A secondary path modeling technique for active noise control systems is developed for both on-line and off-line modeling with faster convergence and higher modeling accuracy. The optimum delay for the adaptive prediction error filter to reduce the interference in system modeling is equal to the length of the impulse response of the secondary path being modeled.

This paper presents some apprilcations of neural networks in the microwave modeling. The applications are related to modeling of either passive or active structures and devices. Modeling is performed using not only simple multilayer perceptron network (MLP) but also advanced knowledge based neural network (KBNN) structures. Keywords–Neural network, modeling, microwave, microstrip gap, microwave...

We present a novel mathematical approach to model noise in dynamical systems. We do so by considering the dynamics of a chain of diffusively coupled Nagumo cells affected by noise. We show that the noise in a variable representing the transmembrane current can be effectively modeled as fluctuations in the model parameters corresponding to electric resistance and capacitance of the membrane. The...

When generating musical sound on a digital computer, it is important to have a good model whose parameters provide a rich source of meaningful sound transformations. Three basic model types are in prevalent use today for musical sound generation: instrument models, spectrum models, and abstract models. Instrument models attempt to parametrize a sound at its source, such as a violin, clarinet, o...

Quantitative diffusion imaging is a powerful technique for the characterization of complex tissue microarchitecture. However, long acquisition times and limited signal-to-noise ratio represent significant hurdles for many in vivo applications. This article presents a new approach to reduce noise while largely maintaining resolution in diffusion weighted images, using a statistical reconstructio...

Jet noise reduction remains an important long-range goal in commercial and military aviation. Comparedwith their early counterparts, modern, ultrahigh-bypass-ratio turbofans on commercial aircraft are very quiet, but evermore stringent noise regulations dictate further reductions. In addition, hearing loss bypersonnel and community noise issues are prompting the military to seek noise reduction...

We introduced a nonlinear shot-noise model, a natural generalization of the "classic" shot-noise model, which differs markedly from the existing linear shot-noise models. This model produces a wide spectrum of stationary noise processes. Because of its intrinsic nonlinearity, the model's resulting noise processes are capable of displaying a rich variety of both amplitudal and temporal statistic...

This paper presents a new approach to acoustic noise identification, by introducing fuzzy modeling techniques. Fuzzy identification is compared to conventional linear identification techniques, using as the system to model a new device called ElectroMechanical Film (EMF), developed by VTT [1]. This device can be used either as an acoustic sensor or actuator. The obtained model represents the be...

The problem of detecting a signal known except for amplitude in incompletely characterized colored non-Gaussian noise is addressed. The problem is formulated as a testing of composite hypotheses using parametric models for the statistical behavior of the noise. A generalized likelihood ratio test is employed. It is shown that for a symmetric noise probability density function the detection perf...

In automatic speech recognition (ASR) systems immunity to additive noise may either be applied at the preprocessing stage or at the pattern matching stage. The Feature Selective Modeling (FSM) approach suggested in this paper is applied in the pattern matching stage, but in contrast to most existing methods, it is optimized on a model basis such that noise robust and phonetically descriptive pa...