Experimental optimization of triangular pulse generation in normal dispersion fiber for all optical processing applications

We experimentally investigate a multi-parameter optimization of conditions for generation of triangular pulses in normal dispersion fiber. We find that triangular pulses suitable for all optical processing applications can be generated for a wide range of input pulse chirps but that triangular pulse quality and stability is improved with increased input pulse chirp.

Analysis and Optimization of Synthetic Aperture Ultrasound Imaging Using the Effective Aperture Approach

An effective aperture approach is used as a tool for analysis and parameter optimization of mostly known ultrasound imaging systems - phased array systems, compounding systems and synthetic aperture imaging systems. Both characteristics of an imaging system, the effective aperture function and the corresponding two-way radiation pattern, provide information about two of the most important parameters of images produced by an ultrasound system - lateral resolution and contrast. Therefore, in the design, optimization of the effective aperture function leads to optimal choice of such parameters of an imaging systems that influence on lateral resolution and contrast of images produced by this imaging system. It is shown that the effective aperture approach can be used for optimization of a sparse synthetic transmit aperture (STA) imaging system. A new two-stage algorithm is proposed for optimization of both the positions of the transmitted elements and the weights of the receive elements. The proposed system employs a 64-element array with only four active elements used during transmit. The numerical results show that Hamming apodization gives the best compromise between the contrast of images and the lateral resolution.

Improvement of stability and load sharing in an autonomous microgrid using supplementary droop control loop

This paper investigates the problem of appropriate load sharing in an autonomous microgrid. High gain angle droop control ensures proper load sharing, especially under weak system conditions. However it has a negative impact on overall stability. Frequency domain modeling, eigenvalue analysis and time domain simulations are used to demonstrate this conflict. A supplementary loop is proposed around a conventional droop control of each DG converter to stabilize the system while using high angle droop gains. Control loops are based on local power measurement and modulation of the d-axis voltage reference of each converter. Coordinated design of supplementary control loops for each DG is formulated as a parameter optimization problem and solved using an evolutionary technique. The sup-plementary droop control loop is shown to stabilize the system for a range of operating conditions while ensuring satisfactory load sharing.

An aspect query language model based on query decomposition and high-order contextual term associations

In information retrieval (IR) research, more and more focus has been placed on optimizing a query language model by detecting and estimating the dependencies between the query and the observed terms occurring in the selected relevance feedback documents. In this paper, we propose a novel Aspect Language Modeling framework featuring term association acquisition, document segmentation, query decomposition, and an Aspect Model (AM) for parameter optimization. Through the proposed framework, we advance the theory and practice of applying high-order and context-sensitive term relationships to IR. We first decompose a query into subsets of query terms. Then we segment the relevance feedback documents into chunks using multiple sliding windows. Finally we discover the higher order term associations, that is, the terms in these chunks with high degree of association to the subsets of the query. In this process, we adopt an approach by combining the AM with the Association Rule (AR) mining. In our approach, the AM not only considers the subsets of a query as “hidden” states and estimates their prior distributions, but also evaluates the dependencies between the subsets of a query and the observed terms extracted from the chunks of feedback documents. The AR provides a reasonable initial estimation of the high-order term associations by discovering the associated rules from the document chunks. Experimental results on various TREC collections verify the effectiveness of our approach, which significantly outperforms a baseline language model and two state-of-the-art query language models namely the Relevance Model and the Information Flow model

Effects of various power system stabilizers on improving power system dynamic performance

To ensure the small-signal stability of a power system, power system stabilizers (PSSs) are extensively applied for damping low frequency power oscillations through modulating the excitation supplied to synchronous machines, and increasing interest has been focused on developing different PSS schemes to tackle the threat of damping oscillations to power system stability. This paper examines four different PSS models and investigates their performances on damping power system dynamics using both small-signal eigenvalue analysis and large-signal dynamic simulations. The four kinds of PSSs examined include the Conventional PSS (CPSS), Single Neuron based PSS (SNPSS), Adaptive PSS (APSS) and Multi-band PSS (MBPSS). A steep descent parameter optimization algorithm is employed to seek the optimal PSS design parameters. To evaluate the effects of these PSSs on improving power system dynamic behaviors, case studies are carried out on an 8-unit 24-bus power system through both small-signal eigenvalue analysis and large-signal time-domain simulations.

