A method to design one-dimensional cellular arrays to be used as TPG circuits of BIST is described. The interconnections between cells are not limited to adjacent ones but allowed to some neighbors. Completely regular structures that have full-transition coverages for every k-dimensional subspace of state variables are first shown. Then, almost regular arrays which can operate on maximum cycles are derived based on fast parallel implementations of LFSRs.

Conformance testing techniques are required for the efficient production of reliable communication protocols. A lot of conformance testing techniques have been developed. However, most of them can only decide whether an implemented protocol conforms to its specification. That is, the exact locations of faults are not determined by them. This paper presents some conditions that enable to find locations of multiple faults, and then proposes a test sequence generation technique under such conditions. The correctness proof and complexity analysis of the proposed technique are also given. The characteristics of this technique are to generate test sequences based on protocol specifications and interim test results, and to find locations of multiple faults in protocol implementations. Although the length of the test sequence generated by the proposed technique is a little longer than the one generated by the previous one, the class to which the proposed technique can be applied is larger than that to which the previous one can be applied.

The subject is the horizontal coil's temperature rise in DY for high frequency by being unavoidable for the tendency of more information on display monitor equipments. Writers made the temperature-balance model from a point of view that this temperature rise is coming from the heat rise and the conductivity, and we expressed the temperature rise of DY by using amount of the heat rise and conductivity characteristics of each element. Also, we indicated the method to decide about the selection of the wire size of coils, the section area and deflection sensitivity, with regard to reducing the temperature rise. We confirmed the effect of the temperature rise reduction by about 9 on products, under the condition of 64 kHz horizontal frequency.

A fiber optic temperature sensor using a conventional graded index multimode optical fiber is proposed. The multimode fiber is excited by two selected modes using a computer-generated holographic filter. A clear periodic signal created by interference between two modes is observed in the experiment.

A 3.3 V single power-supply 64 Mb flash memory with a DBL programming scheme has been developed and fabricated with 0.4 µm CMOS technology. 50 ns access time and 256 b erase/programming unit-capacity have been achieved by using hierarchical word- and bit-line structures and DBL programming scheme. Furthermore in order to lower operating voltage the HiCR cell is used. The chip size is 19.3 mm13.3 mm.

In this paper we present a design method for all-pass networks with consideration of the stability. It is based on the eigen filter method and Remez exchange algorithm is used to obtain the equiripple phase error solution. In the iteration of the proposed algorithm, the eigen values besides maximum eigen value are used in order to obtain a stable all-pass networks.

Ever increasing demand for higher bandwidth memories, which is fueled by multimedia and 3D graphics, seems to be somewhat satisfied with various emerging memory solutions. This paper gives a review of these emerging DRAM architectures and a performance comparison based on a condition to let the readers have some perspectives of the future and optimized graphics systems.

The word error probability of linear block codes is computed for diversity systems with maximal ratio combining in mobile communications with three decoding algorithms: error correction (EC), error/erasure correction (EEC), and maximum likelihood (ML) soft decoding algorithm. Ideal interleaving is assumed. EEC gives 0.1-1.5dB gain over EC. The gain of EEC over EC decreases as the number of diversity channels increases. ML soft gives 1.8-5.5dB gain over EC.

In this paper, we evaluate the performance of handoff schemes in microcellular personal communication systems (PCS) which cater to both pedestrian and vehicular users. Various performance parameters, including blocking of new calls,channel utilization, handoff blocking and call termination probabilities for each user type are evaluated. We study different queuing disciplines for handoff calls and their impact on system performance. We also study the tradeoff in handoff blocking and call termination probabilities between user types as the handoff traffic carried by the system from each user type is varied.

This paper describes analytical results of high-Tc superconducting asymmetric coplanar strip lines using the frequency-dependent finite-difference time-domain method. The propagation constants of the YBa2Cu3O7-x asymmetric coplanar strip line fabricated on the LiNbO3 substrate are reported. The effect of the SiO2 buffer layer is also investigated.

