β—BBO晶体的电光性能

用干涉法测量了β－ＢＢＯ晶体的电光系数：γ２２＝２．６，γ３３＝０．２３，γ３１＝０．２５，γ５１＝－３．５×１０－１２ｍ／Ｖ。结果表明如果在Ｙ方向加电场，Ｚ方向通光，β—ＢＢＯ晶体可能制作成有应用价值的光开关。     

可调谐钛宝石双波长激光在β－BaB_2O_4晶体中和频

根据ＢＢｏ晶体Ｓｅｌｌｍｅｉｅｒ方程确定的折射率，计算了在钛宝石激光可调谐波段的和频相位匹配角。结果与实验基本一致。实验发现了４０７．３～３８４．６ｎｍ可调谐的紫－紫外相干光。     

Handling multiple objectives with biogeography-based optimization

Biogeography-based optimization (BBO) is a new evolutionary optimization method inspired by biogeography. In this paper, BBO is extended to a multi-objective optimization, and a biogeography-based multi-objective optimization (BBMO) is introduced, which uses the cluster attribute of islands to naturally decompose the problem. The proposed algorithm makes use of nondominated sorting approach to improve the convergence ability effciently. It also combines the crowding distance to guarantee the diversity of Pareto optimal solutions. We compare the BBMO with two representative state-of-the-art evolutionary multi-objective optimization methods, non-dominated sorting genetic algorithm-II (NSGA-II) and archive-based micro genetic algorithm (AMGA) in terms of three metrics. Simulation results indicate that in most cases, the proposed BBMO is able to find much better spread of solutions and converge faster to true Pareto optimal fronts than NSGA-II and AMGA do.     

Dendrite crystal morphology evolution mechanism of β-BaB_2O_4 crystal

Existence of [B3-O6]3- hexagonal ring growth unit in melt solution of β-BaB2O4 crystal was proved by the results of high temperature Raman measurements.A morphology evolution process of β-BaB2O4 crys-tal was observed by a high temperature in-situ observation device.The crystal morphology varied with the supersaturation of growth melt solution.The mechanism of β-BaB2O4 crystal morphology evolution was analyzed through the growth unit model.     

Biologically adaptive robust mean shift algorithm with Cauchy predator-prey BBO and space variant resolution for unmanned helicopter formation

Visual tracking technology can provide measurement information for unmanned helicopter formation and thus, more attention is being paid to this research area. We propose a novel mean shift （MS） algorithm that is both adaptive and robust for unmanned helicopter formation and apply it to the leading unmanned helicopter tracking. The movement of an unmanned helicopter is very flexible and changeable, which makes the tracking there of more difficulty than for common targets. In creating an algorithm that can adapt to the acceleration of the unmanned helicopter and estimates both the scale and orientation of the movement changes, we combine the traditional MS with the bio-inspired Cauchy predator-prey biogeography-based optimization （CPPBBO） evolutionary algorithm, and also the space variant resolution （SVR） mechanism of the human visual system （MS-CPPBBO-SVR）. To demonstrate the effectiveness and robustness of the proposed method and justify the importance of the CPPBBO algorithm and SVR mechanism at the same time, a series of comparative exper- iments were carried out. The experimental results of the proposed MS-CPPBBO-SVR method are compared with other competitive tracking methods, such as MS, MS with SVR （MS-SVR）, MS-SVR with several other optimization algorithms, and the robust particle filter algorithm. The experimental results demonstrate that our proposed tracking approach, MS-CPPBBO-SVR, is more adaptive, robust and efficient in target tracking than the other methods.     

多无人艇联合攻击任务规划模型仿真

多水面无人舰艇之间的攻击任务规划是保证无人舰艇顺利高效完成攻击任务.多无人舰艇在执行联合攻击任务时,需要考虑到环境因素、不同任务的复杂度与各种复杂攻击任务执行能力等多方面的约束因素.传统的攻击任务调度模型在处理上述问题时,没有考虑攻击任务外界与内部的约束条件,只是将复杂的攻击任务简单地分解为个体的叠加,在任务执行过程中不仅达不到提高任务执行效率的目的,还会由于缺乏相应的协同规划机制陷入混乱状态.提出一种多无人艇联合攻击任务规划模型.根据水面无人舰艇集群攻击任务规划问题的多约束性,建立任务规划模型,引入代价函数,运用改进的生物地理粒子群优化算法对任务分配问题进行求解,避免了生物地理优化算法容易陷入局部最优和粒子群算法解多约束离散问题时的不稳定性.进行仿真的结果表明,所提出算法有效解决了多水面无人舰艇之间的攻击任务规划问题.     

可调谐钛宝石双波长激光在β－BaB2O4晶体中和频

本文用矩阵光学推导出了相位共轭腔的热稳条件。     

种子注入对可调谐光学参量振荡激光器阈值和转换效率影响的理论与实验研究

通过对种子注入调谐光参量振荡激光器的理论计算．从理论上证明了种子注入法不仅能压窄参量激光的线宽，还能降低参量振荡激光器振荡的阈值．增大其输出参量激光的能量．提高输出激光能量的转换效率．并在实验上给予证明。     

Biogeography based hybrid scheme for automatic detection of epileptic seizures from EEG signatures

Biogeography Based Optimization (BBO) algorithm is one of the nature-inspired optimization methods, based on the study of geographical distribution of species on earth. The present research work is based upon decomposition of human electroencephalograms (EEG) signal by Wavelet Packet Transform, computation of a complete feature set using statistical and non-statistical properties followed by optimal selection of features by BBO; the optimality criterion being classification rate. The stopping criterion for BBO is set to 100% correct classification rate. The proposed algorithm is novel in terms of TWSVM computing the Habitat Suitability Index (HSI) values for BBO, perfect classification rate, low computation time, and feature selection mechanism. The proposed scheme outperforms several previous results reported in literature in that it gives a feature subset which gives 100% classification accuracy for different classification instances.     

Parkinson’s Disease Detection Using Biogeography-Based Optimization

In recent years, Parkinson's Disease (PD) as a progressive syndrome of the nervous system has become highly prevalent worldwide. In this study, a novel hybrid technique established by integrating a Multi-layer Perceptron Neural Network (MLP) with the Biogeography-based Optimization (BBO) to classify PD based on a series of biomedical voice measurements. BBO is employed to determine the optimal MLP parameters and boost prediction accuracy. The inputs comprised of 22 biomedical voice measurements. The proposed approach detects two PD statuses: 0-disease status and 1- good control status. The performance of proposed methods compared with PSO, GA, ACO and ES method. The outcomes affirm that the MLP-BBO model exhibits higher precision and suitability for PD detection. The proposed diagnosis system as a type of speech algorithm detects early Parkinson’s symptoms, and consequently, it served as a promising new robust tool with excellent PD diagnosis performance.