一种改进的二进制查询树RFID标签防碰撞算法

在射频识别（RFID）系统中,存在阅读器与多个标签同时通信的碰撞问题,标签防碰撞技术是解决标签碰撞问题、提高标签识别效率的关键技术。在阐述传统二进制查询树算法（QT）的基础上提出了一种改进的查询树标签防碰撞算法-动态二进制查询树算法（DQT）。该算法通过曼彻斯特编码,识别出碰撞位,从而动态改变查询前缀,使阅读器的查询次数与标签的通信量大大减少,提高了标签的识别效率。仿真实验表明,DQT算法在大量标签识别场合下比QT算法更具有效性和稳定性。     

增强型四叉树RFID防碰撞算法

在四叉树及各类自适应防碰撞算法的基础上,提出一种增强型四叉树防碰撞算法——EFFT(Enhanced four-fork tree )。该算法首先利用曼彻斯特编码准确定位出标签的碰撞位,对K位长度标签提取出其碰撞位形成新的k位标签UID信息,再采取动态四叉树进行识别。在MATLAB平台对EFFT算法、后退式二进制算法、自适应算法进行仿真对比实验。仿真结果与理论分析表明,所提算法大幅度减少了阅读器查询次数和传输比特数,同时也提高了吞吐率及系统识别效率。     

基于转换码的双时隙RFID防碰撞算法

针对无线射频识别(RFID)系统中的标签碰撞问题,提出一种基于转换码的双时隙防碰撞算法BSCC。根据标签附加码的信息,标签在不同的时隙响应阅读器。同时该方法通过编码器编码用转换码表示标签识别码,使阅读器更容易读取碰撞信息,对标签进行准确识别。通过数学分析,准确地描述了BSCC算法识别标签所需的时隙数。仿真结果表明,BSCC算法消除了阅读器识别的空闲时隙,减少系统通信量,提高了标签的识别效率。     

一种改进的RFID标签防碰撞算法

在射频识别系统中,存在阅读器与多个标签同时通信的碰撞问题,标签的防碰撞算法是解决数据冲突的关键。文章详细阐述了已有的二进制查询树的防碰撞算法,并在此基础上进行了改进,使阅读器的询问次数和标签识别所需的数据流大大减少,提高了标签的识别效率。从仿真实验中表明,该算法比已有的二进制查询树算法具有更明显的优势。     

超高频RFID新型后退式二叉树防碰撞算法

针对目前超高频射频识别(radio frequency identification,RFID)二叉树防碰撞算法通信量大和传输时延长等问题,结合跳跃式动态搜索(jumping dynamic search,JDS)和新颖跳跃式动态搜索(novel JDS,NJDS)防碰撞算法,引入后退寻呼策略,提出了一种新的后退式二叉树(novel back-off binary tree,NBBT)防碰撞算法。该算法通过在阅读器寻呼指令中加入引导位使标签以更快的速度响应阅读器,从而减少总通信量和传输时延。仿真结果表明,与现有JDS或NJDS防碰撞算法相比,该算法在传输时延和通信量方面更高效。此外,该算法能够显著提高阅读器和标签之间的通信速率。     

改进的RFID混合查询树防碰撞算法

为了改善射频识别(radio frequency identification,RFID)系统中大量无源标签识别时,普通算法识别速度慢、性能不稳定等的问题,在混合查询树算法的基础上提出了一种改进型的混合查询树防碰撞算法.在原有查询队列的基础上,由每个符合前缀标签的除去前缀后高三位比特中“1”的个数来决定其延时多少个时隙再进行对阅读器的应答;应答过程中,采用曼彻斯特编码进行数据的发送,有效地识别了碰撞位.仿真结果表明,改进算法在大量标签识别的场合比混合查询树算法更具有效性和稳定性.     