In this paper approaches to language identification based on the sequential information of phonemes are described. These approaches assume that each language can be identified from its own phoneme structure, or phonotactics. To extract this phoneme structure, we use phoneme classifiers and grammars for each language. The phoneme classifier for each language is implemented as a multi-layer perceptron trained on quasi-phonetic hand-labeled transcriptions. After training the phoneme classifiers, the grammars for each language are calculated as a set of transition probabilities for each phoneme pair. Because of the interest in automatic language identification for worldwide voice communication, we decided to use telephone speech for this study. The data for this study were drawn from the OGI (Oregon Graduate Institute)-TS (telephone speech) corpus, a standard corpus for this type of research. To investigate the basic issues of this approach, two languages, Japanese and English, were selected. The language classification algorithms are based on Viterbi search constrained by a bigram grammar and by minimum and maximum durations. Using a phoneme classifier trained only on English phonemes, we achieved 81.1% accuracy. We achieved 79.3% accuracy using a phoneme classifier trained on Japanese phonemes. Using both the English and the Japanese phoneme classifiers together, we obtained our best result: 83.3%. Our results were comparable to those obtained by other methods such as that based on the hidden Markov model.

We propose an objective measure from assessing low-rate coded speech. The model for this objective measure, in which several known features of the perceptual processing of speech sounds by the human ear are emulated, is based on the Hertz-to-Bark transformation, critical-band filtering with preemphasis to boost higher frequencies, nonlinear conversion for subjective loudness, and temporal (forward) masking. The effectiveness of the measure, called the Bark spectral distortion rating (BSDR), was validated by second-order polynomial regression analysis between the computed BSDR values and subjective MOS ratings obtained for a large number of utterances coded by several versions of CELP coders and one VSELP coder under three degradation conditions: input speech levels, transmission error rates, and background noise levels. The BSDR values correspond better to MOS ratings than several commonly used measures. Thus, BSDR can be used to accurately predict subjective scores.

This paper presents a new Adaptive Convergence Factor (ACF) algorithm without the damping parameter adjustment acoording to the input signal and/or the composition of the filter system. The damping parameter in the ACF algorithms has great influence on the convergence characteristics. In order to examine the relation between the damping parameter and the convergence characteristics, the normalization which is realized by the related signal terms divided by each maximum value is introduced into the ACF algorithm. The normalized algorithm is applied to the modeling of unknown time-variable systems which makes it possible to examine the relation between the parameters and the misadjustment in the adaptive algorithms. Considering the experimental and theoretical results, the optimum value of the damping parameter can be defined as the minimum value where the total misadjustment becomes minimum. To keep the damping parameter optimum in any conditions, the new ACF algorithm is proposed by improving the invariability of the damping parameter in the normalized algorithm. The algorithm is investigated by the computer simulations in the modeling of unknown time-variable systems and the system indentification. The results of simulations show that the proposed algorithm needs no adjustment of the optimum damping parameter and brings the stable convergence characteristics even if the filter system is changed.

A multi-layer perceptron (MLP) acting directly in the time-domain is applied as a speech signal enhancer, and the performance examined in the context of three common classes of degradation, namely low bit-rate CELP degradation is non-linear system degradation, additive noise, and convolution by a linear system. The investigation focuses on two topics: (i) the influence of non-linearities within the network and (ii) network topology, comparing single and multiple output structures. The objective is to examine how these characteristics influence network performance and whether this depends on the class of degradation. Experimental results show the importance of matching the enhancer to the class of degradation. In the case of the CELP coder the standard MLP with its inherently non-linear characteristics is shown to be consistently better than any equivalent linear structure (up to 3.2 dB compared with 1.6 dB SNR improvement). In contrast, when the degradation is from additive noise, a linear enhancer is always, superior.

In this paper, we present an analysis of a high-speed slotted ring with a single packet buffer at each station. Assuming that distances between stations affect the network performance only through the sum of themselves (this will be called the "lumpability assumption"), we introduce a model system called the lumped model in which stations are aggregated at a single point on the ring with their relative positions preserved. At the instant when each slot visits the aggregated point of the lumped model, we build a Markov chain by recording the system state of buffers and slots. From the steady state probabilities of the Markov chain, we obtain the mean waiting time and the blocking probability of each station. It will be shown analytically and by simulation that the analysis based on the lumped model yields accurate results for various network conditions.

