In this paper, we propose a learning fuzzy network (LFN) which can be used to implement most of fuzzy logic functions and is much available for hardware implementations. A learning algorithm largely borrowed from back propagation algorithm is introduced and used to train the LFN systems for several typical fuzzy logic problems. We also demonstrate the availability of the LFN hardware implementations by realizing them with CMOS current-mode circuits and the capability of the LFN systems by testing them on a benchmark problem in intelligent control-the inverted pendulum system. Simulations show that a learning fuzzy network can be realized with the proposed LFN system, learning algorithm, and hardware implementations.

This paper proposes a new pitch prediction method for 4 kbps CELP (Code Excited LPC) speech coding with 20 msec frame, for the future ITU-T 4 kbps speech coding standardization. In the conventional CELP speech coding, synthetic speech quality deteriorates rapidly at 4 kbps, especially for female and children's speech with short pitch period. The pitch prediction performance is significantly degraded for such speech. The important reason is that when the pitch period is shorter than the subframe length, the simple repetition of the past excitation signal based on the estimated lag, not the pitch prediction, is usually carried out in the adaptive codebook operation. The proposed pitch prediction method can carry out the pitch prediction without the above approximation by utilizing the current subframe excitation codevector signal, when the pitch prediction parameters are determined. To further improve the performance, a split vector synthesis and perceptually spectral weighting method, and a low-complexity perceptually harmonic and spectral weighting method have also been developed. The informal listening test result shows that the 4 kbps speech coder with 20 msec frame, utilizing all of the proposed improvements, achieves 0.2 MOS higher results than the coder without them.

We frequently need to calculate the Neumann function Nν(x) of complex order ν numerically in order to solve boundary problems on electromagnetic fields. This paper presents a new method for the numerical calculation of Nν(x) of complex order ν. This method can calculate Nν(x) precisely even when the order ν is close to an integer n, and the algorithm by the method is very simple.

In this paper, we propose a dialogue model that reflects two important aspects of spoken dialogue system: to be robust' and to be cooperative'. For this purpose, our model has two main inference spaces: Conversational Space (CS) and Problem Solving Space (PSS). CS is a kind of dynamic Bayesian network that represents a meaning of utterance and general dialogue rule. Robust' aspect is treated in CS. PSS is a network so called Event Hierarchy that represents the structure of task domain problems. Cooperative' aspect is mainly treated in PSS. In constructing CS and making inference on PSS, system's process, from meaning understanding through response generation, is modeled by dividing into five steps. These steps are (1) meaning understanding, (2) intention understanding, (3) communicative effect, (4) reaction generation, and (5) response generation. Meaning understanding step constructs CS and response generation step composes a surface expression of system's response from the part of CS. Intention understanding step makes correspondence utterance type in CS with action in PSS. Reaction generation step selects a cooperative reaction in PSS and expands a reaction to utterance type of CS. The status of problem solving and declared user's preference are recorded in mental state by communicative effect step. Then from our point of view, cooperative problem solving dialogue is regarded as a process of constructing CS and achieving goal in PSS through these five steps.

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 partially ferrites and dielectric loaded water filled waveguide applicator is presented which can be used for microwave heating of tissues. The applicator can change its heating pattern by changing the external DC magnetic field applied to the ferrites. The electromagnetic (EM) field distribution inside the applicator is obtained theoretically and the simulated EM field inside the applicator is checked experimentally using 430MHz. Furthermore, on the basis of the EM field distribution inside the applicator, simulations of SAR distribution inside lossy homogeneous human tissue as muscle are performed using finite difference time domain (FD-TD) method. Simulated data of Specific Absorption Rate (SAR) distribution is compared with the experimental ones. Simulations of temperature distribution are also performed using heat transfer equation. Simulated data of temperature elevation distribution is compared with the experimental ones. The simulated results agree well with the experimental ones and it is confirmed that the heating pattern can be changed by external DC magnetic field applied to the applicator. The results obtained here show that the partially ferrites and dielectric loaded water filled waveguide applicator which operates at 430 MHz can change its heating pattern without changing its setup and can heat local target on the human body for hyperthermia treatment.

