Genetic algorithms have been shown to be very useful in a variety of search and optimization problems. In this paper we present a genetic algorithm for maximum independent set problem. We adopt a permutation encoding with a greedy decoding to solve the problem. The DIMACS benchmark graphs are used to test our algorithm. For most graphs solutions found by our algorithm are optimal, and there are also a few exceptions that solutions found by the algorithm are almost as large as maximum clique sizes. We also compare our algorithm with a hybrid genetic algorithm, called GMCA, and one of the best existing maximum clique algorithms, called CBH. The exiperimental results show that our algorithm outperformed two of the best approaches by GMCA and CBH in final solutions.

The concept of a basis matrix is introduced to investigate the trade-off between complexity and storage for multiplication in a finite field. The effect on the storage requirements of using polynomial and normal bases for element representation is also considered.

The Virtual Path (VP) concept is one of the versatile features of ATM/B-ISDN. Using the VP concept, a bundle of virtual circuits can be grouped together between any two switching nodes in the network. Further, the VP bandwidth and routing can be dynamic. Building on this idea, a dynamically reconfigurable, dynamic call routing wide area (backbone) broadband network concept is proposed. Specifically, this provides dynamism at two levels: at the VP level and at the connection level. For an incoming connection request, at most two logical virtual path connections (VPCs) are allowed between the origin and the destination; these logical VPCs are defined by setting virtual paths links (VPLs) which are, in turn, physically mapped to the transmission network. Based on the traffic pattern during the day, the bandwidth of such VPCs and their routing, as well as call routing, changes so that the maximum number of connection requests can be granted while maintaining acceptable quality of service (QoS) for various services. Within this framework, we present a mathematical model for network design (dimensioning) taking into account the variation of traffic during the day in a heterogeneous multi-service environment. We present computational results for various cost parameter values to show the effectiveness of such networks compared to static-VP based networks in terms of network cost.

This paper presents algorithms for computing the Minkowski sum of two polygons P and Q for a family of problems. For P being convex and Q being monotone, an algorithm is given with O (nm) time and space complexity. For both P and Q being monotone polygons, an O (nm log nm) time algorithm is presented and it is shown that the complexity of the sum is Θ (nmα(min(n,m))) in the worst case, where α() is the inverse of Ackermann's function. Finally, an O ((nm+k)log nm) time complexity algorithm is given when P is monotone and Q is simple, where k in the worst case could be Θ(n2m). The complexity of P Q is shown to be Θ(n2m) in the worst case. Here, m and n denote the number of edges of P and Q, respectively.

A new structure for adaptive AR spectral estimation based on multi-band decomposition of the linear prediction error is introduced and the mathematical background for the soulution of the related adaptive filtering problem is derived. The presented structure gives rise to AR spectral estimates that represent the true underlying spectrum with better fidelity than conventional LS methods by allowing an arbitrary trade-off between variance of spectral estimates and tracking ability of the estimator along the frequency spectrum. The linear prediction error is decomposed through a filter bank and components of each band are analyzed by different window lengths, allowing long windows to track slowly varying signals and short windows to observe fastly varying components. The correlation matrix of the input signal is shown to satisfy both time-update and order-update properties for rectangular windowing functions, and an RLS algorithm based on each property is presented. Adaptive forward and backward relations are used to derive a mathematical framework that serves as a basis for the design of fast RLS alogorithms. Also, computer experiments comparing the performance of conventional and the proposed multi-band methods are depicted and discussed.

In this paper, we introduce a parallel algorithm for parsing context-free languages. Our algorithm can handle arbitrary context-free grammars since it is based on Earley's algorithm. Our algorithm can operate on any loosely coupled multiprocessor which can provide a topology of a one-way ring. Our algorithm uses p processors to parse an input string of length n where 1 p n. It is shown that our algorithm requires O(n3/p) time. The algorithm uses a simple job allocation strategy. However, it achieves high load balancing and uses the processors efficiently.

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.

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.

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.

