The process of room acoustic planning & design can be aided by Binaural Technology. To this end, a three-stage modelling process is proposed that consists of a "sound"-specification phase, a design phase and a work-plan phase. Binaural recording, reproduction and room simulation techniques are used throughout the three phases allowing for subjective/objective specification and surveillance of the design goals. The binaural room simulation techniques involved include physical scale models and computer models of different complexity. Some basics of binaural computer modelling of room acoustics are described and an implementation example is given. Further the general structure of a software system that tries to model important features of the psychophysics of binaural interaction is reported. The modules of the model are: outer-ear simulation, middle-ear simulation, inner-ear simulation, binaural processors, and the final evaluation stage. Using this model various phenomena of sound localization and spatial hearing, such as lateralization, multiple-image phenomena, summing localization, the precedence effect, and auditory spaciousness, can be simulated. Finally, an interesting application of Binaural Technology is presented, namely, a so called Cocktail-Party-Processor. This processor uses the predescribed binaural model to estimate signal parameters of a desired signal which may be distored by any type of interfering signals. In using this strategy, the system is able to even separate the signals of competitive speakers.

This paper describes a new trial of dynamical parameter estimation for the actual room acoustic system, in a practical case when the input excitation is polluted by a background noise in contrast with the usual case when the output observation is polluted. The room acoustic system is first formulated as a discrete time model, by taking into consideration the original standpoint defining the system parameter and the existence of the background noise polluting the input excitation. Then, the recurrence estimation algorithm on a reverberation time of room is dynamically derived from Bayesian viewpoint (based on the statistical information of background noise and instantaneously observed data), which is applicable to the actual situation with the non-Gaussian type sound fluctuation, the non-linear observation, and the input background noise. Finally, the theoretical result is experimentally confirmed by applying it to the actual estimation problem of a reverberation time.

Inverse filters can be designed in order to enhance the accuracy with which signals recorded in a given space can be reproduced in a given listening space. The problem is considered here of the design of an inverse filter matrix which enables K recorded signals to be accurately reproduced at K points in the listening space when transmitted via M loudspeaker channels. The analysis is sufficiently general to incorporate the case when the best (least squares) approximation is sought to the reproduction of K signals at L points in the space when LK. An analysis is presented which demonstrates that the approach suggested by the Multiple-Input/Output Inverse Filtering theorem of Miyoshi and Kaneda can be realised adaptively by using the Multiple Error LMS algorithm of Elliott et al.

The realization of acoustic inverse filter is often difficult because of the non-minimum phase property and the long time duration of the impulse response of the acoustic enclosure. However, if the signals are divided into a large number of sub-bands, many of the sub-bands are found to be invertible. The invertibility of a sub-band signal depends on the zero distribution of the transfer function in the z-plane. In a multi-microphone system, the transfer functions between the sound source and the mirophones have different zero distributions. The method proposed here, taking advantage of the differences of zero distributions, selects the best invertible microphone in each sub-band, and reconstructs the full band signal by summing up the inverse filtered sub-band signals of the best microphones. The quality of the dereverberated signal using the proposed inverse filtering approach is improved with increasing number of microphones and sub-bands. When seven microphones are used and the number of sub-bands is 513, the quality of the dereverberated speech signals are almost the same with the original ones even when the revergeration time is about one second. The introduction of multi-microphones in addition to sub-band processing provides a new way of dealing with the non-minimum phase problem in deconvolution.

This paper proposes a method to estimate the waveform of a specified sound source in a noisy and reverberant environment using a sensor array. Previously, we proposed an iterative method to estimate the waveform. However, in this method the effect of reflection sound reduces to 1/M, where M is the number of microphones. Therefore, to solve the reverberation problem, we propose a new method using inverse filters of the transfer functions from the sound sources to each microphone. First, the transfer function from each sound source to each microphone is measured by the cross-spectrum technique and each inverse filter is calculated by the QR method. Then the initially estimated waveform of a sound source is the averaged signal of the inverse filter outputs. Since this waveform still contains the effects of the other sound sources, the iterative technique is adopted to estimate the waveform more precisely, reducing the effects of the other sound and the reflection sound. Some computer simulations and experiments were carried out. The results show the effectiveness of our method.

This paper proposes a new adaptive algorithm of the FIR type digital filter for an acoustic echo canceller and similar application fields. Unlike an echo canceller for line, an acoustic echo canceller requires a large number of taps, and it must work appropriately while it is driven by colored input signal. By controlling the filter tap length and updating filter coefficients multiple times during a single sampling interval, the proposed algorithm improves the convergence characteristics of adaptation even if colored input signal is introduced. This algorithm is maned VT-LMS after variable tap length LMS. The results of simulation show the effectiveness of the proposed algorithm not only for white noise but also for colored input signal such as speech. The VT-LMS algorithm has better convergence characteristice with very little extra computational load compared to the conventional algorithm.

