Microcellular systems are suitable as personal mobile communication systems because of their high channel re-use efficiency and low transmission power. To implement a microcellular system, the antennas of base stations should be low enough, compared to the buildings around them, to reduce the interference to or from other base stations. In high-speed digital mobile radio communications, the time delay spread caused by multipath propagation is a significant factor in determining the maximum data transmission rate. In the case of a low-antenna-height microcellular system, the propagation characteristics rapidly change when the mobile terminal moves from a line-of-sight (LOS) location to a non-line-of-sight (NLOS) location. In this paper, the time dealy spread characteristics under LOS and NLOS conditions are examined using a geometrical street model which has a reflecting wall at one end of the street on which the base station is located. The RMS delay spreads are calculated using optical ray theory, taking into consideration the wedge diffraction on the street corner. If a reflecting wall exists, the RMS delay spread increases as the mobile terminal moves away from the base station under LOS conditions, or away from the street corner under NLOS conditions. The calculated results agree with the experimental results if measuring equipment noise is taken into consideration.

This paper is concerned with the study of fast-frequency-hopped spread-spectrum multiple-access (FFH-SSMA) digital systems employing antenna diversity and noncoherent binary frequency-shift-keying (FSK) modulation operating through an indoor radio multipath Rayleigh channel. The diversity technique of equal gain combing (EGC) is considered in our study. It is assumed that the frequency-hopping rate is equal to the bit rate.

The problem of test generation for VLSI circuits computationally requires prohibitive costs. Parallel processing on a multiprocessor system is one of available methods in order to speedup the process for such time-consuming problems. In this paper, we analyze the performance of parallel test generation for combinational circuits. We present two types of parallel test generation systems in which the communication methods are different; vector broadcasting (VB) and fault broadcasting (FB) systems, and analyze the number of generated test vectors, the costs of test vector generation, fault simulation and communication, and the speedup of these parallel test generation systems, where the two types of communication factors; the communication cut-off factor and the communication period, are applied. We also present experimental results on the VB and FB systems implemented on a network of workstations using ISCAS'85 and ISCAS'89 benchmark circuits. The analytical and experimental results show that the total number of test vectors generated in the VB system is the same as that in the FB system, the speedup of the FB system is larger than that of the VB, and it is effective in reducing the communication cost to switch broadcasted data from vectors to faults.

For reducing requirement of large memory and minimizing computation complexity in a large-vocabulary continuous speech recognition system, speech segmentation plays an important role in speech recognition systems. In this paper, we formulate the speech segmentation as a two-phase problem. Phase 1 (frame labeling) involves labeling frames of speech data. Frames are classified into three types: (1) silence, (2) consonant and (3) vowel according to two segmentation features. In phase 2 (syllabic unit segmentation) we apply the concept of transition states to segment continuous speech data into syllabic units based on the labeled frames. The novel class of hyperrectangular composite neural networks (HRCNNs) is used to cluster frames. The HRCNNs integrate the rule-based approach and neural network paradigms, therefore, this special hybrid system may neutralize the disadvantages of each alternative. The parameters of the trained HRCNNs are utilized to extract both crisp and fuzzy classification rules. In our experiments, a database containing continuous reading-rate Mandarin speech recorded from newscast was utilized to illustrate the performance of the proposed speaker independent speech segmentation system. The effectiveness of the proposed segmentation system is confirmed by the experimental results.

This paper considers the estimation of speech parameters and their enhancement using an approach based on the estimation-maximization (EM) algorithm, when only noisy speech data is available. The distribution of the excitation source for the speech signal is assumed as a mixture of two Gaussian probability distribution functions with differing variances. This mixture assumption is experimentally valid for removing the residual excitation signal. The assumption also is found to be effective in enhancing noise-corrupted speech. We adaptively estimate the speech parameters and analyze the characteristics of its excitation source in a sequential manner. In the maximum likelihood estimation scheme we utilize the EM algorithm, and employ a detection and an estimation step for the parameters. For speech enhancement we use Kalman filtering for the parameters obtained from the above estimation procedure. The estimation and maximization procedures are closely coupled. Simulation results using synthetic and real speech vindicate the improved performance of our algorithm in noisy situations, with an increase of about 3 dB in terms of output SNR compared to conventional Gaussian assumption. The proposed algorithm also may be noteworthy in that it needs no voiced/unvoiced decision logic, due to the use of the residual approach.

