A multilevel systolic approach for fuzzy inference hardware

Our digital fuzzy processor's main features are high throughput, performance independent of fuzzy-model size, high design parameter flexibility, Max-Min inference, and ability to handle a large number of complex rules without loss of efficiency. We carried out circuit development using a VHDL simulator, with European Silicon Structures' 1-μm standard cells. We have achieved performance results of over 10-million fuzzy logical inferences per second     

A novel approach for multistage inference fuzzy control

This paper presents a methodology to the design of a multistage inference fuzzy controller in which the consequence in an inference stage is passed to the next stage as fact, and so forth. A new general method which is based on a performance index of the control system is used to generate fuzzy rule bases for the multistage inference. This proposed method can reduce the design cycle time. In order to reduce the computation time, a method for precomputing the match-degrees of fuzzy values is adopted. Thus, the number of operations that must be carried out at execution time can be significantly reduced. The new method has been applied to two applications, a two-trailer-and-truck system and a three-trailer-and-truck system. The simulation studies showed that the proposed method is feasible.     

An algorithmic approach to group decision making problems under fuzzy and dynamic environment

Our paper introduces a new methodology to solve group decision-making problems under fuzzy and dynamic environment. The methodology takes group members’ linguistically defined pair wise preferences of alternatives in different time intervals and aggregates them across the intervals to obtain each member's net preference levels. Each member's net preference levels are again aggregated across the members to obtain the group's preference. Our paper attaches higher importance to the members whose involvement in the decision process is more recent than the members who opined their views in the past. The fuzzy aggregation operator, IOWA (Induced Ordered Weighted Average) is used to aggregate their views in accordance to their importance in the group. The Ranked_List algorithm, introduced in our paper, inputs the aggregated views of the members in pair wise form and produces the set of sequences of ranked list of alternatives representing the group's consensus view as output. The Ranked_List algorithm is validated and analyzed through a series of synthetic data sets and its results are compared with a movie selection case study. The methodology is illustrated with a numerical example.     

An algorithmic approach to resolutions

We provide an algorithmic method for constructing projective resolutions of modules over quotients of path algebras. This algorithm is modified to construct minimal projective resolutions of linear modules over Koszul algebras.     

模糊推理的函数变换观点

基于函数论的立场 ,指出模糊推理过程是一个函数变换过程 ,模糊规则蕴涵了一个从函数空间到函数空间的映射 ,现存的种种模糊推理方法都是对这种映射的估计 ,进而指出插值和回归的方法都适用于这种估计。系统地提出了用回归的方法处理模糊推理的思想 ,并结合线性回归模型进行了示范 ,证明了基于线性回归模型的模糊推理系统 (FIS)同样是一个万能函数逼近器。     

An algorithmic approach to coordinate transformation for robotic manipulators

Coordinate transformation is one of the most important issues in robotic manipulator control. Robot tasks are naturally specified in work space coordinates, usually a Cartesian frame, while control actions are developed on joint coordinates. Effective inverse kinematic solutions are analytical in nature; they exist only for special manipulator geometries and geometric intuition is usually required. Computational inverse kinematic algorithms have recently been proposed; they are based on general closed-loop schemes which perform the mapping of the desired Cartesian trajectory into the corresponding joint trajectory. The aim of this paper is to propose an effective computational scheme to the inverse kinematic problem for manipulators with spherical wrists. First an insight into the formulation of kinematics is given in order to detail the general scheme for this specific class of manipulators. Algorithm convergence is then ensured by means of the Lyapunov direct method. The resulting algorithm is based on the hand position and orientation vectors usually adopted to describe motion in the task space. The analysis of the computational burden is performed by taking the Stanford arm as a reference. Finally a case study is developed via numerical simulations.     

A fuzzy inference approach to template-based visual tracking

The tracking of visual features using appearance models is a well studied but still open area of computer vision. In the absence of knowledge about the structural constraints of the tracked object, the validity of the model can be compromised if only appearance information is used. We propose a fuzzy inference scheme that can be used to selectively update a given template-based model in tracking tasks. This allows us to track moving objects under translation, rotation, and scale changes with minimal feature drift. Moreover, no rigidity constraint needs to be enforced on the moving target. Some experiments have been performed using several targets, and the results are very close to the ground truth paths. The computational cost of our approach is low enough to allow its application in real-time tracking using modest hardware requirements.     