The operation scheduling is an important subtask in the automatic synthesis of digital systems. Many greedy heuristics have been proposed for the operation scheduling, but they cannot find the globally best schedule. In this paper we present an algorithm to construct near optimal schedules. The algorithm combines characteristics of simulated annealing and neural networks. The neural network used in our scheduling algorithm is similar to that proposed by Hellstrom et al. However, while the problems of Refs. [11] and [12] have a single type of constraint, the problem considered in this paper has three types of constraints. As the result, the energy function of the proposed neural network is given by the weighted sum of three energy functions. To minimize the weighted sum of two or more energy functions, conventional methods try to find a good set of weights using a try and error method. Our algorithm takes a different approach than these methods. Results of the experiments show that the proposed algorithm can be used as an alternative heuristic for solving the operation scheduling problem. In addition, the proposed algorithm can exploit the inherent parallelism of the neural network.

The previous literature on consecutive k-out-of-r-from-n: F systems give recursive equations for the system reliability only for the special case when all component probabilities are equal. This paper deals with the problem of calculating the reliability for a (linear or circular) consecutive 2-out-of-r-from-n: F system with unequal component probabilities. We provide two new algorithms for the linear and circular systems which have time complexity of O(n) and O(nr), respectively. The results of some computational experiments are also described.

A problem of synthesizing an optimal file transfer on a file transmission net N is to consider how to distribute, with a minimum total cost, copies of a file J with some information from source vertex set S to all vertices of N by the respective vertices' copy demand numbers. The case of |S| =1 has been studied so far. This paper deals with N such that |S|1, where a forest-type file transfer is defined. This paper proposes a polynomial time algorithm to synthesize an optimal forest-type file transfer on such N satisfying SM U, where M and U are mother vertex set and positive demand vertex set of N, respectively.

A new approach is presented for the detection and computation of a two-dimensional motion field in image sequences. This computational model has a multi-channel motion detector and an optimal motion selector. In the motion detector, each channel has an inherent spatial resolution. The detector computes a two-dimensional motion field by the gradient-based method in parallel. The motion selector compares those candidates of the motion field by a correlation value of the intensity patterns hierarchically arranged from low to high resolution. It then determines the most probable motion for each image point. Experimental results are shown for synthetic images. This model can detect more reliable motion fields than the conventional one-chanel model.

A parallel blower system is quite familiar in hydraulic machine systems and quite often employed in many process industries. It is dynamically dual to the fundamental functional element of digital computer, that is, the flip-flop circuit, which was extensively studied by Moser. Although the global dynamic behaviour of such systems has significant bearing upon system operation, no substantial study reports have hitherto been presented. Extensive research concern has primarily been concentrated upon the local stability of the equilibrium point. In the paper, a piecewise linear model is used to analytically and numerically investigate its manifold global dynamic behaviour. To do this, first the Poincar map is defined as a composition boundary map, each of which is defined as the point transformation from the entry point to the end point of any trajectory on some boundary planes. It was already shown that, in some parameter region, the system exhibits the so-called chaotic states. The chaos generating process is investigated using the above Poincar map and it is shown that the map contains the contracting, stretching and folding operations which, as we often see in many cases particularly in horse shoe map, produce the chaotic states. Considering the one dimensional motions of the orbits by such Poincar map, that is, the stretching and folding operations, a one dimensional approximation of the Poincar map is introduced to more closely and exactly study manifold bifurcation processes and some illustrative bifurcation diagrams in relation to system parameters are presented. Thus it is shown how many types of bifurcations like the Hopf, period doubling, saddle node, and homoclinic bifurcations come to exist in the system.

A new upper hound on the error probability for maximum likelihood sequence estimation of digital signaling on intersymbol interference channels with additive white Gaussian noise is presented. The basic idea is to exclude all parallel error sequences and to exclude some of the overlapping error events from the union bound. It is shown that the new upper bound can be easily and efficiently computed by using a properly labeled error-state diagram and a one-directional stack algorithm. Several examples are presented that compare the new upper bound with bounds previously reported in the literature.

