The derivation of suitable analytical models is an important step for the design and analysis of molecular communication systems. However, many existing models have limited applicability in practical scenarios due to various simplifications (e.g., assumption of an unbounded environment). In this paper, we develop a realistic model for particle diffusion in a bounded sphere and particle transport through a semi-permeable boundary. This model can be used for various applications, such as modeling of inter-/intra-cell communication or the release process of drug carriers. The proposed analytical model is based on a transfer function approach, which allows for fast numerical evaluation and provides insights into the impact of the relevant molecular communication system parameters. The proposed solution of the bounded spherical diffusion problem is formulated in terms of a state-space description and the semi-permeable boundary is accounted for by a feedback loop. Particle-based simulations verify the proposed modeling approach.

This paper considers particle propagation in a cylindrical molecular communication channel, e.g. a simplified model of a blood vessel. Emitted particles are influenced by diffusion, flow, and a vertical force induced e.g. by gravity or magnetism. The dynamics of the diffusion process are modeled by multi dimensional transfer functions in a spatio-temporal frequency domain. Realistic boundary conditions are incorporated by the design of a feedback loop. The result is a discrete-time semi-analytical model for the particle concentration in the channel. The model is validated by comparison to particle-based simulations. These numerical experiments reveal that the particle concentration of the proposed semi-analytical model and the particle-based model are in excellent agreement. The analytical form of the proposed solution provides several benefits over purely numerical models, e.g. high flexibility, existence of low run-time algorithms, extendability to several kinds of boundary conditions, and analytical connection to parameters from communication theory.

Fault detection in DC grids requires new concepts for the design of protection devices. A promising concept for predictive circuit protection is model based learning, e.g. Kalman estimation. It requires detailed system models of electrical circuits. An established modeling technique in circuit theory is the wave digital principle which preserves circuit passivity and stability. This contribution combines both ideas and derives a Kalman filter in the wave digital domain.

Low end extra low voltage direct current grids require selective fault protection designed for the specific application and system voltage. System identification and machine learning methods are helpful to identify, to localize and to classify occurring fault events. A category of non-recursive large-signal methods in the time domain for system identification and for refined fault detection and analysis is introduced.

Measurements of the input impedance of electrical transmission lines indicate a frequency dependency of the line parameters. This behavior can be simulated by adjustments to a suitable transfer function model for frequency independent parameters. To this end, functional transformations in time and space set up a transfer function model as a decomposition into individual modes. Adjusting the parameters for each single mode to measured input impedances faithfully describes the frequency dependent behavior. The presented approach does not only model the input impedance, it is also suitable for time domain simulations.

The rich literature on acoustic source localization mostly relies on the assumption of a constant value for the speed of sound. This hypothesis allows establishing simple relations between range differences and time differences and leads to effective estimation algorithms. However, it must be challenged for certain applications of wireless acoustic sensor networks in multizone buildings and outdoor environments. This article revisits the source localization problem for the more general case of an unknown value for the speed of sound. It reviews the physical foundations for the dependence of the speed of sound on the air temperature and presents the essential approaches to acoustic source localization. On this basis, several methods for source localization under uncertain or variable speed of sound conditions from the literature are discussed. Applications from different fields are shown. They comprise the localization of sources, sensors, and reflecting surfaces, time-difference-of-arrival disambiguation, and the direct determination of the speed of sound or the air temperature from acoustic measurements.

DC grids of system voltages above 20V demand different safety concepts compared to conventional AC grids. More elaborate protection devices have to be developed to detect not only high-power, but also low-power faults. The discrimination between faults and load variations can be supported by model-based machine learning methods. For this purpose, this contribution developes time-invariant and linearized system-models with chains of two-ports including possible faults. To consider faults in transmission lines occuring after steady-state system conditions, the initial distribution of voltages and currents is modeled by spatially concentrated equivalent sources. This approach leads to an analytic frequency domain solution without spatial discretization. Measurements on a two-core cable compare favourably with this closed form model.

Spatially distributed acoustic sensors find increasingly many new applications in speech-based human-machine interfaces. One well researched topic is the localization of sound sources from Time Differences Of Arrival (TDOAs) measurements. Typically, the propagation speed of sound is considered a known constant. However due to temperature variations its value is known only up to some uncertainty. This paper exploits TDOA-based localization techniques in order to estimate accurately the actual speed of sound. Experimental results using both simulated and real data demonstrate the feasibility of the proposed method. Furthermore, the practical validation of this work considers two distinct experiments that are aimed at inferring information about enclosed sound fields. The first experiment concerns the calculation of the air temperature from the estimated speed of sound. The second experiment highlights the effects of temperature variations on the inference of the physical location of reflective boundaries of the acoustic enclosure. In the latter case it is shown that the position estimates of the reflective surfaces in a room can be improved when the correct propagation speed is first estimated using this method.

