The optimal robust control policy for uncertain semi-Markov control processes

The optimization problems of Markov control processes (MCPs) with exact knowledge of system parameters, in the form of transition probabilities or infinitesimal transition rates, can be solved by using the concept of Markov performance potential which plays an important role in the sensitivity analysis of MCPs. In this paper, by using an equivalent infinitesimal generator, we first introduce a definition of discounted Poisson equations for semi-Markov control processes (SMCPs), which is similar to that for MCPs, and the performance potentials of SMCPs are defined as solution of the equation. Some related optimization techniques based on performance potentials for MCPs may be extended to the optimization of SMCPs if the system parameters are known with certainty. Unfortunately, exact values of the distributions of the sojourn times at some states or the transition probabilities of the embedded Markov chain for a large-scale SMCP are generally difficult or impossible to obtain, which leads to the uncertainty of the semi-Markov kernel, and thereby to the uncertainty of equivalent infinitesimal transition rates. Similar to the optimization of uncertain MCPs, a potential-based policy iteration method is proposed in this work to search for the optimal robust control policy for SMCPs with uncertain infinitesimal transition rates that are represented as compact sets. In addition, convergence of the algorithm is discussed.     

一种多芯片封装(MCP)的热仿真设计

集成电路封装热设计的目的在于尽可能地提高封装的散热能力,确保芯片的正常运行。多芯片封装(MCP)可以提高封装的芯片密度,提高处理能力。与传统的单芯片封装相比,由于包含多个热源,多芯片封装的热管理变得更为关键。本文针对一种2维FBGAMCP产品,进行有限元建模仿真,并获得封装的热性能。通过热阻比较的方式,分析了不同的芯片厚度对封装热性能的影响。针对双芯片封装,通过对不同的芯片布局进行建模仿真,获得不同的芯片布局对封装热阻的影响。最后通过封装热阻的比较,对芯片的排列布局进行了优化。分析结果认为芯片厚度对封装热阻的影响并不明显,双芯片在基板中心呈对称排列时封装的热阻最小。     

KnowBaSICS-M: an ontology-based system for semantic management of medical problems and computerised algorithmic solutions

In this paper, an ontology-based system (KnowBaSICS-M) is presented for the semantic management of Medical Computational Problems (MCPs), i.e., medical problems and computerised algorithmic solutions. The system provides an open environment, which: (1) allows clinicians and researchers to retrieve potential algorithmic solutions pertinent to a medical problem and (2) enables incorporation of new MCPs into its underlying Knowledge Base (KB). KnowBaSICS-M is a modular system for MCP acquisition and discovery that relies on an innovative ontology-based model incorporating concepts from the Unified Medical Language System (UMLS). Information retrieval (IR) is based on an ontology-based Vector Space Model (VSM) that estimates the similarity among user-defined MCP search criteria and registered MCP solutions in the KB. The results of a preliminary evaluation and specific examples of use are presented to illustrate the benefits of the system. KnowBaSICS-M constitutes an approach towards the construction of an integrated and manageable MCP repository for the biomedical research community.     

A Superscalar software architecture model for Multi-Core Processors (MCPs)

Design of high-performance servers has become a research thrust to meet the increasing demand of network-based applications. One approach to design such architectures is to exploit the enormous computing power of Multi-Core Processors (MCPs) that are envisioned to become the state-of-the-art in processor architecture. In this paper, we propose a new software architecture model, called SuperScalar, suitable for MCP machines. The proposed SuperScalar model consists of multiple pipelined thread pools, where each pipelined thread pool consists of multiple threads, and each thread takes a different role. The main advantages of the proposed model are global information sharing by the threads and minimal memory requirement due to fewer threads.We have conducted in-depth performance analyses of the proposed scheme along with three prior software architecture schemes (Multi-Process (MP), Multi-Thread (MT) and Event-Driven (ED)) via an analytical model. The performance results indicate that the proposed SuperScalar model shows the best performance across all system and workload parameters compared to the MP, MT and ED models. Although the MT model shows competitive performance with less number of processing cores and smaller data cache size, the advantage of the SuperScalar model becomes obvious as the number of processing cores increases.     

Multiple Comparisons in Induction Algorithms

A single mechanism is responsible for three pathologies of induction algorithms: attribute selection errors, overfitting, and oversearching. In each pathology, induction algorithms compare multiple items based on scores from an evaluation function and select the item with the maximum score. We call this a multiple comparison procedure (MCP). We analyze the statistical properties of MCPs and show how failure to adjust for these properties leads to the pathologies. We also discuss approaches that can control pathological behavior, including Bonferroni adjustment, randomization testing, and cross-validation.     

