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Identification and tracking of time- variant systems is relevant in many applications, such as acoustic echo cancellation, active noise control, or in acoustics, e.g., for fast acquisition of head-related transfer functions (HRTFs) via dynamic measurements. Unlike in many other applications, for acoustic measurements the excitation signals can be chosen and optimized for the specific measurement scenario. So far, for this optimization the impact of the group delay on the tracking behavior has not been explicitly considered as a design criterion. In this paper, the influence of time-variance in combination with the temporal properties (envelope, group delay) of the excitation signal is addressed. In simulations and in dynamic binaural room impulse response measurements it is shown how the group delay of the excitation sequence affects the progression in tracking.

Research in static and time-variant system identification has brought up a broad variety of identification algorithms. In acoustics, e.g., static measurements of transfer functions are commonly conducted using Inverse Cyclic Convolution (ICC) with Exponential Sweep excitation. Identification and tracking of time-variant systems, however, often employ adaptive filter algorithms, such as the Normalized Least Mean Square (NLMS) algorithm. An interesting implementation variant is the so-called Efficient NLMS (eNLMS) algorithm for arbitrary periodic excitation. ICC and the eNLMS algorithm originate from different fields and have so far evolved independently. This paper bridges the gap using a theoretical analysis of both algorithms to prove that they can be transferred into each other. This understanding provides a joint perspective, such that know-how from both fields can be combined to further optimize the system identification process.

In system identification one problem is the autocorrelation of the excitation signal which often crucially affects the adaptation process. This paper focuses on the Kalman filter based adaptation working in the frequency domain and the implication due to correlated signal input. Principle simulations and the introduction of a reference model indicate to which extent correlation take effect. The experimental results demonstrate that even though the Kalman approach already takes advantage from a certain level of inherent decorrelation, it also benefits from additional decorrelation. To address this issue, we derive a new realizable efficient structure combining the Kalman filter based adaptation with linear prediction techniques. The performance gains of the proposed approach are confirmed via experiments for an acoustic echo cancellation application for different scenarios.

In stereo or multi-channel system identification, the most critical problems regarding online identification, e.g., for acoustic echo control, are the correlation properties of the excitation signals of the different audio channels. In this paper the impact of both the auto- and cross-correlation properties is considered and investigated. A new system combining appropriate decorrelation techniques with a Kalman filter driven adaptation algorithm in the frequency domain is presented. For the auto-decorrelation a new structure is proposed where the signals in the adaptation paths are decorrelated via linear prediction without affecting the acoustic signals. A small non-linearity is added into each channel for the reduction of the cross-correlation between channels. The performance evaluation clearly shows the influence of the different countermeasures and the effectiveness of the combined approach.

Sonotubometry with perfect sequences (PSEQ) was able to detect eustachian tube (ET) openings in both normal and pathological ears. Impaired ears showed ET openings in almost all cases; however, these proved to be not only less frequent, but also with lower amplitude and shorter duration.To investigate the function of impaired ET under physiological conditions, using a novel kind of sound stimulus for sonotubometry – the PSEQ.Twenty otologically healthy subjects (40 normal ears) and 32 patients with ear diseases (40 pathological ears) were examined sonotubometrically using noise signals with an ideally flat spectrum (PSEQ). Dry swallowing, water swallowing, and Toynbee maneuver were used to induce ET openings. Analysis was performed regarding the frequency of occurrence, duration, amplitude, and form of the ET openings.PSEQ allowed the detection of an ET opening in all 40 normal ears (91% of the performed maneuvers) and in 87.5% of the ears with impaired ET function (but only 47% of the maneuvers). The average amplitude of the openings in healthy ears was 16.86 dB, the average duration was 363 ms. In diseased ears these values were significantly lower: 9.73 dB, p0.001 and 280 ms, p0.05.

