This paper evaluates the performance of a reliable multicast protocol for bulk-data transfer over unreliable networks via IP-multicast. Bulk-data type reliable multicast appears promising for commercial publishing and large-scale data replication. The proposed reliable multicast transport protocol (RMTP) provides high-performance due to the use of IP multicast while also providing confirmed and error free transfer by end-to-end controls. The protocol includes a multi-round selective repeat scheme dedicated for bulk-data multicast applications. This paper examines the multicast retransmission procedures in RMTP through analysis and tests on an implemented system and clarifies the basic performance behavior of the protocol. Evaluations are conducted with regard to retransmission redundancy, transfer time, and packet processing load with various error conditions and number of receivers. Against the response concentration problem seen in end-to-end communication, the backoff time algorithm is applied to the protocol; the limits it places on system scalability are clarified.

This paper proposes an adaptive microphone array using blind deconvolution. The method realizes an signal enhancement based on the combination of blind deconvolution, synchronized summation and DSA (Delay-and-Sum Array) method. The proposed method improves performance of estimation by the iterative operation of blind deconvolution using a cost-function based on the coherency function.

In this paper we present a complete methodology for efficient electro-mechanical characterization of a CMOS compatible MEMS technology. Using an original test structure, the so-called "U-shape cantilever beam," we are able to determine all mechanical characteristics of force sensors constituted with elementary beams in a given technology. A complete set of electro-mechanical relations for the design of Microsystems have also been developed.

In order that the speech recognition system might have a high performance in the noisy environment, the directional microphone arrays at the input of the system have been broadly investigated. The purpose of this study is to develop a new wide-band directional microphone system in view of advancing to an adaptive one afterwards. In the proposed system, three microphones are arranged on a straight line and the beamforming is accomplished in such a way that the output value of the middle microphone is added to the integrated value of the difference between two microphones at both sides. In this study, the signal processing of microphone outputs is implemented by using active RC circuits. Finally, the objective directivity can be experimentally obtained in wide frequency ranges required for the speech recognition.

The optimistic consistency scheme has been established with respect to data consistency and availability in distributed systems. The nomadic data consistency model using version vectors to support data versioning for data synchronization and concurrent conflict detection is suitable for an optimistic replication system that supports large-scale wireless networks. This paper describes the architecture and its data consistency model using data versioning and its access domain control targeted for nomadic data sharing systems, such as collaborative works using database and messaging, and the data transfer optimizations of the model. We evaluate our data versioning scheme comparing with a traditional data versioning and the data transfer optimization by estimation and measurement assuming a mobile worker's job. We generate arithmetic formulas for data transfer estimation using the optimizing techniques and apply them to large-scale data sharing configurations in which collaboration groups are dynamically formed and data is exchanged in each group. The data versioning with an access domain increases flexibility in data sharing configurations, such as mobile collaboration systems and client/server type mobile systems. We confirmed that the combination of the general optimizations and the access domain configurations based on our data consistency model is applicable for large-scale mobile data sharing systems.

Under a contamination of background sound noises, it seems difficult especially in a real working situation to evaluate various type statistics of only an objective sound signal fluctuation. In many cases of the noise evaluation, some signal processing method have been employed to eliminate the effect of background sound noises by first measuring emitted sound levels. In this study, a new evaluation method of sound level fluctuation is proposed in principle on the basis of the measurement of heterogeneous physical quantity other than sound pressures or sound levels to eliminate the effect of background sound noises. Though the theoretical analysis on acoustical emission caused by a mechanical vibration seems very difficult in a working situation, the sound noise fluctuation emitted only from an objective sound source can be effectively evaluated through its related vibration measurement by employing a fairly unified stochastic method proposed on the basis of a generalized regression analysis between sound and vibration. Here, the regression coefficients are determined by employing the least squares error method to minimize the mean square of estimation error to illustrate well the sound data by means of vibration data. Finally, the effectiveness of proposed method has been experimentally applied to the sound noise evaluation of a jigsaw.

As network services become more diverse and powerful, service applications that perform such services are acquiring an ever-larger amount of complicated and changeable relationships. We present a network dependence graph (NDG) that captures both data and control flow relationships between components of service applications that work collaboratively. This graph is constructed based on analysis of both the behavior of each of the service applications and their configuration, which describes the device names they refer to, and allows network slicing to be implemented as a simple graph traversal. Network slicing is the extraction of necessary and minimum service components that may affect the execution of a specified service application; it helps a network manager to find the location of service faults lurking somewhere in the network. We also present a method for locating faults that uses network slicing and a system based on this method.

