## 1 Introduction
They require the identification of the transfer functions between the secondary sources and the virtual microphones in advance. In the identification phase, physical microphones are placed at the virtual positions. The VMT assumes that the primary sound pressure of the virtual microphone equals that of the physical microphone. While the magnitudes at the two locations can be largely equal, the phase can differ significantly at the same time. Hence, the estimation of the primary field by the VMT can be inaccurate. The RMT is the improved version of the VMT, as it estimates the primary field more precisely. This is accomplished by filtering the physical error signals by the transfer functions between the physical and the virtual microphones, with respect to the positon of the primary source. It also requires the identification of the appropriate transfer functions in advance. However, if the position of the primary source changes, the estimation is no longer correct. These algorithms estimate the error signal at the virtual locations, at the expense of modeling additional transfer functions. In the case of active headrest systems, where at least two microphones and two loudspeakers are installed, the VMT requires one and the RMT two \(2\times 2\) filter matrices. The authors of the cited works have used different algorithms. In the noise-canceling chair reported in [6], no virtual sensing is applied, and the emphasis is on the low computational demand. The system could suppress complex tonal disturbance (motorcycle noise) in the low frequency range. The VMT has been successfully used by [4]. Up to a 20-dB reduction has been achieved for tonal noise and only 4-7 dB for narrowband random noise. The superiority of the RMT has been proven in [5], but only a single frequency tonal noise has been used for the experiments. Recently, a noise-canceling office chair equipped with a very complex controller has been published [7]. The RMT has been applied, complemented by an ultrasonic head-tracking system. The actual transfer functions are chosen by the estimated head position. The performance of the chair has been tested in simulations, where tonal noise has been applied at different frequencies. A similar system is described in [8] with more emphasis on the theoretical investigations. Offices are moderately damped rooms where many reflections occur, and not only tonal, but broadband noises are present, as well. In addition, the positions and even the number of the primary sources vary. In a sense, these impose contradictory requirements on the noise controller to be designed. Broadband noise calls for feedforward control, but the arrangement of the reference microphones has to be carefully considered. The error microphones should be located near the ears, so as not to cause any discomfort. To fulfill the latter requirement, the remote microphone technique is a feasible solution. However, it has a high computational demand, and the varying position of the primary sources deteriorates its efficiency. Our noise-canceling chair controls not only tonal, but also broadband disturbances, generated at any point of the room. To achieve this, feedforward control is applied. To overcome the problem of varying primary sources, multiple reference microphones are utilized that surround the chair. Our preliminary investigations have shown that in such rooms, multiple reference signals result in greater suppression, even if only one primary noise source is present. Instead of the widespread filtered-reference least mean squared (XLMS) algorithm, the filtered-error least mean squared (ELMS) algorithm [11] has been applied. The ELMS algorithm ensures faster convergence and needs less computations in this special case, when multiple reference signals are processed. Mainly because of the high computational demand, the remote microphone technique is rejected. We have used two flexible gooseneck microphones fastened to the headrest. The user can adjust the microphone positions to a comfortable distance from the ears. The paper is organized as follows.