In this paper a novel algorithm is presented for the efficient Two-Dimensional (2-D), Least Squares (LS) FIR filtering and system identification. Causal filter masks of general boundaries are allowed. Efficient order updating recursions are developed by exploiting the spatial shift invariance property of the 2-D data set. Single step order updating recursions are developed. During each iteration, the filter coefficients set is augmented by a single new element. The single step order updating formulas allow for the development of an efficient, true order recursive algorithm for the 2-D LS causal linear prediction and filtering.

Two methods to measure the acoustic input impedance of a horn are compared. The first method measures standing-wave patterns in a tube which is loaded by the horn. The input impedance is calculated from the position of the first minimum in the standing-wave pattern and the ratio of maximum to minimum sound pressure levels in the tube. Second a direct method was applied. A novel flow sensor, the microflown, is used together with a pressure microphone, which are mounted in the throat of the horn. Results from both measurements are compared with simulated models.

Based on a simplified nonlinear lumped element model of the electrodynamic loudspeaker in either a closed or a vented cabinet, a new nonlinear controller is derived, simulated and implemented on a DSP. The Volterra series expansion, a well known functional expansion to model nonlinear systems, is used to estimate the nonlinear parameters from distortion measurements. The controller is directly based on the nonlinear differential equation, and is tested for the case of a low frequency electrodynamic loudspeaker in a closed cabinet. Digital implementation is realized on a general purpose TMS320C30 DSP development board, using the automatic code generation from schematic entry of the Alta-Group SPW software.

Inter symbol interference is a well-known problem in mobile communications. This type of interference can be reduced by an adaptive equalizer. For the reduction of ISI in a mobile indoor environment complying to DECT, an adaptive equalizer has to be implemented in the mobile unit. Hence the extra required power consumption should be minimal. Therefore, the computational complexity of the equalizer algorithm is important. The purpose of the research presented in this paper, is to investigate the implementation of an adaptive equalizer in finite precision arithmetic. Scaling methods are used to reduce the wordlength to the mimimum value at which the algorithm still has the same ISI performance as with floating point computation. We present simulated scatter diagrams of different channels for Fast Transversal Filter (FTF) based equalizer structures.

A novel nonlinear controller based on the theory of exact input–output linearization is presented, using a state space model of the nonlinear electrodynamical loudspeaker in a closed cabinet. The model comprises three major nonlinearities due to cone displacement dependent force factor, (suspension) stiffness and self–inductance. Simulation and measurement results of the controller implemented on a Digital Signal Processor (DSP), are given.

High quality sound reproduction by loudspeakers is increasingly problematic if the dimensions of the loudspeaker decrease. To produce enough power, large diaphragm excursions are needed which give rise to significant distortions especially at very low frequencies. Instead of improving the mechanical construction of the transducer we apply a feedforward nonlinear digital inverse circuit. Results of two 2nd order Volterra compensators show a significant reduction of the second order harmonics, leaving higher order distortions unchanged. The structure of the realization influences the performance considerably. Two realization structures are considered, and the error caused by the differentiators in the output of the compensators are compared. Both algorithms are implemented in real-time on a digital signal processor (DSP) for on-line testing with the transducer.

In this paper a fast spatial adaptive algorithm is presented for the efficient least squares (LS), autoregressive exogenous (ARX), two-dimensional (2-D) modeling. Filter masks of general boundaries are allowed. Efficient space updating recursions are developed by exploiting the spatial shift invariance property of the 2-D data set.< >

In this paper a novel algorithm is presented for the efficient two-dimensional (2-D) symmetric noncausal finite impulse response (FIR) filtering and autoregressive (AR) modeling. Symmetric filter masks of general boundaries are allowed. The proposed algorithm offers the greatest maneuverability in the 2-D index space in a computational efficient way. This flexibility can be taken into advantage if the shape of the 2-D mask is not a priori known and has to be dynamically configured.<>

In this paper we will present an algorithm that is capable of recognizing symmetry in an electronic network graph in better than O((n+b)/sup 2/) time for typical circuits. Applications in symbolic analysis and behavioural modeling are presented.< >

