A new method is proposed for estimating a single complex sinusoid and its parameters (frequency and amplitude) from measurements corrupted by white noise. This method is called the ECKF-SVD method, which is derived by applying an extended complex Kalman filter (ECKF) to a nonlinear stochastic system whose state variables consist of the AR coefficient (a function of frequency) and a sample of the original signal. Proof of the stability is given in the case of a single sinusoid. Simulations demonstrate that the proposed ECKF-SVD method is effective for estimating a single complex sinusoid and its frequency under a low signal-to-noise ratio (SNR). In addition, the amplitude estimation by means of the ECKF-SVD method is also discussed.

Our compact switching converter using a thin-film microtransformer mono-lithically integrated with rectifier diodes represents the first step in developing a monolithic micro-switching converter that can be integrated with semiconductor devices and magnetic components. This converter is a single-ended forward converter with resonant reset and operates successfully at 15 MHz. The maximum output power is 0.5 W.

The defects in the cold rolled strips have textural characteristics, which are nonuniform due to its irregularities and deformities in geometrical appearance. In order to handle the textural characteristics of images with defects, this paper proposes a surface inspection method based on textural feature extraction using the wavelet transform. The wavelet transform is employed to extract local features from textural images with defects both in the frequency and in the spatial domain. To extract features effectively, an adaptive wavelet packet scheme is developed, in which the optimum number of features are produced automatically through subband coding gain. The energies for all subbands of the optimal quadtree of the adaptive wavelet packet algorithm and four entropy features in the level one LL subband, which correspond to the local features in the spatial domain, are extracted. A neural network is used to classify the defects of these features. Experiments with real image data show good training and generalization performances of the proposed method.

This paper proposes a new method for recovering the original signals from their linear mixtures observed by the same number of sensors. It is performed by identifying the linear transform from the sources to the sensors, only using the sensor signals. The only assumption of the source signals is basically the fact that they are statistically mutually independent. In order to perform the 'blind' identification, some time-correlational information in the observed signals are utilized. The most important feature of the method is that the full information of available time-correlation data (second-order statistics) is evaluated, as opposed to the conventional methods. To this end, an information-theoretic cost function is introduced, and the unknown linear transform is found by minimizing it. The propsed method gives a more stable solution than the conventional methods.

MPO optical backplane connectors using multi-fiber push-on plugs (MPO plugs) have been developed. MPO optical backplane connector is a connector connecting a printed board to a backplane using MPO plug. MPO plug is held in the housing with self-retentive mechanism. To get same optical performances as standard MPO connector, precision in dimension and mechanism for appropriate connecting-disconnecting sequence are necessary. We have developed a new backplane housing and printed board housing based on previously reported MU connector. The optical performance is similar to that of MPO connectors.

This paper proposes a data-localization scheduling scheme inside a processor-cluster for multigrain parallel processing, which hierarchically exploits parallelism among coarsegrain tasks like loops, medium-grain tasks like loop iterations and near-fine-grain tasks like statements. The proposed scheme assigns near-fine-grain or medium-grain tasks inside coarse-grain tasks onto processors inside a processor-cluster so that maximum parallelism can be exploited and inter-processor data transfer can be minimum after data-localization for coarse-grain tasks across processor-clusters. Performance evaluation on a multiprocessor system OSCAR shows that multigrain parallel processing with the proposed data-localization scheduling can reduce execution time for application programs by 10% compared with multigrain parallel processing without data-localization.

The convergence characteristics of the adaptive beamformer with the RLS algorithm are analyzed in this paper. In case of the RLS adaptive beamformer, the convergence characteristics are significantly affected by the spatial characteristics of the signals/noises in the environment. The purpose of this paper is to show how these physical parameters affect the convergence characteristics. In this paper, a typical environment where a few directional noises are accompanied by background noise is assumed, and the influence of each component of the environment is analyzed separately using rank analysis of the correlation matrix. For directional components, the convergence speed is faster for a smaller number of noise sources since the effective rank of the input correlation matrix is reduced. In the presence of background noise, the convergence speed is slowed down due to the increase of the effective rank. However, the convergence speed can be improved by controlling the initial matrix of the RLS algorithm. The latter section of this paper focuses on the physical interpretation of this initial matrix, in an attempt to elucidate the mechanism of the convergence characterisitics.

