Signal conservation logic (SCL) is a model of logic for the physical world subject to the matter conservation law. This letter proves that replication, complementary replication, and computational universality called elemental universality are equivalent in SCL. Since intelligence has a close relation to computational universality, the presented theorem may mean that life under the matter conservation law eventually acquires some kind of intelligence.

It is an important problem in signal processing, system realization and system identification to find linear discrete-time systems which are consistent with given covariance parameters. This problem is formulated as a problem of finding discrete-time positive real functions which interpolate given covariance parameters. Among various solutions to the problem, a recent remarkable one is a parameterization of all the discrete-time strictly positive real functions that interpolate the covariance parameters and have a limited McMillan degree. In this paper, we use more general input-output characteristics than covariance parameters and consider finding discrete-time positive real functions which interpolate such characteristics. The input-output characteristics are given by the coefficients of the Taylor series at some complex points in the open unit disk. Based on our previous work, we present an algorithm to generate all the discrete-time positive real functions that interpolate the input-output characteristics and have a limited McMillan degree. The algorithm is more general and simpler than the previous one, and is an important practical supplement to the previous work. Moreover, the interpolation of the general input-output characteristics can be effectively applied to the frequency-weighted model reduction. Hence, the algorithm makes a contribution to the problem from the practical viewpoint as well as the theoretical viewpoint.

For a wireless communication system to work effectively without interference, the electromagnetic environment needs to be controlled. We experimentally and analytically investigated the requirements for controlling the electrical field strength and delay spread so as to achieve the best communication without electromagnetic interference in selected regions for a 2.4-GHz-band wireless LAN system. To control the coverage, partitions were placed around desks in a test environment and covered on the inside with electromagnetic absorbing board from the top of the desks to the top of the partitions; four indoor environments that combined one of two wall-material types and one of two partition heights were used. The transmission loss and delay spread were measured, then calculated using ray tracing to verify the effectiveness of using ray-tracing calculation. The throughput and BER characteristics were measured for the same environments to clarify the requirements for controlling the coverage. We found that covered and uncovered regions could be created by using partitions with absorbing boards and that the delay spread must be less than 15 ns and the received-signal must be stronger than -75 dBm for a region to be covered. We verified that the delay spread can be calculated to within 5 ns and the received-signal level can be calculated to within 5 dB of the measured data by using ray tracing. Therefore, ray tracing can be used to design antenna positions and indoor environments where electromagnetic environments are controlled for 2.4-GHz-band wireless LAN systems.

In the phase locked loop (PLL) frequency synthesizer which is used in a higher frequency region, the prescaler method is employed in order to increase the operating frequency of the programmable divider. However, since the fixed divider whose division ratio is same as the prescaler is installed at the following stage of the reference divider, the reference frequency is decreased and the performance of the PLL frequency synthesizer is degraded. The prescaler PLL frequency synthesizer using multi-programmable divider is one of the counter measures answering the request. In this paper we propose the reduction of the number of programmable dividers by using the (N+1/2) programmable divider. The effectiveness of the proposed method is confirmed by experimental results.

Nonlinear dynamics of xn+1=λ {4xn (1-xn)}q is studied in this paper. Different from the logistic map (q=1), in the case of q

A performance comparison between TCP and UDP in PHS Internet access is made by experiment from a media synchronization point of view. We consider a situation where PHS mobile terminals access H. 263 video and G. 726 audio stored at a media server by a streaming method. PIAFS is adopted as the data link protocol for the PHS wireless channels. We examined how white noise and Rayleigh fading on the PHS channel as well as the Internet traffic affect the performance. For the comparison, we evaluated several performance measures such as the coefficient of variation of output interval, and found that UDP outperforms TCP in almost all cases.

This paper analyzes what structural features of graph problems allow efficient parallel algorithms. We survey some parallel algorithms for typical problems on three kinds of graphs, outerplanar graphs, trapezoid graphs and in-tournament graphs. Our results on the shortest path problem, the longest path problem and the maximum flow problem on outerplanar graphs, the minimum-weight connected dominating set problem and the coloring problem on trapezoid graphs and Hamiltonian path and Hamiltonian cycle problem on in-tournament graphs are adopted as working examples.

Distributed computation has attracted considerable attention and large-scale distributed systems have been designed and developed. A distributed system inherently has possibility of fault tolerance because of its redundancy. Thus, a great deal of investigation has been made to design fault-tolerant distributed algorithms. This paper introduces two promising paradigms, self-stabilization and wait-freedom, for designing fault-tolerant distributed algorithms and discusses some subjects important from the point of view of algorithm engineering.