一种基于二进制码调制的射频识别防碰撞算法

针对射频识别( RFID)标签防碰撞算法识别效率低的问题,提出一种基于二进制码调制的RFID标签防碰撞算法BCMA。对传统多叉树防碰撞算法进行改进,活动标签采用位编码技术把标签ID在多叉数中的位置信息调制到一个2m位的二进制数主控继电器(MCR)上,并把MCR回送给阅读器;阅读器采用位跟踪技术,定位MCR碰撞发生的数位,从而解调出活动标签的分组信息。阅读器对待识别标签的分组是确定性的,进而避免空闲时隙的产生,提高系统识别效率。仿真结果表明,与常见的八叉树算法相比,BCMA算法使系统吞吐率提高168%。     

基于改进后退策略的按位二进制防碰撞算法

为解决无线射频识别系统中的标签碰撞问题,提出一种基于改进后退策略的按位二进制防碰撞算法。该算法利用标签ID的唯一性,使阅读器只需通过标签ID的部分比特位就能准确地识别某个标签。仿真结果表明,改进的搜索算法能减少阅读器与标签之间的识别通信量及阅读器的搜索次数,提高标签的识别速度。     

基于锁位的并行二进制分割防碰撞算法研究

针对传统超高频射频识别(UHF RFID)系统中出现的多标签碰撞问题,提出一种基于锁位的并行二进制分割(LPBS)防碰撞算法。利用曼彻斯特编码发送锁位指令,确定并提取碰撞位,不再传输非碰撞位信息;利用并行二进制分割技术,使得阅读器和标签可以进行一位标签应答。该算法减少阅读器和标签之间传送的比特数量的同时,减少了碰撞时隙。仿真结果表明,在大多数情况下,该算法在吞吐率、时间延迟等方面优于传统的防碰撞算法。     

计数型双时隙射频识别防碰撞算法

针对射频识别（RFID）二进制搜索防碰撞算法搜索次数多、通信数据量大等问题,在后退式搜索树算法和时隙算法的基础上,提出一种新的计数型双时隙RFID防碰撞算法CBS。CBS算法根据标签中的时隙计数器和阅读器收到的碰撞位信息对标签进行逐级分类搜索,并将应答标签分为两组,分别在两个时隙向阅读器返回数据信息;且阅读器仅发送最高碰撞位位置信息,而标签仅返回最高碰撞位以后的数据位。理论分析和仿真结果表明：和传统的后退式二进制搜索（RBS）算法相比,CBS算法搜索次数减少了51%以上,数据通信量减少了65%以上。CBS算法性能优于其他常用防碰撞算法,能大幅度减少搜索次数和数据通信量,提高搜索效率。     

煤矸石识别方法研究现状与展望

从煤矸石识别特征出发,对煤矸石识别方法的研究现状进行了总结,列举了密度识别法、硬度识别法等以密度、硬度等为识别特征的煤矸石识别方法,以及射线识别法、图像识别法等以灰度、纹理为识别特征的煤矸石识别方法的代表性研究成果,并对比了各种识别方法的特点。对煤矸石识别方法的研究方向和途径进行了展望,提出应全面分析、理解煤矸石的特征差异,研究符合煤矿绿色发展要求的煤矸石识别方法、快速高效的煤矸石图像识别方法、融合和创新现有方法的新型煤矸石高效识别方法。     

关于模糊系统辨识近年来的研究与发展

为了实现理想的模糊控制，基于对象的模糊系统辨识研究具有非常重要的理论与实际应用价值．本文主要从模糊系统结构辨识和参数辨识两方面讨论了近年来在该领域的一些研究内容和方法，分析了它们的主要优缺点并探讨了这一研究领域目前存在的问题和研究趋势．     

An algorithm for bounded-error identification of nonlinear systems based on DC functions

This paper presents a guaranteed method for the parameter estimation of nonlinear models in a bounded-error context. This method is based on functions which consists of the difference of two convex functions, called DC functions. The method considers DC representations of the functional form of the dynamic system to obtain an outer bound of the set of parameters that are consistent with the measurements, the system and the considered bounded error. At each iteration, the proposed algorithm solves several convex optimization problems to discard from the initial search region subregions that are proved not consistent. This operation is repeated while the obtained solution is improved. Four examples are provided to clarify the proposed identification algorithm.     

