A W-graph is a partially known graph which contains wild-components. A wild-component is an incompletely defined connected subgraph having p vertices and p-1 unspecified edges. The informations we know on a wild-component are which has a vertex set and between any two vertices there is one and only one path. In this paper, we discuss the properties of circuits in a W-graph (called W-circuits). Although a W-graph has unspecified edges, we can obtain some important properties of W-circuits. We show that the W-ring sum of W-circuits is also a W-circuit in the same W-graph. The following (1) and (2) are proved: (1) A W-circuit Ci of a W-graph can be transformed into either a circuit or an edge disjoint union of circuits, denoted by Ci*, of a graph derived from the W-graph, (2) if W-circuits C1, C2, , Cn are linearly independent, then C1*, C2*, , Cn* obtained in (1) are also linearly independent.

The sidelobe canceler in radar systems is a highly computational demanding problem. It can be efficiently tackled by resorting to the QR decomposition mapped onto a systolic array processor. The paper reports several mapping strategies by using massive parallel computers available on the market. MIMD as well as SIMD machines have been used, specifically MEIKO Computing Surface, nCUBE2, Connection Machine CM-200, and MasPar MP-1. The achieved data throughput values have been measured for a number of operational situations of practical interest.

Composite materials of solid lubricants, such as graphite, MoS2, WS2, etc., and metals are being used as the sliding electrical contacts. However, few reports have so far been presented on the detailed characteristics of such composite materials. It is shown in this report that contact resistance and coefficient of friction of the sliding contact of the composite material of Cu-Nb system against Cu were higher than those of the sliding contact of the composite material of Cu-Sn system against Cu. It was, further, found that composite materials of Cu-Sn system were superior to those of Cu-Nb system being both contact resistances and coefficients of friction lowered. At the same time, it was found that performances of composite materials of Cu-Sn alloy base containing exclusively WS2 were superior to those containing both WS2 and MoS2. It was, therefore, suggested that proper samples suitable for the service conditions should be selected from the composite materials of Cu-Sn system which contain exclusively WS2 for the practical applications.

This paper describes a high-density, high-pin-count flexible SMD connector used for high-speed data buses between MCMs or daughter boards. This connector consists of a flexible film cable interconnection with accurately controlled characteristic impedance, and a contact housing composed of double-line contacts and SMD type leads. It has 98 contacts each with a pitch of 0.4 mm. The connector mounting area is 6 mm wide and 23 mm long. The flexible cable has a double-sided triple-parallel micro stripline structure with an insertion force of less than 2.9 kgf and characteristic impedance of 48 to 50 Ω. Insertion loss is -0.5 dB at 600 MHz and crosstalk noise is less than 110 mV at 250 ps rising time. This connector can be used for high-speed data transmission of up to 300 ps rising time.

Recently, a lot of research works have been carried out regarding intelligent communication. If the final information sink is assumed as a human being, a communication channel can be used more effectively when encoders/decoders work "intelligently" or take into account of the semantics of information to be sent. We have been studying error-controlling systems based on different importance of segmental information. The system divides the information input into segments to which individual importance can be assigned. The segments are individually encoded by appropriate error-correcting codes (ECCs) which correspond to their importance among codes with different error-correcting capabilities. For the information that difference of the importance is systematically aligned, conventional UEP (unequal error protection) codes can be applied, but we treat the case that alignment of the importance of the information source is not systematically aligned. Since the system uses multiple ECCs with different (n,k,d) parameters, information regarding what length of the next codeword is required for decoding. We propose error controlling schemes using mulriple ECCs; the first scheme and the second scheme use the obvious codelength identifying information. In the second scheme, information bits are sorted so that segments with the same importance can be encoded by an ECC with the same error-correcting capability. The third scheme is a main proposal in this paper and uses Variable Capability Coding scheme (VCC) which uses some ECCs having different error-correcting capabilities and codelengths. A sequence encoded by the VCC is separable into appropriate segments without obvious codelength identifying information when the channel error probability is low. Subsequently, we evaluate these schemes by coderate when (1) error correcting capability (2) codelength identifying capability are the same. One of the feature of VCC is the capability of resuming from propagative errors because errors beyond the codelength identifying capability occur and the proper beginning of the codeword is lost in the decoder. We also evaluate this capability as (3) resynchronizing capability.