Optimized Policies for the Retransmission Probabilities in Slotted Aloha

In this paper, we study the behaviour of the slotted Aloha multiple access scheme with a finite number of users under different traffic loads and optimize the retransmission probability q(r) for various settings, cost objectives and policies. First, we formulate the problem as a parameter optimization problem and use certain efficient smoothed functional algorithms for finding the optimal retransmission probability parameter. Next, we propose two classes of multi-level closed-loop feedback policies (for finding in each case the retransmission probability qr that now depends on the current system state) and apply the above algorithms for finding an optimal policy within each class of policies. While one of the policy classes depends on the number of backlogged nodes in the system, the other depends on the number of time slots since the last successful transmission. The latter policies are more realistic as it is difficult to keep track of the number of backlogged nodes at each instant. We investigate the effect of increasing the number of levels in the feedback policies. Wen also investigate the effects of using different cost functions (withn and without penalization) in our algorithms and the corresponding change in the throughput and delay using these. Both of our algorithms use two-timescale stochastic approximation. One of the algorithms uses one simulation while the other uses two simulations of the system. The two-simulation algorithm is seen to perform better than the other algorithm. Optimal multi-level closed-loop policies are seen to perform better than optimal open-loop policies. The performance further improves when more levels are used in the feedback policies.

On Convergence of Differential Evolution Over a Class of Continuous Functions With Unique Global Optimum

Differential evolution (DE) is arguably one of the most powerful stochastic real-parameter optimization algorithms of current interest. Since its inception in the mid 1990s, DE has been finding many successful applications in real-world optimization problems from diverse domains of science and engineering. This paper takes a first significant step toward the convergence analysis of a canonical DE (DE/rand/1/bin) algorithm. It first deduces a time-recursive relationship for the probability density function (PDF) of the trial solutions, taking into consideration the DE-type mutation, crossover, and selection mechanisms. Then, by applying the concepts of Lyapunov stability theorems, it shows that as time approaches infinity, the PDF of the trial solutions concentrates narrowly around the global optimum of the objective function, assuming the shape of a Dirac delta distribution. Asymptotic convergence behavior of the population PDF is established by constructing a Lyapunov functional based on the PDF and showing that it monotonically decreases with time. The analysis is applicable to a class of continuous and real-valued objective functions that possesses a unique global optimum (but may have multiple local optima). Theoretical results have been substantiated with relevant computer simulations.

Joint Performance Analysis of Channel Quality Indicator Feedback Schemes and Frequency-Domain Scheduling for LTE

Frequency-domain scheduling and rate adaptation enable next-generation orthogonal frequency-division multiple access (OFDMA) cellular systems such as Long-Term Evolution (LTE) to achieve significantly higher spectral efficiencies. LTE uses a pragmatic combination of several techniques to reduce the channel-state feedback that is required by a frequency-domain scheduler. In the subband-level feedback and user-selected subband feedback schemes specified in LTE, the user reduces feedback by reporting only the channel quality that is averaged over groups of resource blocks called subbands. This approach leads to an occasional incorrect determination of rate by the scheduler for some resource blocks. In this paper, we develop closed-form expressions for the throughput achieved by the feedback schemes of LTE. The analysis quantifies the joint effects of three critical components on the overall system throughput-scheduler, multiple-antenna mode, and the feedback scheme-and brings out its dependence on system parameters such as the number of resource blocks per subband and the rate adaptation thresholds. The effect of the coarse subband-level frequency granularity of feedback is captured. The analysis provides an independent theoretical reference and a quick system parameter optimization tool to an LTE system designer and theoretically helps in understanding the behavior of OFDMA feedback reduction techniques when operated under practical system constraints.