We studied the application of precursor solutions that can be fired into oxides to form a protective layer for AC-type Plasma Display Panel (AC-PDP). Our study of alkoxide and metallic soap as MgO precursors revealed that the crystallinity of MgO films depends on the starting substance. Since the electric discharge characteristics of a panel and the lamination effect of the protective layer depend on precursors, it was confirmed that binders having higher crystallinity provide better characteristics. Our study revealed that a compound-oxide film has high crystallinity. The application of a Ba0.6Sr0.4Gd2O4 formation solution to a binder and the application of a Sr0.6Mg0.4Gd2O4 formation solution to a protective layer both are seemed promising We also found that a double-layer film, made by forming a protective layer of fine MgO powder and a Ba0.6Sr0.4Gd2O4 binder, on top of a protective layer made of fine MgO powder and a MgO binder, provides a luminous efficiency 5.3 times higher than that of sputtered MgO film which is one of candidates for the large panel, and the conventional electron beam evaporation is not suitable for the large panel. We further found that a triple-layer protective film made by forming a thin film of Sr0.6Mg0.4Gd2O4 provides low voltages of 1 V in firing voltage (Vf) and 35 V in sustaining voltage (Vs) compared to the double-layer film and provides a luminous efficiency 5.5 times higher than that of sputtered MgO film. A life test revealed the triple-layer film in particular providing a useful life of more than 10,000 hours. From these findings, we concluded that the compound-oxides which is composed of alkaline-earth-metal and rare-earth-element could be applied effectively to a protective layer for AC-PDP.

The multichannel distortions of direct modulated laser diode were studied from the view point of rate equations. A novel technique for compensating the composite second order distortion (CSO) was proposed. Meanwhile, the related calibration procedures were indicated. After the compensation, 10 dB improvement in CSO was obtained

We present a topological framework of stepwise specification for concurrent systems in this paper. Some of description techniques can make topologies on the system space. Such topologies corresponds to abstract levels of those description techniques. Using a family of such description techniques, one can specify systems stepwisely. This framework allows to bridge various DTs and modularizing, so that global properties and module properties of systems become to be related to each other. Within this framework, we show derivation of a LOTOS cpecification from temporal logic formulae. An extended version of LOTOS with respect to concurrency is used in this paper. A semantics including concurrency is introduced to do this in this method. The method presented in this paper is applied to mobile telecommunication.

The fabrication of InAlAs wire structures and InGaAs quantum wire structures on non-planer InP substrates with truncated ridges by molecular beam epitaxy is demonstrated. Indium-rich InAlAs epitaxial layers grown on top of ridges exhibit self-formation of electron-confining InAlAs wire structures. The InAlAs layers on top of the ridges lattice-matched to the substrate are obtained by the control of In flux during the growth. The InGaAs quantum wire structures have been fabricated on thus composition-controlled InAlAs barrier layers. The optical properties of the InGaAs quantum wires with composition-controlled InAlAs barrier layer are found to be better than that of the wires without compositional control.

M-ary orthogonal keying (MOK) systems under carrier frequency offset (CFO) are investigated. It is shown that spurious signals are introduced by the offset frequency components of spectrum after multiplication in correlation detection process, and some conditions on robust orthogonal signal sets are derived. Walsh function sets are found to be very weak against CFO, since they produce large spurious signals. As robust orthogonal signal sets against CFO, the rows of circulant Hadamard matrices are proposed and their error performanses are evaluated. The results show that they are good M-ary orthogonal signal sets in the presence of CFO.

The evaluation of a error probability of a trellis-coded modulation scheme by an ordinary Monte-Carlo simulation method is almost impossible since the excessive simulation time is required to evaluate it. The reduction of the number of simulation runs required is achieved by an importance sampling method, which is one of the variance reduction simulation methods. The reduction of it is attained by the modification of the probability density function, which makes errors more frequent. The error event simulation method, which evaluates the error probability of finite important error events, cannot avoid a truncation error. It is the fatal problem to evaluate the precision of the simulation result. The reason of it is how to design the simulation probability density function. We propose a evaluation method and the design methods of the simulation conditional probability density function. The proposed method simulates any error event starting at the fixed time, and the estimator of it has not the truncation error. The proposed design method approximate the optimum simulation conditional probability density function. By using the proposed method for an additive non-Gaussian noise case, the simulation time of the most effective case of the proposed method is less than 1/5600 of the ordinary Monte-Carlo method at the bit error rate of 10-6 under the condition of the same accuracy if the overhead of the selection of the error events is excluded. The simulation time of the same bit error rate is about 1/96 even if we take the overhead for the importance sampling method into account.