This paper presents an O(mn log n) time algorithm for an approximate string matching problem, in which a pattern string may contain variable length don't care characters. This problem is important for searching DNA sequences or amino acid sequences.

Efficient parallel algorithms for several problems on proper circular arc graphs are presented in this paper. These problems include finding a maximum matching, partitioning into a minimum number of induced subgraphs each of which has a Hamiltonian cycle (path), partitioning into induced subgraphs each of which has a Hamiltonian cycle (path) with at least k vertices for a given k, and adding a minimum number of edges to make the graph contain a Hamiltonian cycle (path). It is shown here that the above problems can all be solved in logarithmic time with a linear number of EREW PRAM processors, or in constant time with a linear number of BSR processors. A more important part of this work is perhaps the extension of basic BSR to allow simultaneous multiple BROADCAST instructions.

This paper discusses a massively parallel interconnection scheme for multithreaded architecture and introduces a new class of direct interconnection networks called the hierarchical Multidimensional Directed Cycles Ensemble (hMDCE). Its suitability for massively parallel systems is discussed. The network is evolved from the Multidimensional Directed Cycles Ensemble (MDCE) network, where each node is substituted by lower-level sub-networks. The new network addresses some serious problems caused by the increasing scale of parallel systems, such as longer latency, limited throughput and high implementation cost. This paper first introduces the MDCE network and then presents and examines in detail the hierarchical MDCE network. Bisection bandwidth of hMDCE is considerably reduced from its ancestor MDCE and the network performs significantly higher throughput and lower latency under some practical implementation constraints. The gate count and delay time of the compiled circuit for the routing function are insignificant. These results reveal that the hMDCE network is an important candidate for massively parallel systems interconnection.

High-resolution algorithms for the detection and estimation of Directions Of Arrival (DOA) such as MUSIC, lead to accurate results but require the computation of the noise-subspace through an expensive covariance matrix eigendecomposition. Adaptive estimators of the noise-subspace can be very useful in a non-stationary environment when the convergence is possible with a few number of snapshots. Some adaptive methods are presented showing that an indirect noise-subspace estimation through a signal subspace estimation can be advantageous both in terms of convergence rate and computation complexity during each update. Some computer simulations examples showing performances are provided.

This paper presents a method for mechanically transforming a parallel algorithm on an original network so that the algorithm can work on a target network. It is assumed that the networks are of cube-type such as the shuffle-exchange network, omega network, and hypercube. Were those networks isomorphic to each other, the algorithm transformation is an easy task. The proposed transformation method is based on a novel graphembedding scheme <φ: δ, κ, π, ψ>. In addition to the dilating operation δ of the usual embedding scheme <φ: δ>, the novel scheme uses three primitive graph-transformation operations; κ (= δ-1) for contracting a path into a node, π for pipelining a graph, and ψ (= π-1) for folding a pipelined graph. By applying the primitive operations, the cube-type networks can be transformed so as to be isomorphic to each other. Relationships between the networks are represented by the composition of applied operations. With the isomorphic mapping φ, an algorithm in a node of the original network can be simulated in the corresponding node(s) of the target network. Thus the algorithm transformation is reduced to routine work.

In this paper, we study the following node-to-node and node-to-set routing problems in r-dimensional torus Trn with r 2 and n 4 nodes in each dimension: given at most 2r - 1 faulty nodes and non-faulty nodes s and t in Trn, find a fault-free path s t; and given at most 2r - k faulty nodes and non-faulty nodes s and t1,..., tk in Trn, find k fault-free node-disjoint paths s ti, 1 i k. We give an O(r2) time algorithm which finds a fault-free path s t of length at most d(Trn) + 1 for the node-to-node routing, where d(Trn) is the diameter of Trn. For node-to-set routing, we show an O(r3) time algorithm which finds k fault-free node-disjoint paths s ti, 1 i k, of length at most d(Trn) + 1. The upper bounds on the length of the found paths are optimal. From this, Rabin diameter of Trn is d(Trn) + 1.