An algorithmic approach to combining belief functions

Methods of combination are used to synthesize pieces of evidence of equal standing that represent different aspects of a specific system about which a diagnosis is to be made. Combination is distinct from consensus, when complete diagnoses rendered by different knowledge sources require synthesis, and conditionalization, where pieces of evidence to be synthesized have dissymmetric relationships to each other. The Dempster-Shafer Rule is the quintessential combination method. However, it has been criticized for its inability to handle inconsistent pieces of evidence and for the way it focuses the weight of evidence. This article presents an alternative combination method that is capable of handling inconsistent evidence and relates evidence focusing to the amount of information resident in pieces of evidence. The method is capable of combining belief functions. Future research should address extending the method to the combination of a broad class of imprecise probability functions. © 1996 John Wiley & Sons, Inc.     

PGMA: An algorithmic approach for multi-objective hardware software partitioning

Designing embedded systems efficiently has always been of significant interest. This has been tremendously scaled-up for contemporary and high-end applications with their increasing complexity and the need to satisfy multiple conflicting constraints. This paper presents a high-speed Hardware Software Partitioning technique for the design of such systems. The partitioning problem has been modeled as a multi-dimensional optimization problem with the aim of minimizing the area utilization, power dissipation, time of execution and system memory requirement of the implementation. A two-phased algorithm (Phased Greedy Metaheuristic Algorithm or PGMA) has been proposed which also takes into consideration the communication costs between hardware and software Processing-Engines (PEs) while partitioning. Subsequently, a detailed empirical analysis of the proposed algorithm is presented to ascertain its efficiency, quality and speed. The execution time is as low as 18 ms for partitioning an algorithm consisting of 1000 blocks. Thereafter, the proposed algorithm is applied to a real-life embedded system, the Joint Photographic Expert-Group (JPEG) Encoder, to demonstrate its effectiveness. For a power constraint of 600 mW, an area utilization of 58.28% has been achieved, which is the maximum amongst all the reported works till date, to the best of our knowledge. This allowed for a decreased offloading of tasks to software, resulting in a memory usage of only 14 KB and execution time of 20 ms.     

复合二维模糊控制器及其模糊推理方法的研究

实现三维模糊控制效果, 而控制规则数与二维模糊控制器相当. 模糊控制规则解析生成. 模糊推理方法基于相平面, 计算量小, 直接用输入连续量进行推理. 该控制器结构及算法简单, 易于在线实现, 具有通用性. 将其用于交流调速系统, 实验结果表明控制性能较PI算法更佳.     

An algorithmic approach to discovering and provingq-series identities

An algorithmic method of producingq-series identities from any given power series is discassed. This recursive technique is then used to give new proofs of several classicalq-identities of Gauss and Rogers. Dedicated to the memory of John Knopfmacher, 1937–1999, the inventor of the Engel expansions for q-series. The first author was partially supported by National Science Foundation Grant DMS-9206993 and by The Centre for Applicable Analysis and Number Theory of the University of the Witwatersrand. He wishes to express his gratitude to the second author who provided the hospitality and support which made his participation possible This paper was presented at the fourth International Conference on Average-Case Analysis of Algorithms, Princeton, NJ, by the second author. Online publication September 6, 2000.     

From inductive inference to algorithmic learning theory

We present two phenomena which were discovered in pure recursion-theoretic inductive inference, namely inconsistent learning (learing strategies producing apparently “senseless” hypotheses can solve problems unsolvable by “reasonable” learning strategies) and learning from good examples (“much less” information can lead to much more learning power). Recently, it has been shown that these phenomena also hold in the world of polynomial-time algorithmic learning. Thus inductive inference can be understood and used as a source of potent ideas guiding both research and applications in algorithmic learning theory.     

