Nonlinear signal processing for vocal folds damage detection based on heterogeneous sensor network

OPTIMAL SENSOR PLACEMENT FOR DAMAGE DETECTION BASED ON A NEW GEOMETRICAL VIEWPOINT

In this study, efficient methods for optimal sensor placement (OSP) based on a new geometrical viewpoint for damage detection in structures is presented. The purpose is to minimize the effects of noise on the damage detection process. In the geometrical viewpoint, a sensor location is equivalent to projecting the elliptical noise on to a face of response space which is corresponding to the sens...

Vocal Folds Stroboscopic Image Processing for Otolaryngology

Wavelet-Based Decompositions for Nonlinear Signal Processing

Nonlinearities are often encountered in the analysis and processing of real-world signals. This paper develops new signal decompositions for nonlinear analysis and processing. The theory of tensor norms is employed to show that wavelets provide an optimal basis for the nonlinear signal decompositions. The nonlinear signal decompositions are also applied to signal processing problems.

Wavelet-based transformations for nonlinear signal processing

Nonlinearities are often encountered in the analysis and processing of real-world signals. In this paper, we introduce two new structures for nonlinear signal processing. The new structures simplify the analysis, design, and implementation of nonlinear filters and can be applied to obtain more reliable estimates of higher-order statistics. Both structures are based on a two-step decomposition c...

HMM-Based Abnormal Behaviour Detection Using Heterogeneous Sensor Network

This paper proposes a HMM-based approach for detecting abnormal situations in some simulated ATM (Automated Teller Machine) scenarios, by using a network of heterogeneous sensors. The applied sensor network comprises of cameras and microphone arrays. The idea is to use such a sensor network in order to detect the normality or abnormality of the scenes in terms of whether a robbery is happening ...