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.

This letter studies the Peak Cell Rate (PCR) policing of ATM connections that consist of multiple cell flow components. It is shown that the conventional methods proposed for policing the aggregate flow do not use the network's resources efficiently. This letter proposes a simple and efficient UPC (Usage Parameter Control) mechanism based on a tandem leaky bucket for multi-component ATM connections. The results show that network resource requirements can be minimized, with reasonable hardware complexity.

The global interpolation method we proposed can extract a handwritten alpha-numeric character pattern even if it overlaps a border. Our method interpolates blank segments in a character after borders are removed by evaluating segment pattern continuity and connectedness globally to produce characters with smooth edges. The main feature of this method is to evaluate global component label connectivity as pattern connectedness. However, it is impossible for the method to interpolate missing superpositioning loop segments, because they lack segment pattern continuity and they have already had global component label connectivity. To solve this problem, we improved the method by adding loop interpolation as a global evaluation. The evaluation of character segment continuity is also improved to achieve higher quality character patterns. There is no database of overlapping characters, so we also propose an evaluation method which generates various kinds of overlapping numerals from an ETL database. Experimental results using these generated patterns showed that the improved global interpolation method is very effective for numbers that overlap a border.

This paper discusses visualization of temporal and spatial information in natural language descriptions (NLDs), focusing on the translation process of intermediate representations of NLDs to proper scenarios" and environments" for animations. First, the intermediate representations are shown according to the idea of actors. Actors and non-actors are represented as primitives of objects, whereas actions as those of events. Temporal and spatial constraints by a given NLD text are imposed upon the primitives. Then, the representations containing unknown temporal or spatial parameters --time and coordinates-- are translated into evaluation functions, where the unlikelihood of the deviations from the predicted temporal or spatial relations are estimated. Particularly, the functions concerning actor's movements contain both temporal and spatial parameters. Next, the sum of all the evaluation functions is minimized by a nonlinear optimization method. Thus, the most proper actors' time-table, or scenario, and non-actors' location-table, or environment, for visualization are obtained. Implementation and experiments show that both temporal and spatial information in NLDs are well connected through actors' movements for visualization.

Induced noises from breaking contact arc discharge and sliding contact discharge of dc motor are measured by pick up coil and current probe. Statistical properties, amplitude distribution probability (APD), of induced noise waveform are analyzed by simple method using intermediate frequency of spectrum analyzer. It is shown that APD characteristics can be used to estimate statistical characteristics and peak value of induced noise. Simulation model of the noise made by the combination of Gaussian noise is mentioned. The model called the composite noise generator (CNG) can be good fit to the real characteristics of both noises from breaking arc and dc motor. Applications of the CNG for noise filter using toroidal coil shows that the CNG is useful to realize the test of noise suppression characteristics. What parameters of the CNG should be considered is described for further applications.

The synergistic effects obtained by adopting both space diversity reception and adaptive equalization play a very important role in circuit outage reduction. This paper quantitatively analyzes these synergistic effects when dispersive and flat fading occur simultaneously. Analytical results show that the synergistic effects are of the same magnitude as the adaptive equalizer improvement factor when only dispersive fading causes outage. The synergistic effects gradually disappear when noise is the predominant cause of outage.

Several papers have been shown equalization in the reception side. However, equalization in transmission side that is partial response signaling (PRS) or precoding is also possible in a two-way interactive communication such as time or frequency division duplex (TDD of FDD). This paper proposes and investigates a system which includes a transmission equalization and reception equalization based on an array antenna. This system is the extension in spatial and temporal domains. The channel capacity can be improved in the super channel which includes the transmitter and receiver array antenna.

Circuit simulators are used to verify circuit functionality and to obtain detailed timing information before the expensive fabrication process takes place. They have become an essential CAD tool in an era of sub-micron technology. We have developed a new event-driven MOS circuit simulator to replace a direct method circuit simulator. In our simulator, partitioned subcircuits are analyzed by a direct method matrix solver, and these are controlled by an event-driven scheme to maintain accuracy. The key of this approach is how to manage events for circuit simulation. We introduced two types of events: self-control events for a subcircuit and prediction correcting events between subcircuits. They control simulation accuracy, and bring simulation efficiency through multi-rate behavior of a large scale circuit. The event-driven scheme also brings some useful functions which are not available from a direct method circuit simulator, such as a selected block simulation function and a batch simulation function for load variation. We simulated logic modules (buffer, adder, and counter) with about 1000 MOSFETs with our event-driven MOS circuit simulator. Our simulator was 5-7 times faster than a SPICE-like circuit simulator, while maintaining the less than 1% error accuracy. The selected block simulation function enables to shorten simulation time without losing any accuracy by selecting valid blocks in a circuit to simulate specified node waveforms. Using this function, the logic modules were simulated 13-28 times faster than the SPICE-like circuit simulator while maintaining the same accuracy.

