e. the granularity level, (ii) choosing two fuzzy exponents to be used, (iii) for each fuzzy exponent, applying the fuzzy c-means variant (FCMV) proposed by Liao et al. [1] to obtain the corresponding centers and membership values, and (iv) carrying out parametric optimization by applying a metaheuristic or a hybrid metaheuristic algorithm to determine the optimal parameters associated with the extended π IT2 MFs so that the mean squared error (MSE) or sum of squared errors (SSE) between the membership values obtained by FCMV and those predicted by the extended π IT2 MFs is minimized. The proposed procedure was illustrated with an example and further tested with iris data and weld data. The effects of using two different interval distance measures and the cluster means obtained by the FCMV as part of the initial solutions in the differential evolution metaheuristic were also investigated and discussed.     

Imperfect premise matching controller design for T-S fuzzy systems under network environments

This paper focuses on an imperfect premise matching controller design for T-S fuzzy systems under network environments. Different with the traditional parallel distribution compensation (PDC) method, the same premises between the PDC controller and the T-S fuzzy systems are no longer needed again in the proposed method. Under consideration of the unmatched grades of membership in the networked T-S fuzzy systems, a unified T-S fuzzy model is firstly proposed, in which a networked state-feedback fuzzy controller with communication delays is used to reconstruct the system. Then, based on the constructed model and by use of the Wirtinger-based inequality technique to deal with the cross items, two less conservative stability and stabilization criteria are derived to enhance the design flexibility. Finally, two numerical examples are used to show the effectiveness of proposed method.     

Bayesian zero-order TSK fuzzy system modeling

Different from the existing TSK fuzzy system modeling methods, a novel zero-order TSK fuzzy modeling method called Bayesian zero-order TSK fuzzy system (B-ZTSK-FS) is proposed from the perspective of Bayesian inference in this paper. The proposed method B-ZTSK-FS constructs zero-order TSK fuzzy system by using the maximum a posteriori (MAP) framework to maximize the corresponding posteriori probability. First, a joint likelihood model about zero-order TSK fuzzy system is defined to derive a new objective function which can assure that both antecedents and consequents of fuzzy rules rather than only their antecedents of the most existing TSK fuzzy systems become interpretable. The defined likelihood model is composed of three aspects: clustering on the training set for antecedents of fuzzy rules, the least squares (LS) error for consequent parameters of fuzzy rules, and a Dirichlet prior distribution for fuzzy cluster memberships which is considered to not only automatically match the “sum-to-one” constraints on fuzzy cluster memberships, but also make the proposed method B-ZTSK-FS scalable for large-scale datasets by appropriately setting the Dirichlet index. This likelihood model indeed indicates that antecedent and consequent parameters of fuzzy rules can be linguistically interpreted and simultaneously optimized by the proposed method B-ZTSK-FS which is based on the MAP framework with the iterative sampling algorithm, which in fact implies that fuzziness and probability can co-jointly work for TSK fuzzy system modeling in a collaborative rather than repulsive way. Finally, experimental results on 28 synthetic and real-world datasets are reported to demonstrate the effectiveness of the proposed method B-ZTSK-FS in the sense of approximation accuracy, interpretability and scalability.     

Stable indirect adaptive interval type-2 fuzzy sliding-based control and synchronization of two different chaotic systems

An indirect approach to adaptive interval type-2 fuzzy sliding mode control is proposed for the stable synchronization of two different chaotic nonlinear systems with different initial conditions under the presence of uncertainties involving process noises and external disturbances. The indirect model-based approach to adaptation is promoted here as a more suitable strategy for the fast changes that occurs in chaotic systems. In other words, the usual direct adaptive strategies may be too slow to respond to the inherently fast changing dynamics of chaotic systems. Using Lyapunov analysis, the sliding mode approach illustrates the asymptotic convergence of synchronization error to zero as well as good robustness against external disturbances. The interval type-2 structure aims to remedy the undesirable chattering phenomenon that is common in most conventional sliding mode control applications. It also provides a more effective equivalent model in the indirect approach, which leads to improved handling of the chaotic variations and uncertainties. Two numerical pairs of chaotic systems, i.e. the Lorenz and Chen’s systems and the Rössler system and modified Chua’s circuit are considered. In particular, in comparison with its type-1 fuzzy counterpart, the control effort is reduced by an average of 26.25% and 17.4% for the synchronization of the two corresponding systems, respectively. Furthermore, the integral of squared error is also improved by an average of 27.2% and 25.33%. This is while convergence time is reduced to less than 0.5 s and 1.5 s.