Spatially distributed acoustic sensors find increasingly new applications in speech-based human-machine interfaces. One well researched topic is the localisation of an emitting source from Time-Difference-Of-Arrival (TDOA) measurements. This manuscript shows how to exploit the source localization framework and its state of the art techniques to accurately estimate the actual sound speed and the air temperature by measuring TDOAs of an unknown located acoustic source. Simulations and experiments show the validity of the proposed method.

This letter describes some of the new entries to the Signal Processing Letters (SPL) Editor's Information Classification Scheme (EDICS) for the topic Audio and Acoustic Signal Processing.

In this paper we propose a methodology for assessing the accuracy of techniques of wave field rendering through loudspeaker arrays. In order to measure the rendered wave field we adopt a solution based on a circular harmonic analysis of the sound field captured by a virtual microphone array. As a result of this analysis stage, we are able to compare the target, the theoretical and the measured wave fields, which may differ due to the non-ideality in the loudspeaker array or in the environment that generates some spurious reverberations. Moreover, in order to quantify the error between target, theoretical and measured wave fields, we define some evaluation metrics, based on RMSE and modal analysis of the acquired wave fields. We show some experimental results on real data.

In this paper we propose a novel technique to localize planar obstacles through the measurement of the Direction of Arrival by a microphone array. The measurement of the Direction of Arrival of the reflected path is turned into a quadratic constraint where the unknowns are the line parameters of the reflector. A cost function that combines multiple constraints is then derived. A parametric description of the obstacle is found by minimization of the cost function. Some simulations and experimental results show the feasibility of the proposed method.

Tubular bells are geometrically simple representatives of three-dimensional vibrating structures. Under certain assumptions, a tubular bell can be modeled as a rectangular plate with different types of homogeneous boundary conditions. Suitable functional transformations with respect to time and space turn the corresponding initial-boundary value problem into a two-dimensional transfer function. An algorithmic model follows according to the functional transformation method in digital sound synthesis. As with simpler vibrating structures (strings, membranes) the synthesis algorithms consist of a parallel arrangement of second-order sections. Their coefficients are obtained by simple analytic expressions directly from the physical parameters of the tubular bell.

The functional transformation method (FTM) provides a frequency domain based analytic solution of arbitrary linear partial differential equation. For wave field simulations however, its application was so far restricted to simple geometries as the FTM involves a search for the eigenmodes of the model. Recently so called block based modeling algorithms were introduced, that follow a divide-and-conquer approach. A complex geometry is split into several simple elementary blocks. These blocks are solved and discretized separately, while their connection is realized in the discrete system during run-time. In this paper a 2D wave field simulation program based on block based modeling is demonstrated. Elementary block models are solved with the FTM and can be connected together to create complex 2D geometries. The complete system benefits from the advantages of the FTM (e.g. dispersion-free simulations), while the complexity of the geometry fits the needs of typical CAD drawings

This paper presents an audio-visual database that can be used as a reference database for testing and evaluation of video, audio or joint audio-visual person tracking algorithms, as well as speaker localization methods. Additional possible uses include the testing of face detection and pose estimation algorithms. A number of different scenes are included in the database, ranging from simple to complex scenes that can challenge existing algorithms. They include different subjects, with appearances that can cause problems to video tracking algorithms, (e.g. facial features such as beards, glasses, etc.), optimal and artificially created sub-optimal lighting conditions, subject movement based on simple as well as random motion trajectories, different distances from the camera/microphones and occlusion. The database incorporates ground truth data (3D position in time) originating from a commercially available 4-camera infrared (IR) tracking system. Examples of how the database can be used to evaluate video and audio tracking algorithms are also provided.

Block-based physical modeling algorithms for sound synthesis have gained more and more interest in the past few years. They have the advantage that new models can be created by combining existing blocks and they offer the opportunity to combine different modeling techniques. We propose a general approach to creating physical models in blocks and how to connect these blocks assuring their correct physical interaction. Furthermore, we show how to implement the interconnection of these models with wave digital filter principles. The complete procedure is applied to the example application scenario of the one-dimensional wave equation. Three different modeling techniques are used. One part is implemented with a finite difference time domain approach, one with the functional transformation method, and the boundaries are implemented by wave digital filters.

