基于自识别交叉算子和自适应变异算子的遗传算法研究

为有效地解决遗传算法收敛速度和局部最优解的矛盾,本文提出了一种具有自识别交叉算子和基于海明距离的动态变异算子的遗传算法。自识别交叉算子保证父代的优良模式遗传到下一代,加快了算法的收敛速度;而动态变异算子扩大了搜索范围,增强了算法跳离局部最优解的能力。实验证明,两种改进算子的有效结合保证算法能以较快速度收敛于全局最优解。

算子识别反问题模型优化与数据优化的联合反演技术

针对算子识别反问题,分析了解的不适定性与模型误差、数据误差的关系,建立了基于模型优化和数据优化的联合反演技术,提出了适合同时处理数字式数据与非数字式数据的量化单调消噪方法。建立了数值反演可靠性概念,包括正演算子可靠性、正演计算可靠性、测量设计可靠性、反演算法可靠性、反演计算可靠性、测量数据可靠性,并建立了相应的可靠性定量评估方法。通过一个岩土工程的算子识别反问题的工程应用与数值试验说明:其一,这一联合反演技术实质是一门系统性的优化技术,能够显著提高数值反演的可靠性和准确度;其二,应用可靠性定量评估方法,能够客观地、定量地获得反问题解估计的质量评定。

一类扩散方程参数算子识别反问题的模拟退火算法

文章给出了利用模拟退火算法求解一类扩散方程的参数算子识别反问题的一种新方法。该方法把对于参数算子识别反问题转化为优化问题并用模拟退火算法进行求解。在Matlab语言环境下实现了该算法,并且与其他文献中用遗传算法求解的例子进行比较。数值模拟结果表明,该算法同样具有可行性和有效性,并且具有较高的精度。

具有自识别能力的遗传算法求解旅行商问题

为解决基本遗传算法求解旅行商(TSP)问题收敛速度慢、种群过早成熟和局部搜索能力差的问题,提出了一种具有自识别能力的遗传算法。算法的主要改进手段是,通过双向贪婪算法来构建初始种群,以提高寻找到最优解的速度;建立个体之间相似度的概念,用自识别交叉算子进行交叉操作,避免种群过早成熟。实验结果表明,与基本遗传算法相比,该算法很好地保持了群体的多样性,并具有较好的收敛速度。仿真结果验证了算法的良好性能。

基于灰关联分析的舰船障碍物自动识别系统

传统舰船障碍物识别系统的连接响应效率过低,且识别结果的准确性始终达不到预期标准。为解决上述问题,引入灰关联分析法则,设计新型舰船障碍自动识别系统。通过识别判断窗建立、障碍物图像分割模块设计两个步骤,完成新型系统的硬件运行环境搭建。在此基础上,通过自动识别准则确立、障碍物完整性判断、自动识别算子提取3个步骤,完成新型系统的软件运行环境搭建,结合软、硬件运行环境,实现基于灰关联分析舰船障碍自动识别系统的顺利运行。对比实验结果表明,与传统系统相比,新型舰船障碍自动识别系统的连接响应效率提升明显,识别结果准确度最大值接近90%。

强干扰下舰船通信网络信号传输质量检测方法

为解决舰船通信网络信号质量检测区间受限的问题,提出强干扰下的新型舰船通信网络信号传输质量检测方法。通过信号波形特征提取、干扰算子定义2个步骤,完成强干扰下舰船通信网络的信号识别。在此基础上,通过传输信号质量的抖动幅值定义、传输时间间隔误差计算、检测相位算子求解3个步骤,完成新型信号传输质量检测方法的搭建。对比实验结果表明,与传统检测方法相比,应用强干扰下舰船通信网络信号传输质量检测方法后,待检测信号质量算子的最大值超过9.50 Mb,最小值低于2.00 Mb,整个检测区间长度得到明显扩充。

基于改进的遗传算法的快速图像相关匹配

为了解决图像匹配中计算速度慢和匹配精度不高的缺陷,提出了一种基于改进的遗传算法的匹配方法,算法的主要改进手段是,用自识别交叉算子进行交叉操作,避免种群过早成熟。实验结果表明,与基本遗传算法相比,基于该算法的图像匹配具有运算量小、匹配精确等优点,且算法稳定。

FACE RECOGNITION USING TWO DIMENSIONAL LAPLACIAN EIGENMAP

Recently, some research efforts have shown that face images possibly reside on a nonlinear sub-manifold. Though Laplacianfaees method considered the manifold structures of the face images, it has limits to solve face recognition problem. This paper proposes a new feature extraction method, Two Dimensional Laplacian EigenMap （2DLEM）, which especially considers the manifold structures of the face images, and extracts the proper features from face image matrix directly by using a linear transformation. As opposed to Laplacianfaces, 2DLEM extracts features directly from 2D images without a vectorization preprocessing. To test 2DLEM and evaluate its performance, a series of ex- periments are performed on the ORL database and the Yale database. Moreover, several experiments are performed to compare the performance of three 2D methods. The experiments show that 2DLEM achieves the best performance.

