The effectiveness of periodic dispersion compensation on single-channel 40 Gbit/s soliton transmission system was experimentally investigated. This technique requires just the dispersion compensation fibers and wideband optical filters in the transmission line, which has no difficulty to be used in the practical system. By using polarization-division-multiplexing together with periodic dispersion compensation, single-channel 40 Gbit/s transmission over 4700 km was demonstrated. Single-polarization 40 Gbit/s transmission experiments, which are more suitable for system implementation and compatible with WDM were also conducted. We investigated the transmission characteristics and pulse dynamics in different dispersion maps and in the optimized dispersion map, single-channel, single-polarization 40 Gbit/s transmission over 6300 km was successfully demonstrated.

This paper presents an integrated network configuration of wired and wireless access systems for nomadic computing and discusses the virtual LAN on a wireless access system. Furthermore, different types of ad hoc networks are summarized to delineate nomadic computing styles. In terms of user mobility, the integrated network provides a seamless connection environment, so a user can move between wireless and wired networks without dropping data communication sessions. This function is critical for nomadic computing users. By defining the integrated network and employing a virtual LAN, a nomadic computing environment can be realized. This paper reviews the key issues to realize integrated networks. They are mobile management including mobile IP, virtual IP and Logical Office, a high performance MAC, and security control.

The VF (Variable-to-Fixed length) arithmetic coding method combines the advantage of an ordinary stream arithmetic code with the simplicity of a block code. One of the advantages of VF codes is that the transmission errors or channel errors do not propagate infinitely and are restricted to the block in question. In this paper, we propose a modified type of non-proper VF arithmetic coding method that defines an input alphabet subset according to both the number of codewords in the current codeword set and input symbol probability and that splits the codeword set completely for a newly defined alphabet subset when the codeword set becomes smaller by each splitting. The proposed coding method carrys out independence of each codeword and guarantees that there is no collision while there is a waste of codeword(s) in conventional AB-coding due to collision. We examine the performance of the proposed method and compare it with that of other VF codes in terms of compression ratio and algorithmic complexity.

An experiment is reported comparing six pen input strategies for selecting a small target using five diffenent sized targets (1, 3, 5, 7 and 9 dot diameter circles respectively, 0. 36 mm per dot). The results showed that the best strategy, in terms of error rate, selection time and subjective preferences, was the "land-on2" strategy where the target is selected when the pen-tip touches the target for the first time after landing on the screen surface. Moreover, "the smallest maximum size" was determined to be 5 dots (1. 8 mm). This was the largest size among the targets which had a significant main effect on error rate in the six strategies. These results are important for both researchers and designers of pen-based systems.

In this paper, the performances of texture classification based on pyramidal and uniform decomposition are comparatively studied with and without feature selection. This comparison using the subband variance as feature explores the dependence among features. It is shown that the main problem when employing 2-D non-separable wavelet transforms for texture classification is the determination of the suitable features that yields the best classification results. A Max-Max algorithm which is a novel evaluation function based on genetic algorithms is presented to evaluate the classification performance of each subset of selected features. It is shown that the performance with feature selection in which only about half of features are selected is comparable to that without feature selection. Moreover, the discriminatory characteristics of texture spread more in low-pass bands and the features extracted from the pyramidal decomposition are more representative than those from the uniform decomposition. Experimental results have verified the selectivity of the proposed approach and its texture capturing characteristics.

This paper is concerned with a concept called universality or completeness of sets of logic devices. Universality characterizes sets of logic devices which can be used for the construction of arbitrary logic circuits. The elemental universality proposed here is the most general condition of universality which covers logic devices with/without delay time and combinational/sequential circuits. The necessary and sufficient condition of elemental universality shows that nonlinearity and nonmonotonicity are essential conditions for the realization of various digital mechanisms.

