The aim of this work was the implementation of the so-called VoldKalman filter. This filter was introduced by Vold and Leuridan in 1993 [1], it is a heterodyne filter for tracking the sinusoidal components of a noisy signal. The formulation of the Vold-Kalman filter leads to a least squares problem. The great advantage of this time-varying filter is that all sinusoids of a signal can be extracted simultaneously yielding a suppression of beating phenomena of close or crossing frequency trajectories. In this paper, we propose a realization for offline processing using the preconditioned conjugate gradient method. Furthermore, we present trivial expressions for the bandwidth and the transition time of first and second order filters.

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Convincing sound reproduction via headphones requires filtering of virtual sound sources with head related transfer functions (HRTF). HRTFs describe signal differences at the two ear drums in level, time and frequency weighting [1,2]. Another psychoacoustic phenomenon of the human auditory system concerning hearing in natural sound fields is the improvement of source localization if small head movements are possible [3]. In this paper a computational efficient implementation to get dynamic binaural signals (in dependence on the head position) is proposed. This realtime modell is based on Ambisonic sound reproduction [4,5].

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The aim of this work was to develop a realtime simulator for vehicle interior noise in varying load situations. Using this simulator, laboratory hearing tests which are common in the automotive industry may be executed more realistically than by using recorded sounds without any interaction possibility. A simplified model for the load situation of a car is presented. Using this model, the interpolation between the prerecorded signals is performed to obtain signals for other load situations. Furthermore, an analysis/resynthesis system for the interior noise of cars is introduced which only needs a sparse set of parameters.

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