In this paper we present an efficient method to solve reachability problems for Petri nets based on genetic algorithms and a kind of random search which is called postpone search. Genetic algorithm is one of algorithms developed for solving several problems of optimization. We apply GAs and postpone search to approximately solving reachability problems. This approach can not determine exact solutions, however, from applicability points of view, does not directly face state space explosion problems and can extend class of Petri nets to deal with very large state space in reasonable time. First we describe how to represent reachability problems on each of GAs and postpone search. We suppose the existence of a nonnegative parickh vector which satisfies the necessary reachability condition. Possible firing sequences of transitions induced by the parickh vector is encoded on GAs. We also define fitness function to solve reachability problems. Reachability problems can be interpreted as an optimization ones on GAs. Next we introduce random reachability problems which are capable of handling state space and the number of firing sequences which enable to reach a target marking from an initial marking. State space and the number of firing sequences are considered as factors which effect on the hardness of reachability problems to solve with stochastic methods. Furthermore, by using those random reachability problems and well known dining philosophers problems as benchmark problems, we compare GAs' performance with the performance of postpone search. Finally we present empirical results that GAa is more useful method than postpone search for solving more harder reachability problems from the both points of view; reliability and efficiency.

A siphon (or alternatively a structutal deadlock) of a Petri net is defined as a set S of places such that existence of any edge from a transition t to a place of S implies that there is an edge from some place of S to t. A minimal siphon is a siphon such that any proper subset is not a siphon. The results of the paper are as follows. (1) The problem of deciding whether or not a given Petri net has a minimum siphon (i.e., a minimum-cardinality minimal siphon) is NP-complete. (2) A polynomial-time algorithm to find, if any, a minimal siphon or even a maximal calss of mutually disjoint minimal siphons of a general Petri net is proposed.

A hardware algorithm for modular division is proposed. It is based on the extended Euclidean algorithm (EEA). The procedure for finding the multiplicative inverse in EEA is modified so that it calculates the quotient. Modular division is carried out through iteration of simple operations, such as shifts and additions. A redundant binary representation is employed so that additions are performed without carry propagation. An n-bit modular division is carried out in O(n) clock cycles. The length of each clock cycle is constant independent of n. A modular divider based on the algorithm has a bit-slice structure and is suitable for VLSI implementation.

The paper deals with Kleenean functions defined as fuzzy logic functions with constants. Kleenean functions provide a means of handling conditions of indeterminate truth value (ambiguous states) which ordinary classical logic (binary logic) cannot cope with. This paper clarifies a necessary and sufficient condition for a function to be a Kleenean function. The condition is provided with a set of two conditions, and it will be shown that they are independent of each other.

In this paper, we propose the distributed stable marriage problem and apply it to planning for cooperative works of autonomous mobile robots and battery charger stations. We develop and analyze a distributed algorithm to determine the partner by message communication.

A minimal siphon (or alternatively a structural deadlock) of a Petri net is defined as a minimal set S of places such that existence of any edge from a transition t to a place of S implies that there is an edge from some place of S to t. The subject of the paper is to find a minimal siphon containing a given set of specified places of a general Petri net.

In this paper, we propose a new design algorithm for nearly linear phase IIR digital filters with prescribed log magnitude response. The error function used here is the sum of the weighted log magnitude-squared error and phase -squared error, and so it is possible to control log magnitude and phase response directly. The gradient vector of the proposed error function is easily calculated as the closed form solution because of its nature, in which the real and imaginary part of the logarithm of a complex transfer transfer function corresponds to the log magnitude and phase response, respectively. This algorithm is simple and converges quickly. Finally, we show the validity of the proposed algorithm with some examples.

This paper describes a new region segmentation method which is detectable carcinoma regions from hematoxylin and eosin (HE)-stained breast tumor images using collective behaviors of artificial organisms. In this model, the movement characteristics of artificial organisms are controlled by the gene, and the adaptive behavior of artificial organisms in the environment, carcinoma regions or not, is evaluated by the texture features.