A novel approach was proposed to recognize the non-rigid 3D objects from their corresponding 2D images by combining the benefits of the principal component analysis and the geometric hashing. For all of the object models to be recognized, we calculated the statistical point features of the training shapes using principal component analysis. The results of the analysis were a vector of eigenvalues and a matrix of eigenvectors. We calculated invariants of the new shapes that undergone a similarity transformation. Then added these invariants and the label of the model to the model database. To recognize objects, we calculated the necessary invariants from an unknown image and used them as the indexing keys to retrieve any possible matches with the model features from the model database. We hypothesized the existence of an instance of the model in the scene if the model's features scored enough hits on the vote count. This approach allowed us to store the rigid and the non-rigid object models in a model database and utilized them to recognize an instance of model from an unknown image.

This paper describes the wavelength division multiplexing technology for the long-haul optical communication system, especially for the undersea cable system. At first, the present WDM technology for the undersea cable system is reviewed briefly. After that, some experiments using compensation of the dispersion slope of the transmission fiber are discussed as future technical options of undersea systems with over 100 Gbit/s capacity.

In this paper some new results for analog hardware realization of secure communication system using chaos synchronization have been presented. In particular the effect of the use of transmission line as channel has been considered assuming practical implementation. The influence of the loss of transmission line and mismatching on synchronization has been investigated in chaotic systems based on the Pecora-Carroll concept. It has been shown that desynchronization due to loss can be checked by using an amplifier with appropriate gain. Moreover the bit error rate (BER) has been evaluated in a digital communication system based on the principle of chaotic masking.

With the advance of computer technologies, mobile computers can hold many local resources in themselves. In many cases it is impossible to announce local resources on them because almost information announcement systems are not designed for them. In this paper, an information announcement system for mobile computers based on WWW is proposed. The system efficiently announces resources on mobile computers independently of whether they are connected to a network or not, and wherever they are connected. The system can also select suitable announcement methods according to the type of resources. We implement a prototype of proposed system and evaluate it. The result of evaluation confirms effectiveness of the proposed system.

Hogg and Huberman have proposed a strategy for stabilizing chaotic multi-agent systems. This paper applies their strategy to a resource allocation problem in a manufacturing system consisting of two machines and two types of parts. These part-types conflict each other over resource allocation. We introduce a discrete-time model of the system by using game theory, and examine stability and bifurcation phenomena of its fixed point. We show by computer simulation that chaotic behaviors are observed after successive occurrence of period-doubling bifurcations. It is also shown that the optimal state of the system is stabilized by a reward mechanism.

IDDQ testing, or current testing, is a powerful method which detects a large class of defects which cause abnormal quiescent current, by measuring the power supply current. One of the problems on IDDQ testing which prevent its full practical use in manufacturing is that the testing speed is slow owing to time-consuming IDDQ measurement. One of the solutions to this problem is test pattern compaction. This paper presents an efficient method for generating a compact test set for IDDQ testing of bridging faults in combinational CMOS circuits. Our method is based on the iterative improvement method. Each of random primary input patterns is iteratively improved through changing its values pin by pin selected orderly, so as to increase the number of newly detected faults in the current yet undetected fault set. While our method is simple and easy to implement, it is efficient. Experimental results for large ISCAS benchmark circuits demonstrate its efficiency in comparison with results of previous methods.

In multilevel block modulation codes for QPSK and 8-PSK modulation, a construction of binary component codes is given. These codes have a good minimum Euclidean distance by using different forms of the dependency properties of the binary component codes. Interdependency among component codes is formed by using the binary component subcodes which are derived by the coset decomposition of the binary component codes. The algebraic structures of the codes are investigated to find out how interdependency among component codes gives a good minimum Euclidean distance. First, it is shown that cyclic codes over ZM for M-PSK (M=4,8), where the coding scheme is given by Piret, can be constructed by forming specific interdependency among binary component codes for proposed multilevel coding method. Furthermore, it is shown that better minimum Euclidean distance than above can be obtained by modifying the composition of interdependency among binary component codes. These proposed multilevel codes have algebraic structure of additive group and cyclic property over GF(M). Finally, error performances are compared with those of some code's reference modulation scheme for transmitting the same number of information bits.