This paper proposes a new adaptive algorithm for acoustic echo cancellers with four times the convergence speed for a speech input, at almost the same computational load, of the normalized LMS (NLMS). This algorithm reflects both the statistics of the variation of a room impulse response and the whitening of the received input signal. This algorithm, called the ESP (exponentially weighted step-size projection) algorithm, uses a different step size for each coefficient of an adaptive transversal filter. These step sizes are time-invariant and weighted proportional to the expected variation of a room impulse response. As a result, the algorithm adjusts coefficients with large errors in large steps, and coefficients with small errors in small steps. The algorithm is based on the fact that the expected variation of a room impulse response becomes progressively smaller along the series by the same exponential ratio as the impulse response energy decay. This algorithm also reflects the whitening of the received input signal, i.e., it removes the correlation between consecutive received input vectors. This process is effective for speech, which has a highly non-white spectrum. A geometric interpretation of the proposed algorithm is derived and the convergence condition is proved. A fast profection algorithm is introduced to reduce the computational complexity and modified for a practical multiple DSP structure so that it requires almost the same computational load, 2L multiply-add operations, as the conventional NLMS. The algorithm is implemented in an acoustic echo canceller constructed with multiple DSP chips, and its fast convergence is demonstrated.

This paper relates to a novel algorithm for fast estimation of the coefficients of the adaptive FIR filter. The novel algorithm is derived from a first order IIR filter experssion clarifying the estimation process of the NLMS (normalized least mean square) algorithm. The expression shows that the estimation process is equivalent to a procedure extracting the cross-correlation coefficient between the input and the output of an unknown system to be estimated. The interpretation allows to move a subtraction of the echo replica beyond the IIR filter, and the movement gives a construction with the IIR filter coefficient of unity which forms the arithmetic mean. The construction in comparison with the conventional NLMS algorithm, improves the covergence rate extreamly. Moreover, when we use the construction with a simple technique which limits the term of calculating the correlation coefficient in the beginning of a convergence process, the convergence delay becomes negligible. This is a very desirable performance for acoustic echo canceller. In this paper, double-talk and echo path fluctuation are also studied as the first stage for application to acoustic echo canceller. The two subjects can be resolved by introducing two switches and delays into the evaluation process of the correlation coefficient.

An acoustic echo canceller that also cancels room noise is proposed. This system has an additive (noise reference) input port, and a noise canceller (NC) precedes the echo canceller (EC) in a cascade configuration. The adaptation control problem for the cascaded echo and noise canceller is solved by controlling the adaptation process to match the occurrence of intermittent speech/echo; the room noise is a stationary signal. A simulation shows that adaptation using the NLMS algorithm is very effective for the echo and noise cancellation. Sub-band cancelling techniques are utilized. Noise cancellation is realized with a lower band EC. Hardware is implemented and its performance evaluated through experiments under a real acoustic field. The combination of the EC with NC maintains excellent performance at all echo to room noise power ratios. It is shown that the proposed canceller overcomes the disadvantages traditionally associated with ECs and NSc.

This paper describes a nonstationary spectral analysis method and its application to prognosis and diagnosis of automobiles. An instantaneous frequency spectrum is considered first at a single point of time based on the instantaneous representation of autocorrelation. The spectral distortion is then considered on two-dimensional spectrum, and the filtering is introduced into the instantaneous autocorrelations. By the above procedure, the Instantaneous Covariance method (ICOV), the Instantaneous Maximum Entropy Method (IMEM), and the Wigner method are shown and they are unified. The IMEM is used for the time-dependent spectral estimation of vibration and acoustic sound signals of automobiles. A multi-dimensional (M-D) space is composed based on the variables which are obtained by the IMEM. The M-D space is transformed into a simple two-dimensional (2-D) plane by a projection matrix chosen by the experiments. The proposed method is confirmed useful to analyze nonstationary signals, and it is expected to implement automatic supervising, prognosis and diagnosis for a traffic system.