Integrated fuzzy logic and genetic algorithmic approach for simultaneous localization and mapping of mobile robots

This paper presents a novel method of integrating fuzzy logic (FL) and genetic algorithm (GA) to solve the simultaneous localization and mapping (SLAM) problem of mobile robots. The core of the proposed SLAM algorithm is based on an island model GA (IGA) which searches for the most probable map(s) such that the associated pose(s) provides the robot with the best localization information. Prior knowledge about the problem domain is transferred to GA in order to speed up the convergence. Fuzzy logic is employed to serve this purpose and allows the IGA to conduct the search starting from a potential region of the pose space. The underlying fuzzy mapping rules infer the uncertainty in the robot's location after executing a motion command and generate a sample-based prediction of its current position. This sample set is used as the initial population for the proposed IGA. Thus the GA-based search starts with adequate knowledge on the problem domain. The correspondence problem in SLAM is solved by exploiting the property of natural selection, which supports better performing individuals to survive in the competition. The proposed algorithm follows essentially no assumption about the environment and has the capacity to resolve the loop closure problem without maintaining explicit loop closure heuristics. The algorithm processes sensor data incrementally and therefore, has the capability of real time map generation. Experimental results in different indoor environments are presented to validate robustness of the algorithm.     

Fuzzy inference and fuzzy inference processor

Fuzzy inference, a data processing method based on the fuzzy theory that has found wide use in the control field, is reviewed. Consumer electronics, which accounts for most current applications of this concept, does not require very high speeds. Although software running on a conventional microprocessor can perform these inferences, high-speed control applications require much greater speeds. A fuzzy inference date processor that operates at 200000 fuzzy logic inferences per second and features 12-b input and 16-b output resolution is described     

Generalized approach for model algorithmic control

This paper considers the development of a general model algorithmic control (MAC). It is shown that the proposed structure contains all the features and principles of MAC. The scheme developed allows choices of prediction and reference trajectories. The regulation effect is studied and non-minimum phase systems are also exemplified. The tracking and regulation properties of the proposed MAC depend on the choice of regulator and controller parameters. Results of simulation studies indicate the effectiveness of the developed algorithmic control.     

直觉F推理与普通F推理的比较研究

直觉F推理克服了普通F推理在不确定性信息的描述、推理结果可信性等方面存在的局限性。在介绍普通F推理直觉化扩展的基础上,首先分析了两类推理算法的相互转化问题,指出普通F推理是直觉F推理的一种特例,当直觉指数为0时二者可相互转化。其次,比较了两类算法的还原性,分析表明Zadeh型、Mamdani型、Larsen型直觉F推理算法与其对应的普通F推理算法具有相同的还原性。最后,通过实例研究了直觉F推理算法在推理结果精度、可信性上的优势,从而较普通F推理更适用于智能控制与决策。     

An approach for ranking of fuzzy numbers

In order to rank all fuzzy numbers, we modify the method of “a new approach for ranking of trapezoidal fuzzy numbers” by Abbasbandy and Hajjari (2009). Our proposed method is used for ranking symmetric fuzzy numbers. The advantage of this method is illustrated by some comparative examples.     

Algebraic solutions of holomorphic foliations: An algorithmic approach

We present two algorithms that can be used to check whether a given holomorphic foliation of the projective plane has an algebraic solution, and discuss the performance of their implementations in the computer algebra system Singular.     

An algorithmic approach for analysis of finite-source retrial systems with unreliable servers

This paper aims at presenting an approach for analyzing finite-source retrial systems with servers subject to breakdowns and repairs, using Generalized Stochastic Petri Nets (GSPNs). This high-level formalism allows a simple representation of such systems with different breakdown disciplines. From the GSPN model, a Continuous Time Markov Chain (CTMC) can be automatically derived. However, for multiserver retrial systems with unreliable servers, the models may have a huge state space. Using the GSPN model as a support, we propose an algorithm for directly computing the infinitesimal generator of the CTMC without generating the reachability graph. In addition, we develop the formulas of the main stationary performance and reliability indices, as a function of the number of servers, the size of the customer source and the stationary probabilities. Through numerical examples, we discuss the effect of the system parameters and the breakdown disciplines on performance.     

An innovative approach for bond strength modeling in FRP strip-to-concrete joints using adaptive neuro–fuzzy inference system

Engineering with Computers - In this study, a new computational approach for determination of the bond strength of fibre reinforced polymer (FRP) strip-to-concrete joints is presented based on...