A virtual closed loop method for closed loop identification

Indirect methods for the identification of linear plant models on the basis of closed loop data are based on the use of (reconstructed) input signals that are uncorrelated with the noise. This generally requires exact (linear) controller knowledge. On the other hand, direct identification requires exact plant and noise modelling (system in the model set) in order to achieve accurate results, although the controller can be non-linear. In this paper, a generalized approach to closed loop identification is presented that includes both methods as special cases and which allows novel combined methods to be generated. Besides providing robustness with respect to inexact controller knowledge, the method does not rely on linearity of the controller nor on exact noise modelling. The generalization is obtained by balancing input-noise decorrelation against noise whitening in a user-chosen flexible fashion. To this end, a user-chosen virtual controller is used to parametrize the plant model, thereby generalizing the dual-Youla method to cases where knowledge of the controller is inexact. Asymptotic bias and variance results are presented for the method. Also, the benefits of the approach are demonstrated via simulation studies.     

压力有关型VAVBOX控制回路的系统辨识

变风量空调末端（VAVBOX）是变风量系统的关键部位,其运行的状况将直接影响空调系统的整个运行效果。本文主要论述了对压力有关型变风量末端控制回路进行了系统辨识,风阀模型采用开环辨识的方法,房间模型辨识中采用了闭环辨识。为研究变风量空调末端（VAVBOX）在室内温度方面的精确控制与抗扰问题打下了坚实基础。     

基于模糊神经网络的非线性系统模型的辨识

该文提出一种非线性系统的模型辨识方法．利用关系聚类法来进行结构辨识，从而自动获得模糊规则库，并可以得到模糊系统的初始参数，在聚类的基础上，构造一个与之相匹配的模糊神经网络，用它的学习算法来训练网络，得到一个精确的模糊模型，从而实现参数辨识，通过对两个非线性系统辨识的仿真结果验证了该方法的有效性。     

Identification of time delays using a polynomial identification method

An algorithm for the exact least-squares identification of an approximate continuous-time time-delay system is derived and its operation verified by simulation.     

Stable on-line parameter identification with general knowledge on level of information noise discrete-time case

An on-line parameter identification problem is posed and solved for discrete-time systems with general knowledge on the level of the inherent information noise. The knowledge can be the bound on either the magnitude or the finite-index ^p norm, pε[1, ∞), of the noise. Based on the knowledge, a switching type gradient algorithm (or called gradient algorithm with dead zone) is proposed to estimate the parameters of the system from the available input-output data. In spite of the existence of the noise, this on-line algorithm guarantees that the estimation error is monotonically decreasing, and the parameter estimate is convergent to a steady-state value under a mild condition. Furthermore, the algorithm is stable in the sense that the estimation error will converge to zero as the bound on the noise gradually diminishes.     

On the accuracy in errors-in-variables identification compared to prediction-error identification

Errors-in-variables estimation problems for single-input–single-output systems with Gaussian signals are considered in this contribution. It is shown that the Fisher information matrix is monotonically increasing as a function of the input noise variance when the noise spectrum at the input is known and the corresponding noise variance is estimated. Furthermore, it is shown that Whittle’s formula for the Fisher information matrix can be represented as a Gramian and this is used to provide a geometric representation of the asymptotic covariance matrix for asymptotically efficient estimators. Finally, the asymptotic covariance of the parameter estimates for the system dynamics is compared for the two cases: (i) when the model includes white measurement noise on the input and the variance of the noise is estimated, and (ii) when the model includes only measurement noise on the output. In both cases, asymptotically efficient estimators are assumed. An explicit expression for the difference is derived when the underlying system is subject only to measurement noise on the output.     

指纹识别技术的研究

由于人体指纹具有唯一性和不变性,使得指纹识别与传统身份识别的方法相比具有更高的安全性和易用性.本文阐述了生物特征识别的发展历史、应用背景,并着重介绍指纹识别系统的工作流程、分类及研究现状.