This paper introduces a new image representation method that is named the projective image representation (PIR). We consider an image as a collage of symmetric segments each of which can be well represented by its projection data of a single orientation. A quadtree-based method is adopted to decompose an image into variable sized segments according to the complexity within it. Also, we deal with the application of the PIR to the image compression and propose an efficient algorithm, the quadtree-structured projection vector quantization (QTPVQ) which combines the PIR with the VQ. As the VQ is carried out on the projection data instead of the pixel intensities of the segment, the QTPVQ successfully overcomes the drawbacks of the conventional VQ algorithms such as the blocking artifact and the difficulty in manipulating the large dimension. Above all, the QTPVQ improves the subjective quality greatly, especially at low bit rate, which makes it applicable to low bit rate image coding.

An invertible length preserving transducer is called a weakly invertible finite automaton (WIFA for short). If the first letter of any input string of length τ + 1 is uniquely determined by the corresponding output string by a WIFA and its initial state, it is called a WIFA with delay τ. The composition of two WIFAs is the natural concatenation of them. The composition is also a WIFA whose delay is less than or equal to the sum of the delays of the two WIFAs. In this paper we derive various results on a decomposition of a WIFA into WIFAs with smaller delays. The motivation of this subject is from theoretical interests as well as an application to cryptosystems. In order to capture the essence of the decomposability problem, we concentrate on WIFAs such that their input alphabets and their output alphabets are identical. A WIFA with size n of the input and output alphabet is denoted by an n-WIFA. We prove that for any n > 1, there exists an n-WIFA with delay 2 which cannot be decomposed into two n-WIFAs with delay 1. A one-element logic memory cell is a special WIFA with delay 1, and it is called a delay unit. We show that for any prime number p, every strongly connected p-WIFA with delay 1 can be decomposed into a WIFA with delay 0 and a delay unit, and that any 2-WIFA can be decomposed into a WIFA wiht delay 0 and a sequence of k delay units if and only if every state of the 2-WIFA has delay k.

There have been many developments on neural network research, and ability of a multi-layered network for classification of multi-spectral image data has been studied. We can classify non-Gaussian distributed data using the neural network trained by a back-propagation method (BPM) because it is independent of noise conditions. The BPM is a supervised classifier, so that we can get a high classification accuracy by using the method, so long as we can choose the good training data set. However, the multi-spectral data have many kinds of category information in a pixel because of its pixel resolution of the sensor. The data should be separated in many clusters even if they belong to a same class. Therefore, it is difficult to choose the good training data set which extract the characteristics of the class. Up to now, the researchers have chosen the training data set by random sampling from the input data. To overcome the problem, a hybrid pattern classification system using BPM and Kohonens feature mapping (KFM) has been proposed recently. The system performed choosing the training data set from the result of rough classification using KFM. However, how the remotely sensed data had been influenced by the KFM has not been demonstrated quantitatively. In this paper, we propose a new approach using the competitive weight vectors as the training data set, because we consider that a competitive unit represents a small cluster of the input patterns. The approach makes the training data set choice work easier than the usual one, because the KFM can automatically self-organize a topological relation among the target image patterns on a competitive plane. We demonstrate that the representative of the competitive units by principal component analysis (PCA). We also illustrate that the approach improves the classification accuracy by applying it on the classification of the real remotely sensed data.

In identification of a finite impulse response (FIR) model using noise-corrupted input and output data, the least squares type of estimation schemes such as the ordinary least squares (LS), the corrected least squares (CLS) and the total least squares (TLS) method become often numerically unstable, when the true input signal to the system is strongly correlated. To overcome this ill-conditioned problem, we propose a regularized CLS estimation method by introducing multiple regularization parameters to minimize the mean squares error (MSE) of the regularized CLS estimate of the FIR model. The asymptotic MSE can be evaluated by considering the third and fourth order cross moments of the input and output measurement noises, and an analytical expression of the optimal regularization parameters minimizing the MSE is also clarified. Furthermore, an effective regularization algorithm is given by using the only accessible input-output data without using any true unknown parameters. The effectiveness of the proposed data-based regularization algorithm is demonstrated and compared with the ordinary LS, CLS and TLS estimates through numerical examples.

In order to evaluate quantitatively TMJ sound, TMJ sound in normal subject group, CMD patient group A with palpable sounds unknown to them, CMD patient group B with palpable sounds known to them, and CMD patient group C with audible sounds were detected by a contact microphone, and frequency analysis of the power spectra was performed. The power spectra of TMJ sound of normal subject group and patient group A showed patterns with frequency values below 100 Hz, whereas the power spectra of patient groups B and C showed distinctively different patterns with peaks of frequency component exceeding 100 Hz. As regards the cumulative frequency value, the patterns for each group clearly differed from those of other groups; in particular the 80% cumulative frequency value showed the greatest difference. From these results, it is assumed that the 80% cumulative frequency value can be used as an effective indicator for quantitative evaluation of TMJ sound.

This paper presents some tighter bounds on universal noiseless coding, in particular, the lowerbound tighter than Davisson et al.'s for finite sequence and the upperbound for some typical universal data compression. We find that Davisson et al.'s bound satisfies some optimization in the case of using the Jeffreys prior and also that the derived upperbound in this paper is within O(1/n) from the Clarke and Barron asymptotics in the case of some restricted typical universal data compression defined in the paper.