In this paper a novel algorithm is presented for the efficient Two-Dimensional (2-D) Least Squares FIR filtering and system identification. Filter masks of general boundaries are allowed. Efficient order updating recursions are developed by exploiting the spatial shift invariance property of the 2-D data set. In contrast to the existing column(row)-wise 2-D recursive schemes based on the Levinson-Wiggins-Robinson's multichannel algorithm, the proposed technique offers the greatest maneuverability in the 2-D index space in a computational efficient way. This flexibility can be taken into advantage if the shape of the 2-D mask is not a priori known and has to be dynamically configured. The recursive character of the algorithm allows for a continuous reshaping of the filter mask. Search for the optimal filter mask, essentially reconfigures the filter mask to achieve an optimal match. The optimum determination of the mask shape offers important advantages in 2-D system modeling, filtering and image restoration.

Horn loaded compression drivers are widely used in the area where high sound pressure levels together with good directivity characteristics are needed. Major disadvantage of this kind of drivers is the considerable amount of nonlinear distortion. Due to the quite high air pressures in the driver the air is driven into its nonlinear range. This paper describes a technique to reduce the distortion caused by this phenomenon. Using a Digital Signal Processor (DSP), a feedforward compensation technique, based on an equivalent lumped parameter circuit, is implemented and tested in real–time in series with the loudspeaker. Measurement and simulation results are given. The overall conclusion is that a distortion reduction is obtained in the frequency span from 600 to 1050 Hz.

Many techniques and design tools have been developed for mapping algorithms to array processors. Linear mapping is usually used for regular algorithms. Large and complex problems are not regular by nature and regularization may cause a computational overhead which prevents the ability to meet real-time deadlines. In this paper, a systematic design methodology for mapping partially-regular as well as regular Dependence Graphs is presented. In this approach the set of all optimal solutions is generated under the given constraints. Due to nature of the problem and the tight timing constraints of real-time systems the set of alternative solutions is limited. An image processing example is discussed

In this paper a novel algorithm is presented for the efficient 2D Least Squares FIR filtering and system identification. Filter masks of general boundaries are allowed. Efficient order updating recursions are developed by exploiting the spatial shift invariance property of the 2D data set. In contrast to the existing column (row)-wise 2D recursive schemes based on the Levinson-Wiggins-Robinson's multichannel algorithm, the proposed technique offers the greatest maneuverability in the 2D index space in a computational efficient way. This flexibility can be taken into advantage if the shape of the 2D mask is not a priori known and has to be dynamically configured. The recursive character of the algorithm allows for a continuous reshaping of the filter mask. Search for the optimal filter mask, essentially reconfigures the filter mask to achieve an optimal match. The optimum determination of the mask shape offers important advantages in 2D system modeling, filtering and image restorations.

This paper presents a methodology to incorporate hierarchy in the design verification process of large full custom digital CMOS circuits including the effects of statistical process variation and variation in external parameters like temperature and supply voltage. Behavioural models are used to describe sub-circuits on a high level of abstraction. Statistical tolerance information from the circuit level is mapped onto the behavioural models. By means of a case study on a large full custom design we show that this design verification methodology can be very efficient

Loudspeakers produce nonlinear distortion. The authors present a method to compensate for this distortion in real time by nonlinear digital signal processing implemented on a digital signal processor (i.e., the TMS320C30 DSP). Based on the literature, an electrical equivalent circuit of an electrodynamic loudspeaker is developed, resulting in a linear lumped parameter model. The parameters in this model are matched with the measurements of a selected test loudspeaker. The linear model is extended to include nonlinear effects by developing the parameters as a function of the voice coil excursion of the loudspeaker in a Taylor series expansion. The resulting nonlinear system is described by a Volterra series. On the basis of this description, an inverse circuit is designed for the second-order nonlinear distortion. This circuit was implemented in real time on the DSP, using a high-level design and code generation system. Simulations and experiments are presented.<>

A systematic approach for modeling failure mechanisms on the circuit level and for using these models for optimization of both reliability and functionability is presented. Since optimization is done using a CAD system, it is possible to carry out such an optimization in a very early stage of the design process. The stress factors of the failure mechanisms are calculated using a circuit simulator and the effect of internal and external tolerances is incorporated in the simulation. From these results the sensitivity of failure behavior for so-called designable parameters on circuit level is determined. This information is used to optimize the design toward minimum occurrence of failures. For functional demands the same methodology is used.<>