二维条形码的识别及应用

Datamatrix是矩阵式二维条形码之一,由于其尺寸小、保密性好、纠错能力强而广泛使用在工业、数据安全及其他行业.在实际应用中,由扫描设备得到的二维条码图像通常有噪声、污损及背景干扰,并具有平移、旋转.为提高实际应用中的正确译码率,通过预处理和两次图像定位,从实际图像中分割出Datamatrix图像,再从中读取数据,进行正确译码,完成对Datamatrix的识别.     

Efficient PAC Learning for Episodic Tasks with Acyclic State Spaces

This paper considers the problem of computing an optimal policy for a Markov decision process, under lack of complete a priori knowledge of (1) the branching probability distributions determining the evolution of the process state upon the execution of the different actions, and (2) the probability distributions characterizing the immediate rewards returned by the environment as a result of the execution of these actions at different states of the process. In addition, it is assumed that the underlying process evolves in a repetitive, episodic manner, with each episode starting from a well-defined initial state and evolving over an acyclic state space. A novel efficient algorithm for this problem is proposed, and its convergence properties and computational complexity are rigorously characterized in the formal framework of computational learning theory. Furthermore, in the process of deriving the aforementioned results, the presented work generalizes Bechhofer’s “indifference-zone” approach for the ranking & selection problem, that arises in statistical inference theory, so that it applies to populations with bounded general distributions.

基于历史数据语义相似度的智能变电站虚端子自动连接

人工连接智能变电站二次设备虚端子花费时间长,而且完成质量受到人为因素的影响。基于虚端子功能描述信息,通过历史虚连接数据计算虚连接语义相似度,建立二次设备间虚端子自动匹配的数学模型,使用匹配正确概率完成匹配结果的筛选。根据典型二次间隔对智能变电站二次设备进行划分,将智能变电站全站虚端子连接问题简化为二次间隔内的二次设备间的虚端子匹配问题。最后利用前旗220 kV智能变电站算例验证了所提出方法的有效性。     

Maximization of average number of correctly received symbols over multiple channels in the presence of idle periods

In this study, optimal channel switching (time sharing) strategies are investigated under average power and cost constraints for maximizing the average number of correctly received symbols between a transmitter and a receiver that are connected via multiple flat-fading channels with additive Gaussian noise. The optimal strategy is shown to correspond to channel switching either among at most three different channels with full channel utilization (i.e., no idle periods), or between at most two different channels with partial channel utilization. Also, it is stated that the optimal solution must operate at the maximum average power and the maximum average cost, which facilitates low-complexity approaches for obtaining the optimal strategy. For two-channel strategies, an upper bound is derived, in terms of the parameters of the employed channels, on the ratio between the optimal power levels. In addition, theoretical results are derived for characterizing the optimal solution for channel switching between two channels, and for comparing performance of single channel strategies. Sufficient conditions that depend solely on the systems parameters are obtained for specifying when partial channel utilization cannot be optimal. Furthermore, the proposed optimal channel switching problem is investigated for logarithmic cost functions, and various theoretical results are obtained related to the optimal strategy. Numerical examples are presented to illustrate the validity of the theoretical results.     

一种联合收获机脱粒滚筒转速的鲁棒预测控制

联合收获机的轴流式脱粒滚筒转速系统具有强非线性、不确定、滞后、大干扰等特点,以收获机的行走速度和喂入量为控制量,滚筒转速为被控量,建立闭环控制系统,设计时变的鲁棒稳定控制器.在频域内基于比例微分校正技术补偿无级变速传动的滞后环节影响;基于近似模型预测的连续预测控制律保证了大范围工作的控制系统性能;同时,设计收敛的非线性...     

概率近似正确的强化学习算法解决连续状态空间控制问题

在线学习时长是强化学习算法的一个重要指标.传统在线强化学习算法如Q学习、状态–动作–奖励–状态–动作(state-action-reward-state-action,SARSA)等算法不能从理论分析角度给出定量的在线学习时长上界.本文引入概率近似正确(probably approximately correct,PAC)原理,为连续时间确定性系统设计基于数据的在线强化学习算法.这类算法有效记录在线数据,同时考虑强化学习算法对状态空间探索的需求,能够在有限在线学习时间内输出近似最优的控制.我们提出算法的两种实现方式,分别使用状态离散化和kd树(k-dimensional树)技术,存储数据和计算在线策略.最后我们将提出的两个算法应用在双连杆机械臂运动控制上,观察算法的效果并进行比较.     

Abductive Explanation-Based Learning: A Solution to the Multiple Inconsistent Explanation Problem

One problem which frequently surfaces when applying explanation-based learning (EBL) to imperfect theories is themultiple inconsistent explanation problem. The multiple inconsistent explanation problem occurs when a domain theory produces multiple explanations for a training instance, only some of which are correct. Domain theories which suffer from the multiple inconsistent explanation problem can occur in many different contexts, such as when some information is missing and must be assumed: since such assumptions can be incorrect, incorrect explanations can be constructed. This paper proposes an extension of explanation-based learning, calledabductive explanation-based learning (A-EBL) which solves the multiple inconsistent explanation problem by using set covering techniques and negative examples to choose among the possible explanations of a training example. It is shown by formal analysis that A-EBL has convergence properties that are only logarithmically worse than EBL/TS, a formalization of a certain type of knowledge-level EBL; A-EBL is also proven to be computationally efficient, assuming that the domain theory is tractable. Finally, experimental results are reported on an application of A-EBL to learning correct rules for opening bids in the game of contract bridge given examples and an imperfect domain theory.     

用动态有序弹性匹配方法识别手写印刷体汉字

本文为手写印刷体汉字分类提供了一种新的实用解决方法。本方法采用日本山本氏提出的用松驰匹配方法识别手写印刷体汉字的基本思想。给出了用汉字轮廓点的差分作为轮廓跟踪及折断点选择的算法,提高了轮廓折线化速度;分类是按汉字四周的外轮廓线分二级进行匹配的,提出了动态有序弹性匹配方法,使全域松弛匹配得以在局部区域进行,从而有效地提高了匹配速度;在进行第一级粗分类时,采用多个模板,有效地提高了按偏旁位置分布进行分类的正确率;最后利用内轮廓折线与字典逐字匹配,达到手写印刷体汉字识别的目的。本识别系统在386微机上用C语言编程实现,对国标一级3755个汉字进行了三万余字的识别试验,前十位的累计正确分类率达92%,第一位的累计正确分类率达84%。识别时间为每字1.8秒。     

异步保密机中密钥量的分析

在保密机中，密钥量的大小是衡量保密机质量的一个重要指标，正确估算密钥量，提高密钥量，是本文的研究目的。     

二维变速偏移成图系统

地震波的传播速度，可表示为地层中各点坐标的函数．即ν=f(x,y,z)。影响速度的因素很多，如岩性、地层时代、构造发展史等，因此速度的横向变化是不可忽视的。用统一的速度解决地质问题已不适应勘探的要求。变速处理地震剖面已经实现，但在解释上变速成图是个难题，其主要困难是如何进行变速空间归位。二维变速偏移成图系统从客观的地下构造几何形态着手．根据真实的视深度，进行变速偏移空间归位，从而实现变速成图。