We sketch two algorithms that solve the undirected st-connectivity problem in a small amount of space. One is due to Nisan, Szemeredy and Wigderson, and takes space O(log3/2n), where n denotes the number of nodes in a give undirected graph. This is the first algorithm that overcame the Savitch barrier on the space complexity of the problem. The other is due to Tarui and this author, and takes space O(sw(G)2 log2 n), where sw(G) denotes the separation-width of a given graph G. Their result implies that the st-connectivity problem can be solved in logarithmic space for any class of graphs with separation-width bounded above by a predetermined constant. This class is one of few nontrivial classes for which the st-connectivity problem can be solved in logarithmic space.

Triangulations have been one of main research topics in computational geometry and have many applications in computer graphics, finite element methods, mesh generation, etc. This paper surveys properties of triangulations in the two- or higher-dimensional spaces. For triangulations of the planar point set, we have a good triangulation, called the Delaunay triangulation, which satisfies several optimality criteria. Based on Delaunay triangulations, many properties of planar triangulations can be shown, and a graph structure can be constructed for all planar triangulations. On the other hand, triangulations in higher dimensions are much more complicated than in planar cases. However, there does exist a subclass of triangulations, called regular triangulations, with nice structure, which is also touched upon.

Given N real weights w1, w2, . . . , wN stored in one-dimensional array, we consider the problem for finding an optimal interval I [1, N] under certain criteria. We shall review efficient algorithms developed for solving such problems under several optimality criteria. This problem can be naturally extended to two-dimensional case. Namely, given a NN two-dimensional array of N2 reals, the problem seeks to find a subregion of the array (e. g. , rectangular subarray R) that optimizes a certain objective function. We shall also review several algorithms for such problems. We shall also mention applications of these problems to region segmentation in image processing and to data mining.

A radiated immunity test method using fields in a three-dimensional Helmholtz-coil set is described. The incident field to equipment under test (EUT) is generated by an orthogonally structured three sets of Helmholtz coil. Using this structure, the resultant field can be generated with arbitrary amplitude and direction. Therefore, the three dimensional immunity characteristics of an EUT can be cleared. The resultant field is calculated numerically and it is established that the field distribution is uniform inside the three dimensional Helmholtz-coil set. This is also confirmed through comparison with measured results. As an example, the immunity test of a cathode ray tube (CRT) display is made and the immunity map of CRT is obtained without reseting placement of EUT. Such map makes us understand the physical meaning and weak points.

In this paper, design and experimental results are described about a newly developed highly flexible fiber Faraday effect current sensor using the flint glass fiber as the sensor element. In the new type, a mirror is coated at an end of the flint glass fiber, and light takes round trip transmission in it. By the round trip transmission, the effect of rotation of polarization plane due to the torsion of the fiber is automatically canceled. Because of the low photo-elastic constant of the flint glass fiber, and the automatic canceling of the rotation, the polarization state of light passed through the fiber is stable. Therefore, in the new reflection type, it is not necessary to support the flint glass fiber with a durable circular frame to maintain accuracy. And so, the sensor head is small, light, and can be easily installed to existing power apparatus by winding the flint glass fiber around the current conductor without pulling out or cutting it. Experiments were done to verify the stable characteristics using the developed sensor model. In the experiments, relation between the final output signal of the sensor and shape of the curve of the flint glass fiber were examined. From the experiments, it became clear that the final output is almost perfectly independent on shape of the curve of the fiber. It was also confirmed that accuracy of the sensor conform to the standard of conventional current transducers for protection of power systems in Japan.

This letter proposes a combined input- and crosspoint-queued (CIC) switch in which virtual output queuing (VOQ) is used at each input port. This CIC switch has a large buffer at each input port and a small buffer at each crosspoint. It does not require high-speed memory access or high-speed internal cell transmission lines. Since the performance of the CIC switch depends on the scheduling algorithms, we propose new scheduling algorithms for the CIC switch. Numerical results show that the mean cell delay time performance of the CIC switch using the proposed scheduling algorithms is better than that of an input-queued ATM switch. In addition, the required buffer size for the CIC switch using the proposed scheduling algorithms is smaller than that for a crosspoint-queued ATM switch.

The Communications Research Laboratory (CRL), the National Astronomical Observatory (NAO), the Institute of Space and Astronoutical Science (ISAS), and the Telecommunication Network Laboratory Group of Nippon Telegraph and Telephone Corporation (NTT) have developed a very-long-baseline-connected-interferometry array, maximum baseline-length was 208 km, using a high-speed asynchronous transfer mode (ATM) network with an AAL1 that corresponds to the constant bit-rate protocol. The very long baseline interferometry (VLBI) observed data is transmitted through a 2.488-Gbps [STM-16/OC-48] ATM network instead of being recorded onto magnetic tape. By combining antennas via a high-speed ATM network, a highly-sensitive virtual (radio) telescope system was realized. The system was composed of two real-time VLBI networks: the Key-Stone-Project (KSP) network of CRL (which is used for measuring crustal deformation in the Tokyo metropolitan area), and the OLIVE (optically linked VLBI experiment) network of NAO and ISAS which is used for astronomy (space-VLBI). These networks operated in cooperation with NTT. In order to realize a virtual telescope, the acquired VLBI data were corrected via the ATM networks and were synthesized using the VLBI technique. The cross-correlation processing and data observation were done simultaneously in this system and radio flares on the weak radio source (HR1099) were detected.