INTRODUCTION: Sonotubometry allows an assessment of the Eustachian tube (ET) function under physiological conditions. The application of conventional sinus signals is not reliable enough for routine clinical use. The aim of this study was to investigate ET activity with so-called perfect sequences (PSEQ). PATIENTS AND METHODS: PSEQs generated by a custom-made device were applied in 25 healthy subjects. ET opening was induced by Toynbee manoeuvre, yawning, dry and water swallowing. All sonotubograms were qualitatively analysed according to their shape, and quantitatively according to increase of sound intensity, frequency of opening and opening duration. The sonotubometry results were combined with the patients' perception of tone variation. RESULTS: A number of 400 measurements were performed. In 92.75 % measurements the patients reported ET openings. These were confirmed by 81.5 % valid sonotubograms. The swallowing manoeuvres dry/water swallowing and Toynbee yielded with 94 %/90 % and 93 % valid measurements favourable results. Yawning was associated with 49 % valid measurements. Sound level increase was also significantly different in these manoeuvres when compared to yawning (p > 0.0001). Nasal decongestion had no influence on the results (p < 0.05). CONCLUSIONS: PSEQs allow an evaluation of ET function. The chosen manoeuvres trigger in healthy subjects objective ET openings with a high reliability. The application of PSEQs can detect ET activity with a high sensitivity and good specificity. By further technical refinements specificity may also be enhanced in future studies.

Sonotubometry allows an assessment of the Eustachian tube (ET) function under physiological conditions. The reliability of the application of an 8 kHz pure-tone signal was investigated. In 40 normal subjects (80 ears) sonotubometric studies were performed with a custom-made device. ET opening was provoked by swallowing, yawning and Valsalva manoeuvre. An opening was detected in all patients but not in all manoeuvres. Four characteristic sonotubogram types were found. Most common was the spike-type (60%). The double-peak and the plateau-shaped curves occured in 17% each. The finding of an descendant curve was rare (5%). Of 623 measurements, only in 55% manouvres a positive sonotubometric result was found despite the fact that the patients reported an opening in all cases. The median opening time in dry swallowing, liquid swallowing, yawning and Valsalva was found to be 486, 355, 1,263 and 1,250 ms. A median sound increase of 16.0, 13.8, 15.0 and 15.0 dB was recorded for these manoeuvres. There was a statistic significant difference (P < 0.02) between the increase in sound intensity of liquid and dry swallowing. There was also a statistic significant difference found for the duration of the forced manoeuvres Valsalva and yawning as compared to dry and liquid swallowing (P < 0.0001). The use of an 8 kHz pure-tone signal showed a limited sensitivity for the detection of ET openings. This is mainly due to noise pollution, but also because of an altered positioning and/or dislocation of the probes and compression of the nostrils. The application of an 8 kHz signal is therefore not reliable enough for the use in practice. Further technical refinements and the use of alternative signals are necessary for a broader clinical application.

Fast and robust acoustic system identification is still a research topic of interest, because of the typically time-variant nature of acoustic systems and the natural performance limitation of electroacoustic measurement equipment. In this paper, we propose NLMS-type adaptive identification with perfect-sweep excitation. The perfect-sweep is derived from the more general class of perfect sequences and, thus, it inherits periodicity and especially the desired decorrelation property known from perfect sequences. Moreover, the perfect-sweep shows the desirable characteristics of swept sine signals regarding the immunity against non-linear loudspeaker distortions. On this basis, we first demonstrate the fast tracking ability of the perfect-sweep NLMS algorithm via computer generated simulation of a time-variant acoustic system. Then, the robustness of the perfect-sweep NLMS algorithm against non-linear characteristics of real measurements in a time-invariant case is presented. By finally addressing the measurement of quasi-continuous head-related impulse responses, we face the combined challenge of time-variant and possibly non-linear distorted acoustic system identification in a real application scenario and we can demonstrate the superiority of the perfect-sweep NLMS algorithm.

Adaptive echo cancellers are currently being studied for applications such as audio teleconference systems or hands-free telephone sets with high speech quality. The purpose of the echo control is to eliminate the acoustic feedback from the loudspeaker to the microphone. One problem of echo cancellers using e.g. the normalized least mean square algorithm(nlms) for the adaptation of the coefficients is that the convergence properties degrade with colored signal input such as speech signals [8, 9, 17]. One approach to accelerate the convergence speed is to introduce linear prediction filters in order to decorrelate the speech signal [1, 2, 12, 15, 20]. This paper presents a new approach, named the excited lms algorithm orelms algorithm, which prewhitens the input signal applying perfect sequences. Coincidently, the proposed algorithm can be interpreted as a combination of the conventionalnlms algorithm and a system identification approach using m-sequences or related sequences.