Wave field synthesis is an auralization technique which allows the entire wave field to be controlled within the entire listening area. However, reflections in the listening room interfere with the auralized wave field and may impair the spatial reproduction. Active listening room compensation aims at reducing these impairments by using the playback system. Due to the high number of playback channels used for wave field synthesis, the existing approaches to room compensation are not applicable. A novel approach to active room compensation overcomes these problems by a transformation from the space-time to the wave domain and application of wave-domain adaptive filtering.

In this combustion, we embed full-duplex multichannel communication interfaces for tele-presence systems into a general framework. On the reproduction side, we consider a wide range of multichannel acoustic rendering techniques including traditional stereophony, '5.1' systems, and wave field synthesis using loud speaker arrays for sound immersion. On the recording side, microphone arrays are discussed for capturing clean desired signals with spatial information. Based on this general framework, real-time implementations of such full-duplex multichannel communication systems are then described. We combine wave field synthesis with multichannel acoustic echo cancellation and adaptive beamforming and discuss a real-time implementation on standard desktop and laptop PCs.

Common room compensation algorithms are capable of dereverberating the listening room at some discrete points only. Outside these equalization points the sound quality is often even worse compared to the unequalized case. As wave field synthesis in principle allows to control the wave field within the listening area it can also be used to compensate for the reflections caused by the listening room in the complete listening area. We present a novel approach to listening room compensation which is based upon the theory of wave field synthesis and that results in a large compensated area.

SYSTOOL is an online learning tool for real or virtual courses in signals and systems. It provides a collection of Java applets for interactive simulation and visualisation of linear systems. While based on a traditional textbook, SYSTOOL is accessible online though the Virtual University of Bavaria. This article describes structure and content of this learning tool and presents selected modules.

Discrete systems for digital sound synthesis derived with the functional transformation method (FTM) from physical models have recently been presented. For linear systems, the FTM solves the partial differential equation (PDE) describing the vibrating structure analytically. The algorithms obtained after discretization of the analytical solution preserve the inherent physical stability of the continuous system. For nonlinear physical models, as they occur in real musical instruments, the direct application of the FTM leads to an implicit continuous equation. This paper shows that discretization results in an explicit solution. Furthermore, the stability problems occurring after discretization of the nonlinear system are fixed by instantaneous energy considerations. For the example of a slapped transversal oscillating tightened string with frequency dependent loss terms an efficient algorithm is derived. It can also be applied to other types of interaction between a resonating body and its environment.

For high-quality multimedia communication systems, such as teleconferencing, or tele-teaching (especially of music), multichannel sound reproduction is highly desirable. While current approaches still rely on a restrained listening area, the sweet spot, a volume solution for a large listening space is offered by the wave field synthesis (WFS) method, where arrays of loudspeakers generate a prespecified sound field. On the recording side of the two-way systems, the use of microphone arrays is an effective approach to cope with undesired signal components in the receiving room. However, before full-duplex communication can be deployed, efficient approaches to the acoustic echo cancellation (AEC) problem in this challenging scenario have to be found. We investigate different options for system integration, after a brief discussion of the current state of the art. We then present a first real-time solution on a regular PC platform, based on an efficient AEC for MIMO (multi-input and multi-output) systems in the frequency-domain.

This paper presents a face localization and tracking algorithm which is based upon skin color detection and principal component analysis (PCA) based eye localization. Skin color segmentation is performed using statistical models for human skin color. The skin color segmentation task results in a mask marking the skin color regions in the actual frame, which is further used to compute the position and size of the dominant facial region utilizing a robust statistics-based localization method. To improve the results of skin color segmentation, a foreground/background segmentation and an adaptive background update scheme are added. Additionally, the derived face position is tracked with a Kalman filter. To overcome the problem of skin color ambiguity, an eye detection algorithm based on PCA is presented.

Multidimensional (MD) physical systems are usually given in terms of partial differential equations (PDEs). Similar to one-dimensional systems, they can also be described by transfer function models (TFMs). In addition to including initial and boundary conditions as well as excitation functions exactly, the TFM can also be discretized in a simple way. This leads to suitable implementations for digital signal processors. Therefore it is possible to implement physics based digital sound synthesis algorithms derived from TFMs in real-time. This paper extends the previously presented solution for vibrating strings with one spatial dimension to two-dimensional drum models.

This paper presents an object localization and tracking algorithm integrating audio and video-based object localization results. A face tracking algorithm and a microphone array are used to compute two single-modality speaker position estimates. These position estimates are then combined into a global position estimate using a decentralized Kalman filter. Experiments with a model railway show that such an approach yields more robust results for audio-visual object tracking than either modality by itself.