This paper deals with the prediction of stock trends by using the wavelet transform and the multi-stage fuzzy inference system based upon the optimization of membership function by using the GA. The system is expected to recognize the short-term feature which is usually used to estimate the rise/fall of price by human experts. In the prediction of stock prices, the wavelet transform is used to describe the short term feature of the stock trend. The fractal dimension and the variance of the time series are also used as the input variables. By dividing the inference system into multiple stages, the total number of rules is sufficiently depressed compared to the single stage system. In each stage of inference only a portion of input variables are used as the input, and output of the stage is treated as an input to the next stage. To give better performance, the shape of the membership function of the inference rules is optimized by using the GA. Each individual corresponds to an inference system, and its fitness is calculated as the ratio of the correct recognition. In the simulation study, we define the rise and fall of prices by considering the threshold value for the price change, and the interval of prediction. Then, the parameters of the system are adjusted by using the data for learning and the performance is evaluated by comparing the prediction and observation. The simulation study shows that the inference system gives about a 70% correct prediction of the price change of stocks. The result is compared to the prediction by the neural network, and we see better classification of the fuzzy system.

In this paper, an algorithm of the median-cut quantization (MCQ) is proposed. MCQ is the technique that reduces multi-valued samples to binary-valued ones by adaptively taking the median value as the threshold. In this work, the search process of the median value is derived from the quick-sort algorithm. The proposed algorithm searches the median value bit by bit, and samples are quantized during the search process. Firstly, the bit-serial procedure is shown, and then it is modified to the bit-parallel procedure. The extension to the multi-level quantization is also discussed. Since the proposed algorithm is based on bit operations, it is suitable for hardware implementation. Thus, its hardware architecture is also proposed. To verify the significance, for the application to the motion estimation, the performance is estimated from the synthesis result of the VHDL model.

As the nonlinear adaptive filter, the neural filter is utilized to process the nonlinear signal and/or system. However, the neural filter requires large number of iterations for convergence. This letter presents a new structure of the multi-layer neural filter where the orthonormal transform is introduced into all inter-layers to accelerate the convergence speed. The proposed structure is called the transform domain neural filter (TDNF) for convenience. The weights are basically updated by the Back-Propagation (BP) algorithm but it must be modified since the error back-propagates through the orthogonal transform. Moreover, the variable step size which is normalized by the transformed signal power is introduced into the BP algorithm to realize the orthonormal transform. Through the computer simulation, it is confirmed that the introduction of the orthonormal transform is effective for speedup of convergence in the neural filter.

Recently, researchers in various fields have shown interest in the behavior of creatures from the viewpoint of adaptiveness and flexibility. Ants, known as social insects, exhibit collective behavior in performing tasks that can not be carried out by an individual ant. In ant colonies, chemical substances, called pheromones, are used as a way to communicate important information on global behavior. For example, ants looking for food lay the way back to their nest with a specific type of pheromone. Other ants can follow the pheromone trail and find their way to baits efficiently. In 1991, Colorni et al. proposed the ant algorithm for Traveling Salesman Problems (TSPs) by using the analogy of such foraging behavior and pheromone communication. In the ant algorithm, there is a colony consisting of many simple ant agents that continuously visit TSP cities with opinions to prefer subtours connecting near cities and they lay strong pheromones. The ants completing their tours lay pheromones of various intensities with passed subtours according to distances. Namely, subtours in TSP tourns that have the possibility of being better tend to have strong pheromones, so the ant agents specify good regions in the search space by using this positive feedback mechanism. In this paper, we propose a multiple ant colonies algorithm that has been extended from the ant algorithm. This algorithm has several ant colonies for solving a TSP, while the original has only a single ant colony. Moreover, two kinds of pheromone effects, positive and negative pheromone effects, are introduced as the colony-level interactions. As a result of colony-level interactions, the colonies can exchange good schemata for solving a problem and can maintain their own variation in the search process. The proposed algorithm shows better performance than the original algorithm with almost the same agent strategy used in both algorithms except for the introduction of colony-level interactions.

It is proposed a novel method that optimizes nonlinear filters by unsupervised learning using a novel definition of morphological pattern spectrum, called "morphological opening/closing spectrum (MOCS)." The MOCS can separate smaller portions of image objects from approximate shapes even if the shapes are degraded by noisy pixels. Our optimization method analogizes the linear low-pass filtering and Fourier spectrum: filter parameters are adjusted to reduce the portions of smaller sizes in MOCS, since they are regarded as the contributions of noises like high-frequency components. This method has an advantage that it uses only target noisy images and requires no example of ideal outputs. Experimental results of applications of this method to optimization of morphological open-closing filter for binary images are presented.