Almost stoichiometric YBa2Cu3O7-δ(110) or (103) and SrTiOx(110) films, and multilayer films consisting of them have successfully been grown epitaxially on hot SrTiO3 substrates by 90off-axis rf magnetron sputtering with facing targets. Their whole composition, compositional distribution in depth, crystallinity and surface morphology were examined by inductively coupled plasma spectroscopy, Auger electron spectroscopy, reflection high-energy electron diffraction, and scanning tunneling microscopy or atomic force microscope, respectively. When any YBa2Cu3O7-δ film was exposed to air after deposition, a Ba-rich layer was formed in a near surface region of the film. However, such a compositional distribution in depth of the film was improved by in situ deposition of a SrTiOx film on it. Moreover, the surface roughness of the YBa2Cu3O7-δ film was improved by predeposition of a SrTiOx film under it. On the basis of these results, both YBa2Cu3O7-δ/SrTiOx/YBa2Cu3O7-δ/SrTiO3(sub.) and YBa2Cu3O7-δ/SrTiOx/YBa2Cu3O7-δ/SrTiOx/SrTiO3(sub.) multilayer films with average surface roughness of 3 nm were grown reproducibly, which had uniform compositional distribution throughout the depth of the film except a near surface region of the top YBa2Cu3O7-δ layer. A new 222 structure described by Sr8Ti8O20 (Sr2Ti2O5) with a long range ordered arrangement of oxygen vacancies was formed in the SrTiOx films deposited epitaxially on YBa2Cu3O7-δ films.

An approach to estimate the information of moving objects is described in terms of their kinetic and static properties such as 2D velocity, acceleration, position, and the size of each object for the features of motion snd shape. To obtain the information of motion/shape of multiple objects, an advanced contour matching scheme is developed, which includes the synthesis of edge images and the analysis of object shape with a high matching confidence as well as a low computation cost. The scheme is composed of three algorithms: a motion estimation by an iterative triple cross-correlation, an image synthesis by shifting and masking the object, and a shape analysis for determining the object size. Implementing fuzzy membership functions to the object shape, the scheme gets improved in accuracy of capturing motion and shape of multiple moving objects. Experimental result shows that the proposed method is valid for several walking men in real scene.

A method is presented to perform image segmentation by accumulatively observing apparent motion in a long image sequence of a dynamic scene. In each image in the sequence, locations are grouped into small patches of approximately uniform optical flow. To reduce the noise in computed flow vectors, a local image motion vector of each patch is computed by averaging flow vectors in the corresponding patches in several images. A segment contains patches belonging to the same 3-D plane in the scene. Initial segments are obtained in the image, and then an attempt to merge or split segments is iterated to update the segments. In order to remove inherent ambiguities in motion-based segmentation, temporal coherence between the local image motion of a patch and the apprent motion of every plane is investigated over long time. In each image, a patch is grouped into the segment of the plane whose apparent motion is temporally most coherent with the local image motion of the patch. When apparent motions of two planes are temporally incoherent, segments of the planes are retained as individual ones.

Myoelectric (ME) signals during dynamic movement suffer from motion arifact noise caused by mechanical friction between electrodes and the skin. It is difficult to reject artifact noises using linear filters, because the frequency components of the artifact noise include those of ME signals. This paper describes a nonlinear method of eliminating artifacts. It consists of an inverse autoregressive (AR) filter, a nonlinear filter, and an AR filter. To deal with ME signals during dynamic movement, we introduce an adaptive procedure and fuzzy rules that improve the performance of the nonlinear filter for local features. The result is the best ever reported elimination performance. This fuzzy rule based adaptive nonlinear artifact elimination filter will be useful in measurement of ME signals during dynamic movement.