The join operation is one of the most expensive operations in relational database systems. So far many researchers have proposed several hash-based algorithms for the join operation. In a hash-based algorithm, a large relation is first partitioned into several clusters. When clusters overflow, that is, when the size of the cluster exceeds the size of main memory, the performance of hash-based algorithms degrade substantially. Previously we proposed the GN hash algorithm which is robust in the presence of overflown clusters. The GN hash join algorithm combines the Grace hash join and hash-based nested-loop join algorithms. We analyze the performance of the GN hash join algorithm when applied to relations with a non-uniform Zipf-like data distribution. The performance is compared with other hash-based join algorithms: Grace, Hybrid, nested-loop, and simple hash join. The GN hash join algorithm is found to have higher performance on non-uniformly distributed relations. In this paper, the robustness of the GN hash algorithm from the point of choosing a run time method is verified. In the GN hash algorithm, the criterion for selecting a run time method from the two algorithm is determined by using the value calculated from the I/O cost formula of the two algorithms. This criterion cannot be guaranteed to be optimal under every data distribution, that is, the optimal criterion may change depending on the data distribution. When the data distribution is unknown, all data has to be repartitioned in order to get an accurate optimal criterion. However, from the view of choosing a method at run time, it is necessary for the GN hash algorithm to determine an appropriate criterion regardless of the data distribution. Thus, we inspect the criterion adopted in our algorithm under a simulation environment. From simulation results, we find that the range of the criterion is very wide under any data distribution and assure that the criterion determined with the assumption of a uniform data distribution can be used even when the data is highly skewed. Consequently, we can conclude that the GN hash algorithm which dynamically selects the nested-loop and Grace hash algorithms provides good performance in the presence of data skew and its performance is not sensitive to the criterion.

For reduction of computational complexity in the IA algorithm, the thinned-out IA algorithm in which only one step size is updated every iteration is proposed and is complementarily switched with the HA algorithm according to the convergence. The switching is determined by using the gradient of the error signal power. These are investigated through the computer simulations.

This paper describes an adaptive neural vector quantization algorithm with a deleting approach of weight (reference) vectors. We call the algorithm an adaptive learning and self-deleting algorithm. At the beginning, we introduce an improved topological neighborhood and an adaptive vector quantization algorithm with little depending on initial values of weight vectors. Then we present the adaptive learning and self-deleting algorithm. The algorithm is represented as the following descriptions: At first, many weight vectors are prepared, and the algorithm is processed with Kohonen's self-organizing feature map. Next, weight vectors are deleted sequentially to the fixed number of them, and the algorithm processed with competitive learning. At the end, we discuss algorithms with neighborhood relations compared with the proposed one. The proposed algorithm is also good in the case of a poor initialization of weight vectors. Experimental results are given to show the effectiveness of the proposed algorithm.

Fairness is one of the important notion for programming language, such as process algebras like CCS, that includes concurrency (or parallelism) and nondeterminism. This ensures that while repeatedly choosing among a set of alternatives, no alternative will be postponed forever. However, the fairness does not mention at what frequency these alternatives are selected. In this paper, we propose a quantitative fairness, which is called economic-oriented fairness, to each alternatives. This fairness ensures that the expected number of selection for each alternatives are same. We give a condition for probability assignment of selection of each alternative to be satisfied for economic-oriented fairness. First we show a simple probability assignment rule. In this assignment, between any two alternatives, if an alternative is selected n times and the other m times then the probability to select the former alternative is (m + 1)/(n + 1) times the probability for the latter. We prove that this assignment satisfies the condition of economic-oriented fairness. For a model of the economic-oriented fairness, we adopt a probabilistic process algebra. Finally, we elaborate with two process models of the economic-oriented fairness. The first one is a server and client model, where each client communicates only with the server, but not among them. In this model, the expected number of communication by each client are equal. The second model considers communication between two processes. In practice, a process has several subprocesses. Each subprocess communicates via a communication port, In the second model, there is economic-oriented fairness where the expected number of communications via each communication port are equal.