A robust feature extraction approach based on an auditory model for classification of speech and expressiveness

Based on an auditory model, the zero-crossings with maximal Teager energy operator (ZCMT) feature extraction approach was described, and then applied to speech and emotion recognition. Three kinds of experiments were carried out. The first kind consists of isolated word recognition experiments in neutral (non-emotional) speech. The results show that the ZCMT approach effectively improves the recognition accuracy by 3.47% in average compared with the Teager energy operator (TEO). Thus, ZCMT feature can be considered as a noise-robust feature for speech recognition. The second kind consists of mono-lingual emotion recognition experiments by using the Taiyuan University of Technology (TYUT) and the Berlin databases. As the average recognition rate of ZCMT approach is 82.19%, the results indicate that the ZCMT features can characterize speech emotions in an effective way. The third kind consists of cross-lingual experiments with three languages. As the accuracy of ZCMT approach only reduced by 1.45%, the results indicate that the ZCMT features can characterize emotions in a language independent way.

3D Object Visual Tracking for the 220 kV/330 kV High-Voltage Live-Line Insulator Cleaning Robot

The 3D object visual tracking problem is studied for the robot vision system of the 220kV/330kV high-voltage live-line insulator cleaning robot. The SUSAN Edge based Scale Invariant Feature (SESIF) algorithm based 3D objects visual tracking is achieved in three stages: the first frame stage,tracking stage,and recovering stage. An SESIF based objects recognition algorithm is proposed to find initial location at both the first frame stage and recovering stage. An SESIF and Lie group based visual tracking algorithm is used to track 3D object. Experiments verify the algorithm's robustness. This algorithm will be used in the second generation of the 220kV/330kV high-voltage live-line insulator cleaning robot.

Automatic recognition and quantitative analysis of Ω phases in Al-Cu-Mg-Ag alloy

The main methods of the second phase quantitative analysis in current material science researches are manual recognition and extracting by using software such as Image Tool and Nano Measurer. The weaknesses such as high labor intensity and low accuracy statistic results exist in these methods. In order to overcome the shortcomings of the current methods, the Ω phase in A1-Cu-Mg-Ag alloy is taken as the research object and an algorithm based on the digital image processing and pattern recognition is proposed and implemented to do the A1 alloy TEM （transmission electron microscope） digital images process and recognize and extract the information of the second phase in the result image automatically. The top-hat transformation of the mathematical morphology, as well as several imaging processing technologies has been used in the proposed algorithm. Thereinto, top-hat transformation is used for elimination of asymmetric illumination and doing Multi-layer filtering to segment Ω phase in the TEM image. The testing results are satisfied, which indicate that the Ω phase with unclear boundary or small size can be recognized by using this method. The omission of these two kinds of Ω phase can be avoided or significantly reduced. More Ω phases would be recognized （growing rate minimum to 2% and maximum to 400% in samples）, accuracy of recognition and statistics results would be greatly improved by using this method. And the manual error can be eliminated. The procedure recognizing and making quantitative analysis of information in this method is automatically completed by the software. It can process one image, including recognition and quantitative analysis in 30 min, but the manual method such as using Image Tool or Nano Measurer need 2 h or more. The labor intensity is effectively reduced and the working efficiency is greatly improved.

Identification of Sperm Subpopulations in Water Buffalo Ejaculates： Changes in Cryopreservation Stages and Bull Variation

This study aimed to identify and characterize the sperm subpopulations existing in water buffalo semen using a computer assisted sperm analyzer （CASA）, as well as assess the effects of cryopreservation on the sperm subpopulation structure and evaluate bull variability. The semen of eight Bulgarian Murrah bulls was collected by four times in an interval of one week each. The semen was cryopreserved following a standard protocol and sperm kinematics was assessed. Clustering methods were applied to individual sperms, forming two significantly different （P 〈 0.05） subpopulations （P1 and P2）. Subpopulation P1 represents those spermatozoa that moved most rapidly and progressively （46.29%）, and subpopulation P2 includes spermatozoa with relatively low velocity or poorly motile but with high progressiveness （53.41%）. There was a decline on the population of P1 sperms from fresh （52.52%）, pre-freeze （45.73%） to post-thaw （35.17%） stages and significant difference on the sperm kinematics between P1 and P2. A significant decline in the values of distance, velocity and amplitude of lateral head （ALH） parameters were observed at post-thaw stage, while an increase was observed on trajectory and beat cross frequency （BCF） kinematics. Values of sperm kinematics were also significantly different （P 〈 0.05） among all bulls. The frequency distribution of spermatozoa on both subpopulations P1 and P2 was quite similar for all bulls in pre-freeze and post-thaw stages, but with significant （P 〈 0.05） variability on fresh stage. Bulls with the highest maintained frequency of P1 sperms are denoted as good freezer bulls. In sum, kinematic characterization of water buffalo sperm and clustering into subpopulation enable to identify bulls that are more resistant to cryopreservation and production of quality semen for genetic propagation.

Experimental quantum Hamiltonian identification from measurement time traces

Identifying Hamiltonian of a quantum system is of vital importance for quantum information processing.In this article, we realized and benchmarked a quantum Hamiltonian identification algorithm recently proposed(Zhang and Sarovar, 2014). we realized the algorithm on a liquid nuclear magnetic resonance quantum information processor using two types of working media with different forms of Hamiltonian. Our experiment realized the quantum identification algorithm based on free induction decay signals. We also showed how to process data obtained in a practical experiment. We studied the influence of decoherence by numerical simulations. Our experiments and simulations demonstrate that the algorithm is effective and robust.