An adaptive array antenna can be considered as a useful tool of combating with fading in mobile communications. We can directly obtain the optimal weight coefficients without updating in temporal sampling, if the arrival angles and signal-to-noise ratio (SNR) of the desired and the undesired signals can be accurately estimated. The Maximum Entropy Method (MEM) can estimate the arrival angles, and the SNR from spatially sampled signals by an array antenna more precisely than the Discrete Fourier Transform (DFT). Therefore, this paper proposes and investigates an adaptive array antenna based on spatial spectral estimation using MEM. We call it MEM array. In order to reduce complexity for implementation, we also propose a modified algorithm using temporal updating as well. Furthermore, we propose a method of both improving estimation accuracy and reducing the number of antenna elements. In the method, the arrival angles can be approximately estimated by using temporal sampling instead of spatial sampling. Computer simulations evaluate MEM array in comparison with DFT array and LMS array, and show improvement owing to its modified algorithm and performance of the improved method.

In this paper, we present a new technique for the semantic analysis of sentences, including an ambiguity-packing method that generates a packed representation of individual syntactic and semantic structures. This representation is based on a dependency structure with constraints that must be satisfied in the syntax-semantics mapping phase. Complete syntax-semantics mapping is not performed until all ambiguities have been resolved, thus avoiding the combinatorial explosions that sometimes occur when unpacking locally packed ambiguities. A constraint satisfaction technique makes it possible to resolve ambiguities efficiently without unpacking. Disambiguation is the process of applying syntactic and semantic constraints to the possible candidate solutions (such as modifiees, cases, and wordsenses) and removing unsatisfactory condidates. Since several candidates often remain after applying constraints, another kind of knowledge to enable selection of the most plausible candidate solution is required. We call this new knowledge a preference. Both constraints and preferences must be applied to coordination for disambiguation. Either of them alone is insufficient for the purpose, and the interactions between them are important. We also present an algorithm for controlling the interaction between the constraints and the preferences in the disambiguation process. By allowing the preferences to control the application of the constraints, ambiguities can be efficiently resolved, thus avoiding combinatorial explosions.

A photonic network with a space- and frequency switching capability is proposed. It provides point-to-point and point-to-multipoint connections without internal blocking. The switching network exclusively uses frequency switching stages and a shared-medium architecture. Our proposal is compared with similar published networks which are either also constructed solely from frequency switching stages or from frequency and space switching stages. It is shown that the proposed switching network features fewer optical and opto-electronic components, fewer different types of component/module, lower losses, a higher capacity and an easier expansibility.

The performances of BPNN (neural network trained by back propagation) and PCANN (neural network which computes principal component analysis) for ECG data compression have been investigated from several points of view. We have compared them with an existing data compression method TOMEK. We used MIT/BIH arrhythmia database as ECG data. Both BPNN and PCANN showed better results than TOMEK. They showed 1.1 to 1.4 times higher compression than TOMEK to achieve the same accuracy of reproduction (13.0% of PRD and 99.0% of CC). While PCANN showed better learning ability than BPNN in simple learning task, BPNN was a little better than PCANN regarding compression rates. Observing the reproduced waveforms, BPNN and PCANN had almost the same performance, and they were superior to TOMEK. The following characteristics were obtained from the experiments. Since PCANN is sensitive to the learning rate, we had to precisely control the learning rate while the learning is in progress. We also found the tendency that PCANN needs larger amount of iteration in learning than BPNN for getting the same performance. PCANN showed better learning ability than BPNN, however, the total learning cost were almost the same between BPNN and PCANN due to the large amount of iteration. We analyzed the connection weight patterns. Since PCANN has a clear mathematical background, its behavior can be explained theoretically. BPNN sometimes generated the connection weights which were similar to the principal components. We supposed that BPNN may occasionally generate those patterns, and performs well while doing that. Finally we concluded as follows. Although the difference of the performances is smal, it was always observed and PCANN never exceeded BPNN. When the ease of analysis or the relation to mathematics is important, PCANN is suitable. It will be useful for the study of the recorded data such as statistics.

This paper describes automatic generation of speech synthesis rules which predict a stress level for each bunsetsu in long noun phrases. The rules are inductively inferred from a lot of speech data by using two kinds of tree-based methods, the conventional decision tree and the SBR-tree methods. The rule sets automatically generated by two methods have almost the same performance and decrease the prediction error to about 14 Hz from 23 Hz of the accent component value. The rate of the correct reproduction of the change for adjacent bunsetsu pairs is also used as a measure for evaluating the generated rule sets and they correctly reproduce the change of about 80%. The effectiveness of the rule sets is verified through the listening test. And, with regard to the comprehensiveness of the generated rules, the rules by the SBR-tree methods are very compact and easy to human experts to interpret and matches the former studies.