In this paper, we propose a novel SPICE oriented steady-state analysis of nonlinear circuits based on the circuit partition technique. Namely, a given circuit is partitioned into the linear and nonlinear subnetworks by the application of the substitution theorem. Each subnetwork is solved using SPICE simulator by the different techniques of AC analysis and transient analysis, respectively, whose steady-state reponse is found by an iteration method. The novel points of our algorithm are as follows: Once the linear subnetworks are solved by AC analysis, each subnetwork is replaced by a simple equivalent RL or RC circuit at each frequency component. On the other hand, the reponse of nonlinear subnetworks are solved by transient analysis. If we assume that the sensitivity circuit is approximated at the DC operational point, the variational value will be also calculated from a simple RL ro RC circuit. Thus, our method is very simple and can be also applied to large scale circuits, effciently. To improve the convergency, we introduce a compensation technique which is usefully applied to stiff circuits containing components such as diodes and transistors.

A method is presented for reconstructing the surface profile of a two dimensional rough surface boundary from the scattered far field data. The proposed inversion algorithm is based on the Kirchhoff approximation and in order to determine the surface profile, the numerical results illustrating the method are presented.

In this paper, we propose a new design method to construct the highly reliable ATM network based on the virtual path (VP) concept. Through our method, we can guarantee a network survivability, by which we mean that connectivity between every pair of two end nodes is assured even after the failure, and that quality of service (QoS) requirements of each VC connection are still satisfied. For achieving a reliable network, every VP connection between two end nodes is equipped with a secondary VP connection such that routes of primary and secondary VPs are established on completely disjoint physical paths. Our primary objective of the current paper is that the construction cost of the VP-based network with such a survivability is minimized while the QoS requirement of traffic sources in fulfilled. For this purpose, after all the routes of VPs are temporarily established by means of the shortest paths, we try to minimize the network cost through (1) the alternation of VP route and (2) the separation of a single VP into several VPs, and optionally through (3) the introduction of VCX nodes. Through numerical examples, we show how the increased cost for the reliable network can be sustained by using our design method.

In this article, a new analogic CNN algorithm to extract features of postage stamps in gray-scale images Is introduced. The Gradient Controlled Diffusion method plays an important role in the approach. In our algorithm, it is used for smoothing and separating Arabic figures drawn with a color which is similar to the background color. We extract Arabic figures in postage stamps by combining Gradient Controlled Diffusion with nearest neighbor linear CNN template and logic operations. Applying the feature extraction algorithm to different test images it has been verified that it is also effective in complex segmentation problems

In the paper a new type of Multilayer Perceptron, developed in Quaternion Algebra, is adopted to realize short-time prediction of chaotic time series. The new introduced neural structure, based on MLP and developed in the hypercomplex quaternion algebra (HMLP) allows accurate results with a decreased network complexity with respect to the real MLP. The short term prediction of various chaotic circuits and systems has been performed, with particular emphasys to the Chua's circuit, the Saito's circuit with hyperchaotic behaviour and the Lorenz system. The accuracy of the prediction is evaluated through a correlation index between the actual predicted terms of the time series. A comparison of the performance obtained with both the real MLP and the hypercomplex one is also reported.

Electronic systems are progressively replacing mechanical devices or human operation for identifying people or objects in everyday-life applications. Especially, the contactless identification systems available today have several advantages, but they cannot handle easily several simultaneously present items. This paper describes a solution to this problem, based on blind source separation techniques. The effectiveness of this approach is experimentally demonstrated, especially by using a real-time DSP-based implementation of the proposed system.

It is shown that most of the binary images of generalized algebraic-geometric codes meet the Varshamov-Gilbert bound from the viewpoint of the average binary weight enumerator.

This paper addresses the problem of estimating 3-D motion of a rigid object from a sequence of monocular 2-D images. The surface of object is assumed to be modeled with several patches, each of which is expressed by an implicit equation. The proposed method estimates the pose (i.e., the location and orientation) of object that corresponds to each image in the sequence: The sequence of the estimated poses gives the motion of the object. The estimation is done by solving a system of equations, each of which is typically an algebraic equation of low degree, that is derived from the expressions of the surface patches and image contours data: so the method does not require establishing the correspondence between successive two frames in the image sequence or computing optic flow. Allowing several-patch models for objects enables the proposed approach to deal with a great variety of objects. The paper includes a numerical example, where our aproach has been applied to a polyhedral object modeled with several patches.