In recent publications, continuous-azimuth inference of head related impulse responses (HRIRs) was treated as a time-varying system identification problem on the basis of dynamical measurements. The system identification thus can be handled by LMS-type adaptive filters for which we have the freedom to choose the excitation signal in this application. In order to provide the perspective of reducing the measurement time to a minimum, we now suggest the optimal excitation signal in terms of the rate of convergence. This excitation signal is given by perfect sequences (PSEQs) out of the larger family of periodic pseudo-noise signals. After the discussion of specific implications of perfect sequences, we compare the performances of our perfect-sequence LMS algorithm (PSEQ-LMS) to the results of white noise processing. We demonstrate a uniform improvement by PSEQ-LMS in terms of instrumental mean-square error analysis as well as subjective listening to dynamic HRIRs. Both measures turn out to be consistent.

The aim of this study was the introduction of a specific class of signals, the so-called perfect sequences (PSEQ), in a novel approach for sonotubometry of the Eustachian tube (ET). Sonotubometry using PSEQ stimuli was performed on 20 healthy subjects in order to gauge its potential for clinical applications. In a series of 320 measurements ET opening was probed, which was induced by dry and water swallowing, Toynbee maneuver, and yawning. All sonotubograms were analyzed with respect to their shape, increase of sound intensity, and opening duration. In 298/320 measurements (93%) the subjects reported subjective ET openings. The evaluation of the recorded sonotubograms showed good detection of ET opening for the inducing maneuvers of swallowing (dry and water swallowing) and the Toynbee maneuver, with 90, 86, and 80% valid sonotubograms, respectively. Yawning led to only 40% valid sonotubograms. In total, 237/320 (~74%) sonotubograms were classified as valid. The evaluation of the sound level increase during ET openings showed that it was significantly higher in measurements with dry and water swallowing, as well as Toynbee maneuvers (mean 17.1, 19.0 and 17.2 dB, respectively), than with yawning (mean 10.17 dB; P0.0001). Nasal decongestion was found to have little influence on the results (P0.05). Sonotubometry using PSEQ stimuli is a novel sonotubometry methodology that provides valuable information regarding the auditory tube patency. By further technical refinements of the method, a diagnostic tool with high sensitivity and specificity could be developed.

Sonotubometry allows for the detection of the dynamic Eustachian tube function under physiological conditions, whether the eardrum is intact or perforated. Quality and reliability of state-of-the-art sonotubometry have been substantially improved by a new real-time system for otological diagnostics [1]–[4]. Moreover, this diagnostic system provides a time-variant virtual model of the Eustachian tube as a new feature, which opens up entirely new possibilities in monitoring Eustachian tube openings. In this work we investigate the correlation of the virtual model to the human anatomy.

In contrast to most of the clinical examinations, the sonotubometric assessment of the Eustachian tube function allows the registration of the tube opening at the perforated, as well as at the intact eardrum in physiological conditions. In this paper, a new procedure is introduced which performs a measurement of the transmission path nose/ear. With digital signal processing algorithms the generation of a new feature relevant for medical diagnostics is made accessible. The method is based on techniques known from speech processing: the acoustic tube model, the normalized least-mean-square (NLMS) algorithm with so-called perfect sequence (PSEQ) (Luke, 1992 and Luke and Schotten, 1995) excitation and the Levinson-Durbin algorithm. Within the framework of an interdisciplinary cooperation we developed a new real-time acoustic measurement prototype which opens up entirely new possibilities in otological diagnostics.

One of the most widely used gradient-based adaptation algorithms is the so called normalized least mean square (NLMS) algorithm. The rate of convergence, misadjustment and noise insensitivity of the NLMS-type algorithm depend on the proper choice of the step size parameter, which controls the weighting applied to each coefficient update. Different step size methods have been proposed to improve the convergence of NLMS-type filters, while preserving the steady-state performance. The step size methods considered here use either a step size parameter which varies with time or a separate, tap-individual step size for each filter tap. The derivation of the respective step size methods is based on different optimization criteria. In this paper a step size parameter is proposed satisfying a combined optimization criterion leading to a time variant and individual step size parameter. The realization aspects of the new concept are discussed for an acoustic echo control application as an example.

For many applications such as acoustic echo compensation, adaptive noise reduction or acoustic feedback control it is of great interest to simulate reproducibly a real, time variant room. One approach to describe the transient behavior of a room is the generation of a physical room model. To identify the variation of a room impulse response with time an alternative concept is presented, which uses the normalized least mean square (NLMS) algorithm excited by perfect sequences. The proposed general concept is capable to efficiently simulate the fluctuations of the room impulse response. The time variant simulation can be performed without the necessity to store large amounts of data by storing only the reaction of the unknown system instead of all sets of filter coefficients. The practical aspects of the new concept are pointed out for an acoustic echo control application.