The importance sampling simulation technique has been exploited to obtain an accurate estimate for a very small probability which is not tractable by the ordinary Monte Carlo simulation. In this paper, we will investigate the simulation for a sample average of an output sequence from a Markov chain. The optimal simulation distribution will be characterized by the Kullback-Leibler divergence of Markov chains and geometric properties of the importance sampling simulation will be presented. As a result, an effective computation method for the optimal simulation distribution will be obtained.

The objective of this paper is to find a parametric representation for the vocal-tract log-area function that is directly and simply related to basic acoustic characteristics of the human vocal-tract. The importance of this representation is associated with the solution of the articulatory-to-acoustic inverse problem, where a simple mapping from the articulatory space onto the acoustic space can be very useful. The method is as follows: Firstly, given a corpus of log-area functions, a parametric model is derived following a factor analysis technique. After that, the articulatory space, defined by the parametric model, is filled with approximately uniformly distributed points, and the corresponding first three formant frequencies are calculated. These formants define an acoustic space onto which the articulatory space maps. In the next step, an independent component analysis technique is used to determine acoustic and articulatory coordinate systems whose components are as independent as possible. Finally, using singular value decomposition, acoustic and articulatory coordinate systems are rotated so that each of the first three components of the articulatory space has major influence on one, and only one, component of the acoustic space. An example showing how the proposed model can be applied to the solution of the articulatory-to-acoustic inverse problem is given at the end of the paper.

A self-organizing neural network model of spatio-temporal visual receptive fields is proposed. It consists of a one-layer linear learning network with multiple temporal input channels, and each temporal channel has different impulse response. Every weight of the learning network is modified according to a Hebb-type learning algorithm proposed by Sanger. It is shown by simulation studies that various types of spatio-temporal receptive fields are self-organized by the network with random noise inputs. Some of them have similar response characteristics to X- and Y-type cells found in mammalian retina. The properties of receptive fields obtained by the network are analyzed theoretically. It is shown that only circularly symmetric receptive fields change their spatio-temporal characteristics depending on the bias of inputs. In particular, when the inputs are non-zero mean, the temporal properties of center-surround type receptive fields become heterogeneous and alter depending on the positions in the receptive fields.

In this paper, we show that by suitably selecting a notation to construct synchronization requirement specifications (SRS) for multimedia presentation we can express the timing characteristics at an abstract level, verify the specification, and obtain a hardware implementation through a sequence of transformations of the specification. First, we introduce the notion of a well-formed SRS and its hardware model. Second, we model an SRS as a timed Petri net and interpret the transitions of the net as hardware signals. To obtain logic functions from the SRS, we simplify the net and obtain a signal transition graph satisfying the unique state coding property. Finally, we show how to obtain a logic-level design of synchronizers.

Three dimensional model based coding methods are proposed as next generation image coding methods. These new representations need 3D reconstruction techniques. This paper presents a method that extracts the surfaces of static objects that occlude other objects from a spatiotemporal image captured with straight-line camera motion. We propose the concept of occlusion types and show that the occlusion types are restricted to only eight patterns. Furthermore, we show occlusion type pairs contain information that confirms the existence of surfaces. Occlusion information gives strong cues for segmentation and representation. The method can estimate not only the 3D positions of edge points but also the surfaces bounded by the edge points. We show that combinations of occlusion types contain information that can confirm surface existence. The method was tested successfully on real images by reconstructing flat and curved surfaces. Videos can be hierarchically structured with the method. The method makes various applications possible, such as object selective image communication and object selective video editing.

A practical structural representation of a segmented image is presented. The practicalness is defined according to whether or not the representation can be directly generated from its corresponding segmented image. Two structural representations have been proposed in the literature. They are hierarchical structure and relational graph. Because they are defined totally on the basis of human perception, neither of the representations can be directly generated from the corresponding segmented image. The structural representation described in this paper, however, is based on the relations among pattern primitives and generated by applying some human-oriented constraints.

A structural active-object system (SAOS) is a transition-based object-oriented system suitable for rapid development of hardware logic simulators. A SAOS consists of a collection of interacting structural active objects (SAOs), whose behaviors are determined by the transition statements provided in their class definitions. Furthermore, SAOs can be structurally and hierarchically composed from their component SAOs like hardware components. These features allow SAOs to model components for circuit simulation more naturally than passive objects used in ordinary object-oriented programming. Also, we can easily create new kinds of components by using the inheritance mechanism. Executions of transition statements may be event-and/or time-driven, and hence digital, analog, and mixed-mode simulation is possible. Prototype simulation programs with graphical user interfaces have been developed as SAOS programs for digital, analog, and mixed-mode circuit simulation.