Optimisation of Montgomery modular multiplication algorithm forsystolic arrays

An improved systolic array for the Montgomery modular multiplication algorithm is presented. The recursive equation proposed by Walter [1993] is explicitly transformed into Boolean algebraic equations. By analysing and optimising these equations an improved systolic array can be made 20% faster than that proposed by Walter     

Distributed and cooperative fuzzy controllers for trafficintersections group

This paper presents a fuzzy traffic controller for a set of intersections and its simulation results. The controller of an intersection controls its own traffic and cooperates with its neighbors. It gets information from its traffic detectors and its neighbors. Using this information, the fuzzy rule base system gives optimal signals. It manages phase sequences and phase lengths adaptively to its neighbors' as well as its own traffic conditions. To carry out the performance evaluation of the controller, a simulator for intersection groups has been developed. The proposed method is compared with the vehicle actuated method which is one of the typical conventional methods. The average delay time of a vehicle is used as a performance index. The simulation results show good performance in the case of time-varying traffic patterns and heavy traffic conditions     

Hierarchical reduction and partition of hypergraph

In this paper, a hierarchical reduction method of hypergraphs is proposed. A macro-vertex in a reduced hypergraph corresponds to an edge of the original hypergraph, and thus a reduced hypergraph can provide a partition of a system. The reduction is realized by the iterations and the sequence of hierarchical reduction gives a sequence of hierarchical partitions. The proposed method allows to reduce and decompose the complexity of the system represented by hypergraphs.     

Design and implementation of a fuzzy elevator group control system

Elevator group control systems (EGCSs) are the control systems that systematically manage three or more elevators in order to efficiently transport passengers. Most EGCSs have used the hall call assignment method to assign elevators in response to passengers' calls. This paper proposes a control strategy generation method, a hall call assignment method based on the fuzzy theory, and then the fuzzy elevator group control system (FEGCS). The control strategy of FEGCS is made using the classification of the passenger traffic and system manager's requirements, and the hall calls are assigned to suitable elevators by the generated control strategy. The system is operated using the given control strategy which is defined by the system manager. The proposed system shows better results than the conventional methods in simulations     

High speed flexible fuzzy hardware for fuzzy information processing

In this paper, we present a system called KAFA (Kaist Fuzzy Accelerator) which provides various fuzzy inference methods and fuzzy set operations. The basic idea of this study is to develop a more general purpose hardware system. The architecture has SIMD structure, which consists of two parts; a system control unit (main controller), and an arithmetic unit (fuzzy processing element (FPE)). Microinstruction codes are defined and any fuzzy operation can be programmed by using these microinstructions. Each FPE has the maximum speed of 10 M FLOPS. As the KAFA contains 128 FPE's, if a fuzzy set consists of 128 elements, we achieve the peak performance of 10 M FSOPS (fuzzy set operation per second) under 10 MHz clock frequency. This system also includes the parallel algorithms for defuzzification on the SIMD mode architecture using KAFA network. The prototype of the proposed architecture was developed with the FPGA chips. The speed of the KAFA holds promise for the development of the new fuzzy application system such as automatic control, fuzzy expert systems, real time systems and fuzzy databases     

Fuzzy Inference Neural Network for Fuzzy Model Tuning

In fuzzy modeling, it is relatively easy to manually define rough fuzzy rules for a target system by intuition. It is, however, time-consuming and difficult to fine-tune them to improve their behavior. This paper describes a tuning method for fuzzy models which is applicable regardless of the form of fuzzy rules and the used defuzzification method. For this purpose, this paper proposes a fuzzy neural network model which can embody fuzzy models. The proposed model provides the functions to perform fuzzy inference and to tune the parameters for the shape of antecedent linguistic terms, the relative importance degrees of rules, and the relative importance degrees of antecedent linguistic terms in rules. In addition, to show its applicability, we perform some experiments and present the results     

Hierarchical partition of nonstructured concurrent systems

In this paper, the concepts of structured and nonstructured concurrency are introduced to classify concurrent systems, and a hierarchical partition method is used to handle the complexity of nonstructured concurrent systems. A concurrent system with structured and nonstructured concurrency is modeled by a precedence graph. The language of the precedence graph is defined, and a representation method of the language is developed. By decomposing the language hierarchically, hierarchical partitions of the concurrent system can be obtained. From the partitions, a concurrent system can be reduced hierarchically.     

The SSD graph: a tool for project scheduling and visualization

A graphic tool, the SSD (structure, states and deviation) graph, is proposed for three important phases of project management; planning and scheduling, control, and evaluation. The SSD graph represents the structure, states (scheduled and actual states), and deviation of a system. A project management system using the SSD graph is developed, and it visualizes the actual state of a project and keeps the historical record of the project performance. This system allows a project manager to see the overall status and to review the project performance. Several applications have shown its usefulness for scheduling and control of project systems     

A method for ranking fuzzy numbers and its application todecision-making

Since fuzzy numbers represent uncertain numeric values, it is difficult to rank them according to their magnitude. In the paper, a method for ranking fuzzy numbers is proposed. The method considers the overall possibility distributions of fuzzy numbers in their evaluations for ranking and provides users with a method of changing viewpoints for evaluations. Users represent their viewpoints with fuzzy sets. The method evaluates fuzzy numbers with a satisfaction function and the viewpoint given by users and then ranks the numbers according to their evaluation values. The satisfaction function is a measure of comparisons between fuzzy numbers. In order to illustrate the ranking method, two numeric examples are shown, and for the comparative study, our method is compared with four existing ranking methods through eight examples. As an example of potential applications, the proposed method is applied to a decision-making problem: a two-person game with fuzzy profit and loss. The ranking method is used to analyze player choices