A soft magnetic force microscope (MFM) tip was used to evaluate the magnetic recording characteristics of compositionally separated Co-Cr perpendicular media. Small magnetic bits were recorded on thick (350 nm). and thin (100 nm) films, focusing on the fineness of compositionally separated microstructures. MFM images showed bit marks 230 and 150 nm in diameter, measured at full-width at half maximum (FWHM) for the thick and thin films, respectively. These results verify that the recordable bit size can be decreased by using a thinner film with a finer compositionally separated microstructure. Simulation was used to clarify the relationship between the actual sizes of the recorded bits and the sizes of their MFM images. The recorded bit size was found to closely correspond to the FWHM of the MFM bit images.

A typed, object-oriented database technology, equipped with appropriate declarative, temporal logic based executable constraints, is presented. The underlying object-oriented database type system is based on advanced features such as subtype, parametric and F-bounded polymorphism. A particularly distinctive feature of the type system is its associated type-safe reflection technology, which provides the flexibility required by database operators without sacrificing type safety. Strongly, and even statically typed, executable class specifications of a variety of standard database abstractions, both application-oriented and system-oriented, are presented in the paper, in order to demonstrate strate the applicability of the paradigm. The temporal logic basis of the constraint language has an execution model, as well as the minimal model semantics, and it allows complex, temporal behavioral patterns to be expressed. It is based on three tomporal operators: always, next time and some time, and rules that determine how these operators may be applied in temporal Horn clauses. Because of the object-oriented nature of the paradigm, the logic basis is also equipped with the equality predicate The proposed technology is intended to provide major advantages not only in managing appropriately complex application environments with temporal constraints, but also in providing more efficient (because of static type checking) and reliable database management systems. It offers the advantages of non-procedural data languages and the richness of a temporal object-oriented paradigm. It also leads to a powerful prototyping tool for structural and behavioral testing of complex, strongly typed object-oriented systems, prior to major procedural implementation efforts.

This paper discusses an object-oriented approach to temporal multimedia data modeling in OMEGA; a multimedia database management under development at the University of Library and Information Science. An object-orientated approach is necessary to integrate various types of heterogeneous multimedia data, but it has become clear that current object-oriented data models are not sufficient to represent multimedia data, particularly when they are temporal. For instance, the current object-oriented data models cannot describe objects whose attribute values change time-dependently. Also, they cannot represent temporal relationships among temporal multimedia objects. We characterize temporal objects as instances of a subclass of class TimeInterval with the temporal attributes and the temporal relationships. This temporal multimedia data model is designed upward compatible with the ODMG-93 standard object model. To organize a temporal multimedia database, a five temporal axes model for representing temporal multimedia objects is also introduced. The five temporal axes--an absolute, an internal, a quasi-, a physical, and a presentation time axis--are necessary to describe time-dependent properties of multimedia objects in modeling, implementing and use. A concrete example of this organization method is also illustrated.

This paper proposes a technique for estimating the harmonic frequencies based on instantaneous frequency (IF) of speech signals. The main problem is how to decompose the speech signal into the harmonic components. For this purpose, we use a set of bandpass-filters, each of whose center frequencies changes with time in order to track the instantaneous freuency of its output. As a result, the outputs of the band-pass filters become the harmonic components, and the instantaneous frequencies of the harmonics are accurately estimated. To evaluate the effectiveness of the approach, we apply it to pitch determination of speech. Pitch determination is simply accomplished by selecting the correct fundamental frequency out of the harmonic components. It is confirmed that the pitch extraction using the proposed pitch determination algorithm (PDA) is stable and accurate. The most significant feature of the PDA is that the extracted pitch contour is smooth and it requires no post-processing such as nonlinear filtering or any smoothing processes. Several examples are presented to demonstrate the capability of the harmonics estimation technique and the PDA.

We propose an algorithm for image decomposition based on Hadamard functions, realized by answer-in-weights neural network, which has simple architecture and is explored with steepest decent method. This scheme saves memory consumption and it converges fast. Simulations with least mean square (LMS) and absolute mean (AM) errors on a 128128 image converge within 30 training epochs.

When bit error probability of a trellis-coded modulation (TCM) scheme becomes very small, it is almost impossible to evaluate it by an ordinary Monte-Carlo simulation method. Importance sampling is a technique of reducing the number of simulation samples required. The reduction is attained by modifying the noise to produce more errors. The low error rate can be effectively estimated by applying importance sampling. Each simulation run simulates a single error event, and importance sampling is used to make the error events more frequent. The previous design method of the probability density function in importance sampling is not suitable for the TCM scheme on an additive non-Gaussian noise channel. The main problem is how to design the probability density function of the noise used in the simulation. We propose a new design method of the simulation probability density function related to the Bhattacharyya bound. It is reduced to the same simulation probability density function of the old method when the noise is additive white Gaussian. By using the proposed method for an additive non-Gaussian noise, the reduction of simulation time is about 1/170 at bit error rate of 106 if the overhead of the calculation of the Bhattacharyya bound is ignored. Under the same condition, the reduction of the simulation time by the proposed method is 1/65 of the ordinary Monte-Carlo method even if we take the overhead for importance sampling into account.