A novel algorithm, as an advanced Hybrid Channel Assignment strategy, for channel assignment problem in a cellular system is proposed. A difference from the conventional Hybrid Channel Assignment method is that flexible fixed channel allocations which are variable through the channel assignment can be performed in order to cope with varying traffic. This strategy utilizes the Channel Rearrangement technique using the artificial neural network algorithm in order to enhance channel occupancy on the fixed channels. The strategy is applied to two simulation models which are the spatial homogeneous and inhomogeneous systems in traffic. The simulation results show that the strategy can effectively improve blocking probability in comparison with pure dynamic channel assignment strategy only with the Channel Rearrangement.

This paper proposes two algorithms for defining a routing domain in multiclass-of-service networks. One an off-line-based method, whose objective is to optimize dynamic routing performance by using precise knowledge on the traffic levels. The algorithm of the proposed method takes into account the random nature of the traffic flow, which is not considered in the network flow approach. The proposed method inherits the conceptual simplicity of the network flow approach and remains applicable to large and complex networks. In simulation experiments, the proposed off-line-based method performs better than the method based on the network flow approach, but has a similar the computation time requirement. The other method proposed here is an on-line-based method for application to B-ISDNs, where precise traffic data is not expected to be available. In this method, the routing domain is defined adaptively according to the network performance (call-blocking probability) measured in real-time. In simulation experiments, the performance of this method is comparable to that of the off-line-based method--especially when highly efficient dynamic routing is used. This paper also derives and describes methods for approximating the implied costs for multiclass-of-service networks. The approximations are very useful not only for off-line-based routing domain definition (RDD) methods but also for other kinds of network controls or optimal network dimensioning based on the concept of revenue optimization.

This paper proposes a functional video handling technique based on structured video. The video handling architecture, which includes a video data structure, file management structure, and visual interface structure, is introduced as the core concept of this technique. One of the key features of this architecture is that the newly proposed video indexing method is performed automatically based on image processing. The video data structure, which plays an important role in the architecture, has two kinds of data structures: content and node. The central idea behind these structures is to separate the video contents from the processing operations and to create links between them. Video indexes work as a backend mechanism in structuring video content. A prototype video handling system called the MediaBENCH, a hypermedia basic environment for computer and human interactions, which demonstrates the actual implementation of the proposed concept and technique, is described. Basic functions such as browsing and editing, which are achieved based on the architecture, exhibit the advantages of structured video handling. The concept and the methods proposed in this paper assure various video-computer applications, which will play major roles in the multimedia field.

In the early stage of hyperthermia, a large number of engineering efforts have been done in the development or the improvement of the heating and temperature measuring techniques. However, they were not always satisfactory clinically. Thus, even in this moment, various engineering researches as well as the electromagnetic techniques for hyperthermia should be build up rapidly. This paper describes some of the highlights of developed or ongoing electromagnetic heating techniques in hyperthermia and identities a trend of emerging electromagnetic heating. Furthermore, the author emphasizes that few medical engineering efforts have been done in the boundary field between pure physics and clinics, and the proper way to develop the hyperthermia equipment is the best use of successes in the three essential regions: Physics, Biology and Clinics.

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.

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.

We carried out a one year field trial of a voice-activated automatic telephone exchange service at KDD Laboratories which has about 200 branch phones. This system has DSP-based continuous speech recognition hardware which can process incoming calls in real time using a vocabulary of 300 words. The recognition accuracy was found to be 92.5% for speech read from a written text under laboratory conditions independent of the speaker. In this paper, we describe the performance of the system obtained as a result of the field trial. Apart from recognition accuracy, there was about 20% error due to out-of-vocabulary input and incorrect detection of speech endpoints which had not been allowed for in the laboratory experiments. Also, we found that the recognition accuracy for actual speech was about 18% lower than for speech read from text even if there were no out-of-vocabulary words. In this paper, we examine error variations for individual data in order to try and pinpoint the cause of incorrect recognition. It was found from experiments on the collected data that the pause model used, filled pause grammar and differences of channel frequency response seriously affected recognition accuracy. With the help of simple techniques to overcome these problems, we finally obtained a recognition accuracy of 88.7% for real data.

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.