When orignal signals are contaminated by both additive and signal-dependent noise components, the test statistics of locally optimum detector are obtained for detection of weak composite signals based on the generalized Neyman-Pearson lemma. In order to consider the non-additive noise as well as purely-additive noise, a generalized observation model is used in this paper. The locally optimum detector test statisics are derived for all different cases according to the relative strengths of the known signal, random signal, and signal-dependent noise components. Schematic diagrams of the structures of the locally optimum detector are also included. The finite sample-size performance characteristics of the locally optimum detector are compared with those of other common detectors.

A fast and efficient heuristic hierarchical global router for Sea-of-Gates(SOG) with embedded macro-blocks is described. The key point in the method is carry out a new optimal domain decomposition scheduling at every hierarchical level. This scheduling is intended to avoid macro-block-through wirings and to reduce wiring congestion near macro-blocks which may occur at lower levels. The new global router yielded superior results compared with previous hierarchical routers and a non-hierarchical maze router by evaluating with several actual SOG circuits including a 300K gate master chip and benchmark data supplied from MCNC. Overflows were reduced to one-half or one-quarter for macro-block embedded data compared with previous hierarchical routers. Concerning the running time, the router remarkably outperformed the non-hierarchical maze router, which took more than 390 times longer time for the tested large data.

Reducing communication complexity is a viable approach to multilevel logic synthesis. A communication complexity based approach was proposed previously. In the previous works, only disjoint input decomposition was considered. However, for certain types of circuits, the circuit size can be reduced by using overlapped decomposition. In this paper, we consider overlapped decompositions. Some design issues for overlapped decompositions such as detecting globals" and deriving subfunctions are addressed. Moreover, the Decomposition Don't Cares (DDC) is considered for improving the decomposed results. By using these techniques together, the area and delay of circuits can be further minimized.

This paper describes an adaptive sensing system with tracking and zooming a moving object in the stable environment. Both the close contour matching technique and the effective determination of zoom ratio by fuzzy control are proposed for achieving the sensing system. First, the estimation of object feature parameters, 2-dimensional velocity and size, is based on close contour matching. The correspondence problem is solved with cross-correlation in projections extracted from object contours in the specialized difference images. In the stable environment, these contours matching, capable of eliminating occluded contours or random noises as well as background, works well without heavy-cost optical flow calculation. Next, in order to zoom the tracked object in accordance with the state of its shape or movement practically, fuzzy control is approached first. Three sets of input membership function--the confidence of object shape, the variance of object velocity, and the object size--are evaluated with the simplified implementation. The optimal focal length is achieved of not only desired size but safe tracking in combination with fuzzy rule matrix constituted of membership functions. Experimental results show that the proposed system is robust and valid for numerous kind of moving object in real scene with system period 1.85 sec.

In this paper we propose a method of formal verfication of fault-tolerance of sequential machines using regular temporal logic. In this method, fault-tolerant properties are described in the form of input-output sequences in regular temporal logic formulas and they are formally verified by checking if they hold for all possible input-output sequences of the machine. We concretely illustrate the method of its application for formal verification of fail-safeness with an example of a comparator for redundant system. The result of verification shows effectiveness of the proposed method.

This paper's main objective is to analyze several procedures which select the model g among a set G of stochastic models to minimize the value of an information criterion in the form of L(g)H[g](zn)+(k(g)/2)c(n), where zn is the n observed data emitted by an information source θ which consists of the model gθ∈G and k(gθ) mutually independent stochastic parameters in the model gθ∈G, H[g](zn) is (-1) (the maximum log likelihood value of the data zn with respect to a model g∈G), and c(n) is a predetermined function (penalty function) of n which controls the amount of penalty for increasing the model size. The result is focused on specific performances when the information criteria are applied to the framework of so-called state decomposition. Especially, upper bounds are derived of the following two performance measures for each penalty function c(n): the error probability of the model selection, and the average Kullback-Leibler information between the true information source and the estimated information source.