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Abstract - AE1

AE1.1	Head-Related Transfer Function Modeling in 3-D Sound Systems with Genetic Algorithms N. Cheung, S. Trautmann (Texas Instruments Tsukuba R&D Center, Japan); A. Horner (Hong Kong University of Sci & Tech, P R China) Head-related transfer functions (HRTFs) describe the spectral filtering that occurs between a source sound and the listener's eardrum. Since HRTFs vary as a function of relative source location and subject, practical implementation of 3D audio must take into account a large set of HRTFs for different azimuths and elevations. Previous work has proposed several HRTF models for data reduction. This paper describes our work in applying genetic algorithms to find a set of HRTF basis spectra, and the normal equation method to compute the optimal combination of linear weights to represent the individual HRTFs at different azimuths and elevations. The genetic algorithm selects the basis spectra from the set of original HRTF amplitude responses, using an average relative spectral error as the fitness function. Encouraging results from the experiments suggest that genetic algorithms provide an effective approach to this data reduction problem.
AE1.2	A Bottle Model for Head-Related Transfer Functions B. Ferguson, R. Bogner, S. Wawryk (University of Adelaide, Australia) We describe a parsimonious model for the direction-dependent transfer function of the pinna. The model describes the transfer function with reference to resonators located in particular physical positions relative to the ear canal. The purpose of the work is to provide a parametric model that permits identification with moderate data-gathering, and filter specification for any direction without the need for interpolation of responses.
AE1.3	Simulation of Three-Dimensional Sound Propagation with Multidimensional Wave Digital Filters T. Schetelig, R. Rabenstein (University Erlangen, Germany) The propagation of sound waves is described by partial differential equations for the acoustic pressure and the acoustic fluid velocity. The solution depends on the shape of the enclosure and on the boundary conditions. Among various methods for the discretization of partial differential equations, the multidimensional wave digital filter approach is known to yield robust algorithms for the discrete simulation of continuous problems. This paper describes the derivation of a discrete model for three-dimensional sound propagation according to multidimensional wave digital filtering principles. The correct treatment of boundary conditions for various wall impedances is shown. A numerical example for the sound propagation in three interconnected rooms of a building demonstrates the capabilities of the method.
AE1.4	Optimum Loudspeaker Spacing for Robust Crosstalk Cancellation D. Ward, G. Elko (Bell Labs, Lucent Technologies, USA) Crosstalk cancellation is a signal processing technique whereby two (or more) loudspeakers are used to deliver desired signals exactly at the listener's ears. Such a system is useful for 3D audio applications, and removes the requirement for the listener to wear headphones. However, crosstalk cancelers are notoriously non-robust to slight movements in head position, and there currently e xists no clear method for determining the best loudspeaker placement in a given situation. In this paper we propose a robustness measure to evaluate the performance of crosstalk cancelers as a function of loudspeaker spacing. Based on this analysis we conclude that certain loudspeaker spacings give far better robustness performance, and provide a simple empirically-derived equation for determining the optimum loudspeaker spacing in a given situation.
AE1.5	Mean Weight Behavior of the Filtered-X LMS Algorithm O. Tobias, J. Bermudez (Universidade Federal de Santa Catarina, Brazil); N. Bershad (University of California, Irvine, USA); R. Seara (Universidade Federal de Santa Catarina, Brazil) This paper presents a stochastic analysis of the Filtered-X LMS algorithm. The mean weight vector recursion is derived for slow adaptation and for a white reference signal without use of independence theory. The Wiener solution is determined explicitly as a function of the input statistics and the impulse responses of the primary and secondary signal paths. It is shown that the steady-state mean weights for the Filtered-X LMS algorithm converge to the Wiener solution only if the estimate of the secondary path is without error. Monte Carlo simulations show excellent agreement with the behavior predicted by the theoretical model.
AE1.6	A Method of Optimizing Source Configuration in Active Control Systems Using Gram-Schmidt Orthogonalization F. Asano (Electrotechnical Laboratory, Japan); Y. Suzuki (R.I.E.C Tohoku University, Japan); D. Swanson (A.R.L Pennsylvania State University, USA) In this paper, a method for optimizing the number and the configuration of control sources in an active control system is proposed. In the optimization process, sources are selected one by one so that the corresponding transfer impedance vector is the most linearly independent. From the results of the simulation, it is shown that the optimized configuration yields not only small average control error but also small condition number in the transfer impedance matrix, which contributes to the robustness of the system against the environmental change.
AE1.7	GMDF with Adaptive Reconstruction Filters and Zero Throughput Delay J. Lariviere, R. Goubran (Carleton University, Canada) With reduction of the block size (increasing the number of subfilters) regular gmdf can achieve low throughput delay at the expense of system performance. In situations where zero delay is desirable, we propose a new method which is not dependent on the block size. In addition, by using an adaptive reconstruction filter, further performance gains can be achieved with minimal additional computation complexity. Results from experiments performed in a conference room show an increase in the average Echo Return Loss Enhancement (ERLE) of > 2.5 dB for acoustic echo cancelation over the traditional moving average reconstruction filter.
AE1.8	Analysis and Design of Narrowband Active Noise Control Systems S. Kuo, X. Kong, S. Chen, W. Hao (Northern Illinois University, USA) This paper presents an analysis and optimization of narrowband active noise control (ANC) systems using the filtered-X least mean-square (LMS) algorithm. First, we derive an upper bound for the eigenvalue spread of the filtered reference signal's covariance matrix, which provides insights into algorithm convergence speed. Amplitude of internally generated sinusoidal reference signal is optimized as the inverse of the secondary path's magnitude response at the corresponding frequency to improve the convergence speed. Second, we analyze the characteristic of asymmetric out-of-band overshoot. Based on the analysis result, the phase of sinusoidal reference signal is optimized to compensate for the phase shift of the secondary path. This phase optimization leads to the minimization of the out-of-band overshoot.

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