Three techniques are proposed for reducing the time required for protocol processing: protocol data unit management using page management, assembly and disassembly of data packet header and contents in hardware, and rescheduling of protocol processing. These techniques were shown to be feasible by applying them to the TCP/IP over a fiber-distributed data interface network. The maximum communication throughput was 91.6 Mbps; the total throughput for 64 sessions was 89.6 Mbps, only 2% less than the maximum. These techniques will enable the development of more effcient video-on -demand systems.

The up and coming multimedia services are based on real-time high-speed networks. For efficient operation of such services, real-time and precise network management is essential. In this paper, we show that presently available MIB designs are severely inadequate to support real-time network management. We point out and analyze the management constraints and bottlenecks. The concept of quality of management of management information is introduced and its importance in practical network management is discussed. We have proposed a new MIB architecture that will raise the quality of management information to meet the requirements of managing high-speed networks and multimedia services. Experimental results from a prototype implementation of the new MIB architecture are presented.

In future mobile radio, high-speed transmission and efficient spectrum utilization will be important. However, multipath propagation with large delay difference and cochannel interference are obstacles to the advanced mobile communication system. An adaptive antenna can suppress multipath signals and cochannel interference signals. This paper reviews basic performance of multipath fading reduction and cochannel interference suppression using the adaptive antenna. After a brief explanation of adaptive antenna concepts, we show simulation and experimental results of the fading reduction. It is pointed out that the adaptive antenna cancels multipath signals with large delay difference strongly. This feature is very important for high-speed TDMA systems. Moreover, it is shown from simulation results that the adaptive antenna improves the spectrum efficiency by suppressing the cochannel interference signals.

Either GMW sequence or m-sequence possesses a 2-valued auto-correlation function which helps to improve the performance of a RAKE receiver. However, their cross-correlation functions are less well controlled. Before they can be applied to a CDMA system, it is necessary to construct their sub-families (taking advantage of their large family size) which offer satisfactory cross-correlation functions. This paper studies several algorithms for constructing those quasi-optimum sub-families in terms of minimized bit error rate under co-channel interference. The study shows that the performance of resultant sub-families is sensitive to sub-family sizes and algorithms. A new criterion based on combined (even and odd) maximum cross-correlation for code selection is introduced, and highest-peak-deleting and most-peak-deleting algorithms are suggested for constructing quasi-optimum sub-families of GMW and m-sequences.

A protocol completion method is proposed to transform protocols synthesized from service specifications into error-free protocols. Communication service specifications described by message sequence charts can be synthesized into protocols. The synthesized protocols may include latent exceptional behaviors that are beyond the given service specifications. Therefore, even if the service specifications themselves are verified, these exceptional behaviors may produce protocol errors such as deadlock states or unspecified reception. Error-free protocols can be obtained from error-free service specifications by synthesizing and then completing the synthesized protocols. By taking account of each service specification through protocol completion, every exceptional behavior can be detected in the protocol entities including erroneous exceptional behaviors. This function can also be applied to resolution of feature interactions. The proposed method is applied to the synthesis of the X.227 protocol from its partial service specifications.

This paper discusses how to derive message sequence charts (MSCs) from a set of state transition descriptions. Recently, MSC notation has received much attention in the communications software field because it graphically shows system global behavior, So MSC handling techniques are being widely studied. These studies have recommended the design a system by a set of formal MSCs in the early stages of development and then to convert them into state transition descriptions. However, it is difficult to apply those results to existing communications software products. This is because these systems are designed based on state transition descriptions and there are no formal MSCs for them. In this paper, we propose a method of deriving MSCs based on optimized reachability analysis. This method generates MCSs that avoid state explosion. A case study using Q.931 protocol shows the feasibility of this method.

When a natural language specification is translated into a formal one, it is important for objects and operations appearing in the natural language specification to be appropriately classified according to the framework of data types in the formal specification. In this paper, we propose a semi-automatic method of constructing a context-free grammar (cfg) representing an assignment of data types to words in a given natural language specification. In our method, a cfg is mechanically constructed from sample sentences in a natural language specification, where the cfg represents type declarations of expressions and type hierarchy. Then, the cfg is appropriately modified by adding nonterminals/production rules that represent type inclusion relations. In this modification process, candidates for the productions to be added are presented to the user. Finally, the cfg is simplified based on structural equivalence. The result of applying this method to a part of the OSI session protocol specification (39 sentences) is also presented. There was an example in which ambiguity of anaphoric bindings was solved by type checking based on the resulting cfg.