This paper presents two kinds of simplification methods for incompletely specified sequential machines. The strategy of the methods is that as many states in original machines are covered in the simplification processes as possible. The purpose of the methods is to derive a simplified machine having either the largest maximal compatible set or its subset. With the methods, one of the minimal machines can not be always derived, but a near-minimal machine can be obtained more quickly with less memory, since they need not derive all the compatible sets. In this paper, the effectiveness of the methods is checked by applying them to simplification problems of incompletely specified machines generated by using random numbers, and of the MCNC benchmark machines. The experimental results show that our methods can derive a simplified machine quickly, especially for machines having a great number of states or don't care rate.

Huynen has already provided a method to decompose a Mueller matrix in order to retrieve detailed target information in a polarimetric radar system. However, this decomposition sometimes fails in the presence of small error or noise in the elements of a Mueller matrix. This paper attempts to improve Huynen's decomposition method. First, we give the definition of stable decomposition and present an example, showing a problem of Huynen's approach. Then two methods are proposed to carry out stable decompositions, based on the nonlinear least square method and the Newton's method. Stability means the decomposition is not sensitive to noise. The proposed methods overcomes the problems on the unstable decomposition of Mueller matrix, and provides correct information of a target.

We study the pm-degrees and pT-degrees of immune and bi-immune sets. We demonstrate the existence of incomparable pT-immune degrees in deterministic time classes.

This paper proposes an automatic structural programming system. Genetic Programming achieves success for automatic programming using the evolutionary process. However, the approach doesn't deal with the essential program concept in the sense of what is called a program in software science. It is useful that a program be structured by various sub-structures, i. e. subroutines, however, the above-mentioned approach treats a single program as one sequence. As a result of the above problem, there is a lack of reusability, flexibility, and a decreases in the possibility of use as a utilitarian programming system. In order to realize a structural programming system, this paper proposes a method which can generate a program constructed by subroutines, named formula, using the evolutionary process.

We present experimental results for a structural learning method of feed-forward neural-network classifiers using Principal Component Analysis (PCA) network and Species Genetic Algorithm (SGA). PCA network is used as a means for reducing the number of input units. SGA, a modified GA, is employed for selecting the proper number of hidden units and optimizing the connection links. Experimental results show that the proposed method is a useful tool for choosing an appropriate architecture for high dimensions.

The adaptive associative memory proposed by Ma is used to construct a new model of semantic network, referred to as associative semantic memory (ASM). The main novelty is its computational effectiveness which is an important issue in knowledge representation; the ASM can do inference based on large conceptual hierarchies extremely fast-in time that does not increase with the size of conceptual hierarchies. This performance cannot be realized by any existing systems. In addition, ASM has a simple and easily understandable architecture and is flexible in the sense that modifying knowledge can easily be done using one-shot relearning and the generalization of knowledge is a basic system property. Theoretical analyses are given in general case to guarantee that ASM can flawlessly infer via pattern segmentation and recovery which are the two basic functions that the adaptive associative memory has.

In [1], approximate eigenvalues and eigenvectors are defined and algorithms to compute them are described. However, the algorithms require a certain condition: the eigenvalues of M modulo S are all distinct, where M is a given matrix with polynomial entries and S is a maximal ideal generated by the indeterminate in M. In this paper, we deal with the construction of approximate eigenvalues and eigenvectors when the condition is not satisfied. In this case, powers of approximate eigenvalues and eigenvectors become, in general, fractions. In other words, approximate eigenvalues and eigenvectors are expressed in the form of Puiseux series. We focus on a matrix with univariate polynomial entries and give complete algorithms to compute the approximate eigenvalues and eigenvectors of the matrix.