A new adaptive AR spectral estimation method is proposed. While conventional least-squares methods use a single windowing function to analyze the linear prediction error, the proposed method uses a different window for each frequency band of the linear prediction error to define a cost function to be meinemized. With this approach, since time and frequency resolutions can be traded off throughout the frequency spectrum, an improvement on the precision of the estimates is achieved. In this paper, a wavelet-like time-frequency resolution grid is used so that low-frequency components of the linear prediction error are analyzed through long windows and high-frequency components are analyzed through short ones. To solve the optimization problem for the new cost function, special properties of the correlation matrix are used to derive an RLS algorithm on the order of M2, where M is the number of parameters of the AR model. Computer simulations comparing the performance of conventional RLS and the proposed methods are shown. In particular, it can be observed that the wavelet-based spectral estimation method gives fine frequency resolution at low frequencies and sharp time resolution at high frequencies, while with conventional methods it is possible to obtain only one of these characteristics.

This paper proposes a mutual exclusion method that is unified for the parallel and distributed systems. The method partially serializes requests into partial queues of requests, which are next totally serialized into a main queue. A request in the main queue is authorized to enter the critical section (CS) when the request receives the privilege token from the previous request in the queue. In the distributed system of N sites that each is a parallel system, mutual exclusion is performed by cooperation of two algorithms based on the same method. The algorithm for the distributed system works on a logical network (that is a directed tree) of S ( N) sites. The algorithm for each site produces a local-main queue of requests. The chunk of requests in the local queue is concatenated at a time to the partial queue of the distributed system. The the cost of mutual exclusion -- the number of intersite messages required per CS entry -- is reduced to O(1) (between 0 and 3).

In this paper, we give an algorithm which, given a set F of at most n-k faulty nodes, and two sets S={s1, , sk} and T = {t1,, tk}, 1kn, of non-faulty nodes in n-dimensional hypercubes Hn, finds k fault-tree node disjoint paths sitje, where (j1, , Jk) is a permutation of (1, , k), of length at most n + k in O(kn log k) time. The result of this paper implies that n disjoint paths of length at most 2n for set-to-set node disjoint path problem in Hn can be found in O(n2 log n) time.

Mathematical morphology is inheriently suitable for range image processing because it can deal with the shape of a function in a natural and intuitive way. In this paper, a new approach to the extraction of the corner-edge-surface structure from 3D range images is proposed. Morphological operations are utilized for segmenting range images into smooth surface regions and high-variation surface regions, where the high-variation surface regions are further segmented into regions of edge type and regions of corner type. A new 3D feature, HV-skeleton, can be extracted for each high-variation surface region. The HV-skeletons can be thought of as the skeletons of high-variation surface regions and are useful for feature matching. The 3D features extracted by our approach are invariant to 3D translations and rotations, and can be utilized for higher-level vision tasks such as registration and recognition. Experimental results show that the new 3D feature extraction method works well for both simple geometric objects and complex shaped objects such as human faces.

In this paper, we present a vision system for a depalletizing robot which recognizes carton objects. The algorithm consists of the extraction of object candidates and a labeling process to determine whether or not they actually exist. We consider this labeling a combinatorial optimization of labels, we propose a new labeling method applying Genetic Algorithm (GA). GA is an effective optimization method, but it has been inapplicable to real industrial systems because of its processing time and difficulty of finding the global optimum solution. We have solved these problems by using the following guidelines for designing GA: (1) encoding high-level information to chromosomes, such as the existence of object candidates; (2) proposing effective coding method and genetic operations based on the building block hypothesis; and (3) preparing a support procedure in the vision system for compensating for the mis-recognition caused by the pseudo optimum solution in labeling. Here, the hypothesis says that a better solution can be generated by combining parts of good solutions. In our problem, it is expected that a global desirable image interpretation can be obtained by combining subimages interpreted consistently. Through real image experiments, we have proven that the reliability of the vision system we have proposed is more than 98% and the recognition speed is 5 seconds/image, which is practical enough for the real-time robot task.