Unified mechanism synthesis method of a planar four-bar linkage for path generation employing a spring-connected arbitrarily sized rectangular block model

In the present study, a unified mechanism synthesis method that carries out type and dimensional syntheses simultaneously is proposed to solve path generation synthesis of a planar four-bar linkage. A spring-connected arbitrarily sized rectangular block model is introduced and an optimization problem using the block model is formulated. Several path generation synthesis problems are successfully solved with the proposed method. It is verified that the proposed method is computationally more efficient than the previous method employing a constant size block model. Furthermore, the proposed method is shown to solve some path synthesis problems that could not be solved by the previous method. Finally, an index to define the level of difficulty of a path generation synthesis problem is proposed, and the index limit value of path generation problems that can be solved by the proposed method is obtained.     

An new immune genetic algorithm based on uniform design sampling

The deficiencies of keeping population diversity, prematurity and low success rate of searching the global optimal solution are the shortcomings of genetic algorithm (GA). Based on the bias of samples in the uniform design sampling (UDS) point set, the crossover operation in GA is redesigned. Using the concentrations of antibodies in artificial immune system (AIS), the chromosomes concentration in GA is defined and the clonal selection strategy is designed. In order to solve the maximum clique problem (MCP), an new immune GA (UIGA) is presented based on the clonal selection strategy and UDS. The simulation results show that the UIGA provides superior solution quality, convergence rate, and other various indices to those of the simple and good point GA when solving MCPs.     

Quantum circuit physical design methodology with emphasis on physical synthesis

In our previous works, we have introduced the concept of “physical synthesis” as a method to consider the mutual effects of quantum circuit synthesis and physical design. While physical synthesis can involve various techniques to improve the characteristics of the resulting quantum circuit, we have proposed two techniques (namely gate exchanging and auxiliary qubit selection) to demonstrate the effectiveness of the physical synthesis. However, the previous contributions focused mainly on the physical synthesis concept, and the techniques were proposed only as a proof of concept. In this paper, we propose a methodological framework for physical synthesis that involves all previously proposed techniques along with a newly introduced one (called auxiliary qubit insertion). We will show that the entire flow can be seen as one monolithic methodology. The proposed methodology is analyzed using a large set of benchmarks. Experimental results show that the proposed methodology decreases the average latency of quantum circuits by about 36.81 % for the attempted benchmarks.     

基于条块拼接的快速纹理合成

针对离线纹理合成算法所生成纹理占用较多存储空间的问题,提出一种所生成纹理可紧凑保存的快速纹理合成算法.该算法相继沿垂直和水平方向以条块拼接的方式合成纹理,合成结果可表示为一系列切割路径的组合,仅需保存这些切割路径即可在渲染时实时重建出纹理图像.通过在预处理中计算得到一组误差小的平行切割路径,合成时无需进行匹配,使得合成速度大幅提高.该算法对于在水平和垂直方向具有自相似性的纹理具有较高的合成质量.     

Scalable multi-process inter-server collaborative design synthesis in the Internet distributed resource environment

With the advanced Internet, numerous and diverse design resources distributed in different locations and disciplines are becoming more and more accessible for designers. To help designers make the most of this Internet distributed resource environment in the design synthesis, a scalable multi-process inter-server collaborative method is proposed in this study. A distributed design resource management mechanism is proposed based on the input–output flow model, and a scalable multi-process inter-server collaborative algorithm is proposed for the design synthesis. Based on this method, a software prototype is established, and the design synthesis of a 3-DOF wave power system is completed with it.     

Synthesis of antenna arrays with an efficient multiobjective differential evolution algorithm

An efficient multiobjective differential evolution algorithm for array synthesis is proposed in this article. By introducing novel strategies in the generalized differential evolution (GDE3), the proposed algorithm can generate a better converged and distributed Pareto front than the standard GDE3. Five typical benchmark functions are optimized by the proposed improved GDE3 (IGDE) to verify its effectiveness. Furthermore, the proposed algorithm is applied in two‐pattern synthesis problems, including an unequal spaced linear array and a conformal array. The superior performance of the proposed IGDE demonstrates that it is an efficient and competitive algorithm in the function optimization, pattern synthesis, and other electromagnetic problems. © 2013 Wiley Periodicals, Inc. Int J RF and Microwave CAE 24:161–169, 2014.     

A method for the modular synthesis of controllers for timed discrete-event systems

A method for the modular supervisory control of timed discrete-event systems (TDES) is presented. The modular synthesis method is an extension of the centralized synthesis method proposed in our earlier work. We consider a state predicate specification as a conjunction of several state subpredicate specifications. The control problem is to synthesize a modular controller, the conjunction of all individual controllers, in such a way that the closed-loop behaviour of TDES satisfies the state predicate specification. Our modular synthesis method is developed based on the concept of state space of TDES, the notion of control-invariant state predicates for the TDES and a fixed point algorithm to calculate a control-invariant state subpredicate of a given state predicate. In addition, for the development of our modular synthesis method, we introduce the notion of control-invariance non-conflict among control-invariant state predicates, and the notion of forcing-non-conflict among controllers synthesized based on control-invariant state predicates which are control-invariance non-conflicting. The modular synthesis method in general offers better design flexibility and may require fewer computations than the centralized one. As in our centralized synthesis method, the proposed modular synthesis method does not require the construction and examination of complete sequences of event trajectories of the system. It is suggested that the computation of our proposed method of yielding solutions for a class of synthesis problems in TDES can be economical.     