受激发射损耗荧光显微镜的模型设计及参量优化

受激发射损耗荧光显微镜利用荧光饱和和激发态荧光受激损耗的非线性关系，通过限制损耗区域，可突破远场光学显微术的衍射极限分辨力并实现三维成像。基于对粒子速率方程组的修正，建立了描述荧光团各能级粒子数概率时间特性的模型，并定义了时间平均损耗效率判据。采用高斯函数模拟两束入射激光脉冲通过对模型的数值计算，模拟了激发脉冲的S1ED激光脉冲的光强、脉冲宽度以及两束光的延迟时间等参量与损耗效率之间的关系，并获得了各参量的最佳值，优化r损耗效率，为提高系统分辨力提供了有效的途径。

Experimental demonstration of a record high 11.25Gb/s real-time optical OFDM transceiver supporting 25km SMF end-to-end transmission in simple IMDD systems.

The fastest ever 11.25Gb/s real-time FPGA-based optical orthogonal frequency division multiplexing (OOFDM) transceivers utilizing 64-QAM encoding/decoding and significantly improved variable power loading are experimentally demonstrated, for the first time, incorporating advanced functionalities of on-line performance monitoring, live system parameter optimization and channel estimation. Real-time end-to-end transmission of an 11.25Gb/s 64-QAM-encoded OOFDM signal with a high electrical spectral efficiency of 5.625bit/s/Hz over 25km of standard and MetroCor single-mode fibres is successfully achieved with respective power penalties of 0.3dB and -0.2dB at a BER of 1.0 x 10(-3) in a directly modulated DFB laser-based intensity modulation and direct detection system without in-line optical amplification and chromatic dispersion compensation. The impacts of variable power loading as well as electrical and optical components on the transmission performance of the demonstrated transceivers are experimentally explored in detail. In addition, numerical simulations also show that variable power loading is an extremely effective means of escalating system performance to its maximum potential.

基于模拟退火算法的挤出模参数优化

建立了塑料熔体在异型材挤出机头流道中的流动均匀性模型 ,阐明了模具结构参数与流动均匀性间的关系,确定了塑料挤出模优化设计的目标函数和设计变量 ,并将一种改进的模拟退火算法用于流线型塑料异型材挤出机头的优化设计。实例表明所用方法对挤出模优化设计的适用性,该方法在利用经验的同时 ,优化了模具结构参数 ,提高了模具设计的智能化

供排气管对接机械手的机构研究与参数优化

根据水下救援作业中连接供排气管的需求,失事对象救生围壁的结构形式,遵循水下机械手机构选型原则,设计了一种专用的六功能气管对接水下机械手,并从机械手工作空间和轻量化要求两方面建立了机械手的数学模型,对其机构参数进行了优化设计。最后对优化结果进行了分析和工作空间的仿真。结果表明该机械手的设计能满足供排气管对接作业要求,达到了预期目的。

扩展CSS仿真程序及其应用

本文介绍了一个连续-离散复合仿真程序。该程序的连续部分基本取自美国的 CSS 程序。经作者扩充后成为复合仿真程序。扩充的模块包括采样系统仿真模块、两点边值问题求解以及参量最优化等。作者提出的单纯形搜索法改进策略可以显著加快参量最优化过程的收敛速度。

基于模糊多目标遗传算法的飞行器模拟件结构参数优化

空间飞行器模拟件的设计是一个具有约束的多目标多准则优化问题。本文在建立空间飞行器模拟件参数优化的数学模型的基础上,将模糊多目标决策理论用于飞行器模拟件的结构参数优化,提出了一种新的模糊评价指数。结构参数优化的结果已经用于某试验系统。