A new method of designing a microphone array with two outputs preserving binaural information is proposed in this paper. This system employs adaptive beamforming using multiple constraints. The binaural cues may be preserved in the two outputs by use of these multiple constraints with simultaneous beamforming to enhance target signals is also available. A computer simulation was conducted to examine the performance of the beamforming. The results showed that the proposed array can perform both the generation of the binaural cues and the beamforming as intended. In particular, beamforming with double-constraints exhibits the best performance; DI is around 7 dB and good interchannel (interaural) time/phase and level differences are generated within a target region in front. With triple-constraints, however, the performance of the beamforming becomes poorer while the binaural information is better realized. Setting of the desired responses to give proper binaural information seems to become critical as the number of the constraints increases.

This paper shows the applicability of the integral equation formulation of the measured equation of invariance (IE-MEI) to two-dimensional dielectric scatterers. That is, a relationship between the scattered electric and magnetic fields, which is derived from the new formulation of the IE-MEI, is applicable to lossless dielectric materials as well as perfect electric conductors (PEC). In addition, we show that the IE-MEI does not suffer from internal resonance problems. These two facts are validated by numerical examples for a circular cylinder and a square cylinder illuminated by Transverse Magnetic (TM) plane wave or a TM line source very close to the scatterers. The numerical results calculated by the IE-MEI agree well with the ones by moment methods that employ combined field formulations with exact boundary conditions.

The conventional linear prediction can be viewed as a constrained blind equalization problem that has gained a lot of interests along with development of telecommunication networks. Because the blind equalization or deconvolution is a general framework of the inverse problem, the reliable and faster algorithm is requested in many applications. This paper proposes an orthogonal wavelet transform domain realization of a blind equalization technique termed as EVA, and presents an application to speech analysis. An orthogonal transformation has no influence to the equalization result in general, but we show that a particular wavelet makes the matrix in EVA nearly lower triangular that promotes the faster convergence in the estimation of maximum eigenvalue and its associate vector in EVA iteration. The experiments with the Japanese vowels show that the the proposed method effectively separates the glottis and vocal tract information, hence is promising for speech analysis.

A compact new test structure using shift register circuits for extracting components of the capacitance matrix of the multi-layer interconnections has been proposed. An extraction method of the capacitance matrix is also presented. As a result of fabrication, capacitance values obtained by measurement are in good agreement with the numerical calculation. We also showed an estimation method of the measurement errors.

We show by numerical calculations that a chaotic neuron model driven by a weak sinusoid has resonance. This resonance phenomenon has a peak at a drive frequency similar to that of noise-induced stochastic resonance (SR). This neuron model was proposed from biological studies and shows a chaotic response when a parameter is varied. SR is a noise induced effect in driven nonlinear dynamical systems. The basic SR mechanism can be understood through synchronization and resonance in a bistable system driven by a subthreshold sinusoid plus noise. Therefore, background noise can boost a weak signal using SR. This effect is found in biological sensory neurons and obviously has some useful sensory function. The signal-to-noise ratio (SNR) of the driven chaotic neuron model is improved depending on the drive frequency; especially at low frequencies, the SNR is remarkably promoted. The resonance mechanism in the model is different from the noise-induced SR mechanism. This paper considers the mechanism and proposes possible explanations. Also, the meaning of chaos in biological systems based on the resonance phenomenon is considered.

An Acoustic echo canceller has problems adaptating under noisy or double-talk conditions. The adaptation process requires a precise identification of the temporarily changed room impulse response. To do this, both minimizing the step size parameter of the Least Mean Square (LMS) method to be as small as possible and giving up on updating the adaptive filter coefficients have been considered. This paper describes an adaptive cross-spectral technique that is robust to adaptive filtering under noisy or double-talk conditions and for colored signals such a speech signal. The cross-spectral technique was originally developed to measure the impulse response in a linear system. Here we apply in the adaptive cross-spectral technique to solve the acoustic echo cancelling problem. This cross-spectral technique takes the ensemble average of the cross spectrum between input and error signals and the averaged cross spectrum is divided by the averaged power spectrum of the input signal to update the filter coefficients. We have confirmed that the echo signal is suppressed by about 15 dB even under double-talk conditions. We also explain that this method has a systematic error due to using a short time block for estimating the room impulse response. Then we investigate overlapping every last half block by the following first half block in order to reduce the effect of the systematic error. Finally, we compare our method with the Frequency-domain Block LMS (FBLMS) method because both methods are implemented in the frequency domain using a short time block.

This paper proposes a phase-rotating phase-shift keying (PSK) modulation and shows that its narrow-band version is suitable for Viterbi equalization. The proposed PSK has the following features: 1) a spectrum shaping of the transmit/receive filters does not need to be restricted to the Nyquist criterion; 2) the transmitted data sequence is rotated for every symbol in order to reduce noise-correlation at the receiver. First, this paper discusses a performance degradation of bit error rate of Viterbi equalizers in the presence of the sampling timing offset or under time-dispersive frequency selective fading. Next, computer simulation confirms that π/2-shifted binary PSK with narrow-band spectrum shaping filter, which includes offset QPSK for its special case, solves the above mentioned performance degradation, keeping good spectrum efficiency equal to M-ary PSK.