The objective of this paper is to provide an effective approach to infrared spectrum recognition. Traditionally, recognizing infrared spectra is a quantitative analysis problem. However, only using quantitative analysis has met two difficulties in practice: (1) quantitative analysis generally very complex, and in some cases it may even become intractable; and (2) when spectral data are inaccurate, it is hard to give concrete solutions. Our approach performs qualitative reasoning before complex quantitative analysis starts so that the above difficulties can be efficiently overcome. We present a novel model for qualitatively decomposing and analyzing infrared spectra. A list of candidates can be obtained based on the solutions of the model, then quantitative analysis will only be applied to the limited candidates. We also present a novel model for handling inaccuracy of spectral data. The model can capture qualitative features of infrared spectra, and can consider qualitative correlations among spectral data as evidence when spectral data are inaccurate. We have tested the approach against about 300 real infrared spectra. This paper also introduces the implementation of the approach.

In this paper we propose an effective ratebased virtual clock (ERVC) scheduling algorithm which is applied to the switching nodes in the connection-oriented high-speed networks. It is based on the effective rate which has a value between the average and peak transmission rates. The algorithm is simple but overcomes the defects of original virtual-clock algorithm. Performance results demonstrate the effectiveness of the ERVC algorithm in comparison with other methods.

Intricate Speech Communication Mode (I-SC Mode) is observed in verbal interaction during ISDN-TV conferencing. It is characterized by conflicts and multiple interactions of speech. I-SC Mode might cause mental stress to participants and be obstacles for smooth communication. However, the reasons of I-SC Mode on the environment of information transmission are hitherto unknown. Furthermore, analyses on the talks inside a conference site (LT: local talk or a talk inside a local site) and between remote sites (MT: media talk or a talk between remote sites) are originally conceived on assumed differences in cognitive distance and media intimacy. This study deals with communication effects/barriers and cognitive distance/intimacy of media correlated with audio-video transmission signals and speech modes or talk types and response delay in human speech interactions by using an innovated conference model (decision-making transaction model: DT-Model) in synchronous ISDN-TV conference systems (SYN) and asynchronous ones (ASYN). The effects of intricate communication can be predicted to a certain extent and in some ways. In I-SC Mode, because a timely answer can not be received from recipients (or partner), response time delay and response rate are analyzed. These factors are thus analyzed with an innovated dynamic model, where the recognizable acceptance of delay is evaluated. The nonlinear model shows that the larger the response time delay, the lower the response rate becomes. Comparing the response rate between SYN and ASYN, the latter is notably lower than the former. This indicates that the communication efficiency is lower in ASYN. An I-SC Mode is the main mode that occurs during ASYN conferences, and this in turn causes psychological stress. Statistics show the prevalence of a high incidence of complicated plural talks and a low response rate exists as the main factors preventing smooth human-to-human communication. Furthermore, comparing the response delays in face-to-face LT (Tf) and machine-mediated MT (Tm), human communication delay is significantly extended by the effects of initial mechanical delays. Therefore, cognitive intimacy of media is clearly affected by the existence of physical distance.

This paper discusses the fixed-point smoothing and filtering problems given lumped covariance function of a scalar signal process observed with additive white Gaussian noise. The recursive Wiener smoother and filter are derived by applying an invariant imbedding method to the Volterra-type integral equation of the second kind in linear least-squares estimation problems. The resultant estimators in Theorem 2 require the information of the crossvariance function of the state variable with the observed value, the system matrix, the observation vector, the variance of the observation noise and the observed value. Here, it is assumed that the signal process is generated by the state-space model. The spectral factorization problem is also considered in Sects. 1 and 2.

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 paper reports a 32k32 1-Mbit CMOS synchronous pipelined burst SRMA. A clock access time of 3.6 ns and a minimum cycle time of 9 ns(111 MHz operation) were obtained. An active current of 210 mA at 111 MHz and a standby current of 2 µA were successfully realized. These results can be obtained by a new activation control method in which the internal clock pulses control the decoders, the low resistive bit line and memory cell GND line and the optimization of write recovery timing and data sense timing.

We propose a speech recognition method using fusion of auditory and visual information for accurate speech recognition. Since we use both auditory information and visual information, we can perform speech recognition more accurately in comparison with the case of either auditory information or visual information. After processing each information by HMM, they are fused by linear combination with weight coefficient. We performed experiments and confirmed the validity of the proposed method.

This paper describes a new and realisable speech enhancement structure which simulates the cocktail party effect with a modified iterative Wiener filter and a multi-layer perceptron neural network. The key idea is to use the neural network as a speaker recognition system to govern the iterative Wiener filter. The neural network is a modified perceptron with a hidden layer using feature date extracted from LPC cepstral analysis. The proposed technique has been successfully used for speech enhancement when the interference is competing speech or broad band noise.