Microwave radiometry has been investigated for non-invasive measurement of temperature in human body. Recent trends are to explore the capability of retrieving a temperature profile or map from a set of brightness temperatures measured by a multifrequency radiometer operating in a 1-6GHz range. The retrieval of temperature from the multifrequency measurement data is formulated as an inverse problem in which the number of independent measurement or data is limited (7) and the data suffer from considerably large random fluctuations. The standard deviation of the data fluctuation is given by the brightness temperature resolution of the instrument (0.04-0.1K). Solutions are prone to instabilities and large errors unless proper solution methods are used. Solution methods developed during the last few years are reviewed: singular system analysis, bio-heat transfer solution matched with radiometric data, and model-fitting combined with Monte Carlo technique. Typical results obtained by these methods are presented to indicate a crosssection of the present-state-of-the-development in the field. This review concludes with discussions on the radiometric weighting function which connects physical temperatures in object to the brightness temperature. Three-dimensional weighting functions derived by the modal analysis and the FDTD method for a rectangular waveguide antenna coupled to a four layered lossy medium are discussed. Development of temperature retrieval procedures incorporating the 3-D weighting functions is an important and challenging task for future work in this field.

Detection of an unknown word or non-vocabulary word uttered by the user is necessary in realizing a practical spoken language user-interface. This paper describes the evaluation of an unknown word processing method for a subword unit based spoken word recognizer. We have assessed the relationship between the word recognition accuracy of a system and the detection rate of unknown words both by simulation and by experiment of the unknown word processing method. We found that the resultant detection accuracies using the unknown word processing are significantly influenced by the original word recognition accuracy while the degree of such effect depends on the vocabulary size.

Many methods have been proposed for constructing context-dependent phoneme models using Hidden Markov Models (HMMs) to improve performance. These conventional methods require previously defined contextual factors. If these factors are deficient, the method exhibit poor recognition performance. In this paper, we propose a new construction algorithm for HMnet which does not require pre-defined contextual factors. Experiments demonstrated that the new algorithm could construct the HMnet even for the case that the Successive State Splitting (SSS) algorithm could not. The new algorithm produced better phoneme recognition characteristics than the SSS algorithm.

This paper proposes a new stochastic language model for speech recognition based on function-word N-grams and content-word N-grams. The conventional word N-gram models are effective for speech recognition, but they represent only local constraints within a few successive words and lack the ability to capture global syntactic or semantic relationships between words. To represent more global constraints, the proposed language model gives the N-gram probabilities of word sequences, with attention given only to function words or to content words. The sequences of function words and of content words are expected to represent syntactic and semantic constraints, respectively. Probabilities of function-word bigrams and content-word bigrams were estimated from a 10,000-sentence text database, and analysis using information theoretic measure showed that expected constraints were extracted appropriately. As an application of this model to speech recognition, a post-processor was constructed to select the optimum sentence candidate from a phrase lattice obtained by a phrase recognition system. The phrase candidate sequence with the highest total acoustic and linguistic score was sought by dynamic programming. The results of experiments carried out on the utterances of 12 speakers showed that the proposed method is more accurate than a CFG-based method, thus demonstrating its effectiveness in improving speech recognition performance.

In conventional word-spotting methods for automatic recognition of continuous speech, individual frames or segments of the input speech are assigned labels and local likelihood scores solely on the basis of their own acoustic characteristics. On the other hand, experiments on human speech perception conducted by the present authors and others show that human perception of words in connected speech is based, not only on the acoustic characteristics of individual segments, but also on the acoustic and linguistic contexts in which these segments occurs. In other words, individual segments are not correctly perceive by humans unless they are accompanied by their context. These findings on the process of human speech perception have to be applied in automatic speech recognition in order to improve the performance. From this point of view, the present paper proposes a new scheme for detecting words in continuous speech based on template matching where the likelihood of each segment of a word is determined not only by its own characteristics but also by the likelihood of its context within the framework of a word. This is accomplished by modifying the likelihood score of each segment by the likelihood score of its phonetic context, the latter representing the degree of similarity of the context to that of a candidate word in the lexicon. Higher enhancement is given to the segmental likelihood score if the likelihood score of its context is higher. The advantage of the proposed scheme over conventional schemes is demonstrated by an experiment on constructing a word lattice using connected speech of Japanese uttered by a male speaker. The result indicates that the scheme is especially effective in giving correct recognition in cases where there are two or more candidate words which are almost equal in raw segmental likelihood scores.