The self-healing capability against network failure is one of indispensable features for the B-ISDN infrastructure. One problem in realizing such self-healing backbone network is the inefficient utilization of the large spare capacity designed for the failure-restoration purpose since it will be used only in the failure time that does not occur frequently. "Pool-capacity" is the concept that allows some VPs (virtual paths) to efficiently utilize this spare capacity part. Although the total capacity can be saved by using the "Pool Capacity," it is paid by less reliability of VPs caused by the emerging influence of indirect-failure. Thus, this influence of indirect-failure has to be considered in the capacity designing process so that network-designers can trade off the saving of capacity with the reliability level of VPs in their self-healing networks. In this paper, Damage Rate:DR which is the index to indicate the level of the influence caused by indirect-failure is defined and the pool-capacity design scheme with DR consideration is proposed. By the proposed scheme, the self-healing network with different cost (pool-capacity) can be designed according to the reliability level of VPs.

In the basic user/network interface of ISDN (ITU-T Recommendation I. 430), the D-channel is shared by up to 8 terminals for signal and data packets. An analytical model is proposed to reveal the performance characteristics of the access control scheme for the D-channel. Numerical and simulation results are shown to demonstrate the performance differentiation of the terminals with different priorities. It is observed that the mean signal delay at low load may become large because of long service time for packets, and that the priority mechanism may not work properly when the loads at terminals are very asymmetric.

This paper proposes a new robust adaptive beamformer applicable to microphone arrays. The proposed beamformer is a generalized sidelobe canceller (GSC) with a variable blocking matrix using coefficient-constrained adaptive filters (CCAFs). The CCAFs, whose common input signal is the output of a fixed beamformer, minimize leakage of the target signal into the interference path of the GSC. Each coefficient of the CCAFs is constrained to avoid mistracking. In the multiple-input canceller, leaky adaptive filters are used to decrease undesirable target-signal cancellation. The proposed beamformer can allow large look-direction error with almost no degradation in interference-reduction performance and can be implemented with a small number of microphones. The maximum allowable look-direction error can be specified by the user. Simulation results show that the proposed beamformer, when designed to allow about 20of look-direction error, can suppress interference by more than 17 dB.

Enhancement of resonance is shown by coupling and summing in sinusoidally driven chaotic neural networks. This resonance phenomenon has a peak at a drive frequency similar to noise-induced stochastic resonance (SR), however, the mechanism is different from noise-induced SR. We numerically study the properties of resonance in chaotic neural networks in the turbulent phase with summing and homogeneous coupling, with particular consideration of enhancement of the signal-to-noise ratio (SNR) by coupling and summing. Summing networks can enhance the SNR of a mean field based on the law of large numbers. Global coupling can enhance the SNR of a mean field and a neuron in the network. However, enhancement is not guaranteed and depends on the parameters. A combination of coupling and summing enhances the SNR, but summing to provide a mean field is more effective than coupling on a neuron level to promote the SNR. The global coupling network has a negative correlation between the SNR of the mean field and the Kolmogorov-Sinai (KS) entropy, and between the SNR of a neuron in the network and the KS entropy. This negative correlation is similar to the results of the driven single neuron model. The SNR is saturated as an increase in the drive amplitude, and further increases change the state into a nonchaotic one. The SNR is enhanced around a few frequencies and the dependence on frequency is clearer and smoother than the results of the driven single neuron model. Such dependence on the drive amplitude and frequency exhibits similarities to the results of the driven single neuron model. The nearest neighbor coupling network with a periodic or free boundary can also enhance the SNR of a neuron depending on the parameters. The network also has a negative correlation between the SNR of a neuron and the KS entropy whenever the boundary is periodic or free. The network with a free boundary does not have a significant effect on the SNR from both edges of the free boundaries.

In this paper, we propose a new competitive learning algorithm for training single-layer neural networks to cluster data. The proposed algorithm adopts a new measure based on the idea of "symmetry" so that neurons compete with each other based on the symmetrical distance instead of the Euclidean distance. The detected clusters may be a set of clusters of different geometrical structures. Four data sets are tested to illustrate the effectiveness of our proposed algorithm.

Today, many kinds of real-time applications are available over IP networks. It is important to measure the network performance for such applications before making use of real applications. Authors developed the general purpose traffic measurement tool for IP networks. This system can generate any kinds of traffic flexibly and calculate the network performance such as throughput, delay and loss ratio according to received packets. In this paper, the concept of this traffic measurement tool is described in detail, and several examples of network measurements are shown.