Object localization based on audio and video information is important for the analysis of dynamic scenes, such as video conferences or traffic situations. In this paper, we view the the dynamic audio-video object localization problem as a joint recursive estimation problem. It is solved using a decentralized Kalman filter fusing both audio and video position estimates. To better take into account different object maneuvers, multiple state-space equations are also incorporated. The result is a recursive multi-state multi-sensor estimator. Experiments show that it yields significantly improved joint position estimates compared to results achieved by using either an audio or a video system only.

The description of the continuous and discrete multidimensional (MD) models in current use has not yet reached the same state of maturity as for one-dimensional systems. To proceed in that direction, we investigate the connections between certain discrete partial differential equation (PDE) models (finite-difference models, transfer function models, MD wave digital filters). The starting points are potential-flux models that are the standard form of physics-based continuous MD systems. It is shown how certain matrix operations lead to various popular PDE models. The properties of the associated matrices provide the link to the discrete PDE models mentioned above. These investigations are presented in general form along with examples for an electrical transmission line and for acoustic wave propagation.

The exact knowledge of the sound field within an enclosure is essential for a number of applications in electro-acoustics. Conventional methods for the assessment of room acoustics model the sound propagation in analogy to the propagation of light. More advanced computational methods rely on the numerical solution of the wave equation. A recently presented method is based on multidimensional wave digital principles. It allows a physically exact numerical modelling of the relevant acoustical effects and yields robust algorithms. This contribution presents a new foundation of the multidimensional wave digital principle as applied to room acoustics. It starts from the first principles of physics. From there, the derivation of the algorithm only involves basic knowledge of numerical mathematics, linear algebra, and multidimensional system theory. An example for the simulation of dynamic three-dimensional sound propagation demonstrates the capability of the method.

Acoustic echo cancellers in today's speakerphones or video conferencing systems rely on the assumption of a linear echo path. Low-cost audio equipment or constraints of portable communication systems cause nonlinear distortions, which limit the echo return loss enhancement achievable by linear adaptation schemes. These distortions are a super-position of different effects, which can be modelled either as memoryless nonlinearities or as nonlinear systems with memory. Proper adaptation schemes for both cases of nonlinearities are discussed. An echo canceller for nonlinear systems with memory based on an adaptive second order Volterra filter is presented. Its performance is demonstrated by measurements with small loudspeakers. The results show an improvement in the echo return loss enhancement of 7 dB over a conventional linear adaptive filter. The additional computational requirement for the presented Volterra filter is comparable to that of existing acoustic echo cancellers.

This paper proposes a solution to the problem of robust speaker localization under adverse acoustic conditions. The approach is based on the classification of time delay estimates. Two classification techniques are investigated in detail: maximum likelihood (ML) classification and classification based on histogram comparison. Their performance under adverse acoustic conditions is compared to outcomes obtained with the traditional approach which uses time delay estimates directly to infer speaker positions. Experiments indicate that the ML classification method provides little improvement over the traditional method. On the other hand, using histogram classification, we can improve the probability of correct speaker localization by more than 60% compared to either the traditional approach or the ML classification technique.

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.

The suitability of methods from multidimensional systems theory and digital signal processing for the efficient simulation of time and space dependent problems has already been demonstrated. Properly chosen functional transformations for the time and space coordinates turn a partial differential equation into a transfer function description of a multidimensional continuous system. It serves as the starting point for the derivation of a discrete system which closely models the behaviour of the given continuous system and which is suitable for computer implementation. This concept is extended here to the simulation of nonlinear multidimensional systems. The essence of the presented method is a systematic way to turn a nonlinear partial differential equation into a set of ordinary differential equations, for which standard methods for numerical integration exist. This paper briefly reviews the linear case, points out the various difficulties arising from nonlinearity and shows how to overcome them. Numerical results demonstrate the effectiveness of the method.

The application of methods from multidimensional systems theory and digital signal processing opens new ways for the efficient simulation of time and space dependent problems like wave propagation or heat and mass transfer. The basic idea, is the application of suitably chosen functional transformations for the time and space coordinates. Initial and boundary conditions are considered in a systematic way. This leads to the structure of a discrete system which closely models the behaviour of the given continuous system and which is suitable for computer implementation. Numerical results show considerable savings in computer time over conventional finite difference methods.

The application of multidimensional wave digital filter principles to the numerical solution of partial differential equations has been introduced in various recent publications. However, the examples presented so far do not explicitly consider boundary conditions. This letter shows how to incorporate boundary values into a multidimensional wave digital filter. A lossy transmission line of finite extent with given terminations is chosen as an example.>