This paper describes the application of adaptive filter and wave equalization technology to acoustics, and to noise reduction of a machine using acoustic field control. Firstly, some problems inherent in applying active noise control (ANC) technology to noise reduction in consumer products are pointed out. In particular, the behavior of Error-Adaptive Control, as named by the authors, is analyzed precisely. Secondly, the relationship between coherence and the performance of active control is investigated. The fact that coherence is large or small is more effective for ANC when adaptive control is used rather than fixed-coefficient filter control. The effects of sound spatial coherence on adaptive ANC are studied precisely. The study looks into the relationship between minimum mean square error and input signal variance, or coherence, which has been measured previously. In three-dimensional spatial control, several microphones and speakers are needed for ANC, and several acoustic paths are present. ANC performance in three-dimensional space was evaluated by multiple coherence, which shows the degree of multiple spatial correlation. Thirdly, the paper describes the application of ANC technology to compressor noise in a refrigerator, a mass product. The problem was solved by treating the machine chamber as a one-dimensional duct, preventing howl, and using Error-Adaptive control. The second application is to fan noise in a small device. The authors discovered that the spatial coherence of the sound is low in the vicinity of the fan. This causes ANC to operate at a low level.

A review is presented of the fundamental principles underlying modern techniques for the active control of acoustic noise. The basic physical principles are first dealt with in the context of the active control of free field radiation and the classical approaches to the problem are briefly discussed. The active control of sound fields in ducts and enclosures is also described and the inherent physical limitations of the technique are emphasised. Modern signal processing methods for realising feedforward control systems are also outlined and least squares formulations are presented which enable performance limits to be established and adaptive algorithms to be derived.

We discuss fault tolerance of an information disseminating scheme, t-disseminate on a network with N processors, where each processor can send a message to t directions at each round. When N is a power of t+1 and at most tlog_t+1N-1 (at most t) processors and/or edges have hailed, log_t+1N+(f1)/t rounds (log_t+1N+2 rounds) suffice for broadcasting information to all destinations from any source by t-disseminate. For a arbitrary N, log_t+1N2f/t1 rounds (log_t+1N+2 rounds) suffice for broadcasting information to all destinations from any source by t-disseminate if at most t(log_t+1N1)/2 (at most t/2) processors and/or edges have failed.

Existing solid models often contain redundant primitives and null blocks, which both slows down the rendering process and makes the process complex. There has been recent progress toward solving this problem, but existing modeling schemes cannot support eliminating all the redundancies, especially the null blocks, from the solid models. This paper proposed a technique that can eliminate redundancies. By dividing a primitive into some surface dispersed points, a new primitive representation is obtained. The sample segments of the primitive or the object are used to locate composition position to prevent the null primitives from being generated. By drawing out the geometric shape points set corresponding to a common acting area, the volume boundary of a primitive or an object is evaluated by only the Boolean set operations. The null blocks can be picked out in terms of the volume boundary. The resulting solid model generated in this way has no redundancies and is suitable for fast rendering of the image.

This paper presents a new method for estimating both the parameters of a nonminimum phase system and its unknown input signal. An approximate inverse system method is used to estimate the unknown input signal, and then, by using a Kalman filter, approximately consistent parameter estimates of the nonminimum phase system can be obtained effectively. This method can be used to estimate the parameters of a nonminimum phase system and a minimum phase one in the case when the input signal is a white noise or an impulse sequence.

This article discusses a synthesis procedure of a discrete-time asynchronous neural network whose information is a limit cycle. The synthesis procedure uses a novel connection matrix and can be reduced into a linear epuation. If all elements of desired limit cycles are independent at each transition step, the equation can be solved and all desired limit cycles can be stored. In some experiments, our procedure exhibits much better storing performance than previous ones.

This paper presents an efficient algorithm for computing the capacity of discrete memoryless channels. The algorithm uses Newton's method which is known to be quadratically convergent. First, a system of nonlinear equations termed Kuhn-Tucker equations is formulated, which has the capacity as a solution. Then Newton's method is applied to the Kuhn-Tucker equations. Since Newton's method does not guarantee global convergence, a continuation method is also introduced. It is shown that the continuation method works well and the convergence of the Newton algorithm is guaranteed. By numerical examples, effectiveness of the algorithm is verified. Since the proposed algorithm has local quadratic convergence, it is advantageous when we want to obtain a numerical solution with high accuracy.

Actual debugging actions during the testing phase in the software development and the operation phase are not always performed perfectly. In other words, all detected software faults are not corrected and removed certainly. Generally, this is called imperfect debugging. In this paper, we discuss a software reliability growth model considering imperfect debugging that faults are not always corrected/removed when they are detected. Defining a random variable representing the cumulative number of faults corrected up to a specified testing time, this model is described by a semi-Markov process. We derive various quantitative measures for software reliability assessment and show their numercal examples.

Fahlman and Lebiere's (FL) learning algorithm begins with a two-layer network and in course of training, can construct various network architectures. We applied FL algorithm to the same three-layer network architecture as a back propagation (BP) network and compared their generalization properties. Simulation results show that FL algorithm yields excellent saturation of hidden units which can not be achieved by BP algorithm and furthermore, has more desirable generalization ability than that of BP algorithm.