On variable structure output feedback controllers for uncertaindynamic systems

A class of variable structure output feedback controllers for uncertain dynamic systems with bounded uncertainties is proposed. No statistical information about the uncertain elements is assumed. A variable structure systems approach and a geometric approach to the analysis and synthesis of system zeros are employed in the synthesis of the proposed controllers     

An evolutionary approach to design practical μ synthesis controllers

This paper proposes an evolutionary approach to solve μ synthesis problem. The goal is to achieve low order, practical μ synthesis controllers without any order reduction. In the proposed approach µ synthesis problem is solved as a constraint optimization problem in which robust stability and robust performance based on μ analysis are considered as the constraint and the cost function respectively. In order to solve the optimization problem an improved particle swarm optimization (PSO) is chosen to find the required coefficients of a structure-specified controller. The performance and robustness of the proposed controller are investigated by an uncertain mass-damper-spring system and is compared with the D-K iteration controller (the conventional solution to μ synthesis problem). Simulation results demonstrate the advantages of the proposed controller in terms of simple structure and robustness against plant perturbations and disturbances in comparison with D-K iteration controller.     

Accurate and simple synthesis formulas for coplanar waveguides

Simple and accurate closed‐form formulas obtained by using a differential evolution algorithm are presented for the synthesis of coplanar waveguides (CPW). The results of the synthesis formulas proposed in this article are compared with those of the quasi‐static analysis, the synthesis formulas reported by the other researchers and also the experimental works available in the literature. The accuracy of the proposed synthesis formulas is found to be better than 0.75% for 9256 CPWs samples. © 2008 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2008.     

Asynchronous switching output feedback control of discrete-time switched linear systems

In this paper, the problem of dynamic output-feedback control synthesis is addressed for discrete-time switched linear systems under asynchronous switching. The proposed hybrid controller consists of a standard dynamic output-feedback switching control law and an impulsive reset law induced by controller state jumps. Using the average dwell time technique incorporating with multiple quadratic Lyapunov functions, the switching control synthesis conditions for asymptotic stability with guaranteed weighted ?₂-gain performance are derived as a set of linear matrix inequalities (LMIs). The proposed hybrid synthesis scheme advances existing design methods for output-feedback asynchronous switching control of switched linear systems in two important aspects: LMI formulation of the synthesis problem; and arbitrary order of the controller state. A numerical example is used to illustrate the effectiveness and advantages of the proposed design technique.     

面向藏语语音合成的语音基元自动标注方法

在基于隐Markov模型（Hidden Markov Model,HMM）的统计参数藏语语音合成中引入了DAEM（Deterministic Annealing EM）算法,对没有时间标注的藏语训练语音进行自动时间标注。以声母和韵母为合成基元,在声母和韵母的声学模型的训练过程中,利用DAEM算法确定HMM模型的嵌入式重估的最佳参数。训练好声学模型后,再利用强制对齐自动获得声母和韵母的时间标注。实验结果表明,该方法对声母和韵母的时间标注接近手工标注的结果。对合成的藏语语音进行主观评测表明,该方法合成的藏语语音和手工标注声、韵母时间的方法合成的藏语语音的音质接近。因此,利用该方法可以在不需要声、韵母的时间标注的情况下建立合成基元的声学模型。     

Phase‐only synthesis of planar arrays using autocorrelation matching method

Autocorrelation matching method is proposed for phase‐only synthesis of power pattern of planar antenna arrays. This method is based on equating the autocorrelation coefficients of a planar array having a specified amplitude of excitations to those of a conventionally designed planar array. The effectiveness of the proposed method is verified by synthesis of pencil‐beam and flat‐top patterns.     

基于微粒群算法的纹理合成图像修补方法

提出了一种基于微粒群算法（PSO）的纹理合成图像修补方法。针对基于块的纹理合成算法中常用的匹配块全搜索效率低下的问题,对候选区域采样确定初始微粒,利用PSO算法搜索得到最优匹配块。实验结果表明了方法的有效性。     

Depth-optimized reversible circuit synthesis

In this paper, simultaneous reduction of circuit depth and synthesis cost of reversible circuits in quantum technologies with limited interaction is addressed. We developed a cycle-based synthesis algorithm which uses negative controls and limited distance between gate lines. To improve circuit depth, a new parallel structure is introduced in which before synthesis a set of disjoint cycles are extracted from the input specification and distributed into some subsets. The cycles of each subset are synthesized independently on different sets of ancillae. Accordingly, each disjoint set can be synthesized by different synthesis methods. Our analysis shows that the best worst-case synthesis cost of reversible circuits in the linear nearest neighbor architecture is improved by the proposed approach. Our experimental results reveal the effectiveness of the proposed approach to reduce cost and circuit depth for several benchmarks.