A key enabler for sustainable growth of aviation is the mitigation adverse environmental effects. One area concern community noise exposure at large hub airports serving growing population centers. Traditionally, computed using contours around airports, which requires knowledge a dataset pertaining to air traffic operations airport interest. Due underlying variability in real-world aircraft ope...

We describe a range of powerful multiscale analysis methods. We also focus on the pivotal issue of measurement noise in the physical sciences. From multiscale analysis and noise modeling, we develop a comprehensive methodology for data analysis of 2D images, 1D signals (or spectra), and point pattern data. Noise modeling is based on the following: (i) multiscale transforms, including wavelet tr...

Speech enhancement is challenging because of the diversity background noise types. Most existing methods are focused on modelling speech rather than noise. In this paper, we propose a novel idea to model and simultaneously in two-branch convolutional neural network, namely SN-Net. SN-Net, two branches predict noise, respectively. Instead information fusion only at final output layer, interactio...

In this paper, we present a system of sines+transients+noise modeling techniques that dynamically switches between parametric representations and transform coding based representations. The sines and noise are represented by parametric models using multiresolution sinusoidal modeling and Bark-band noise modeling, respectively. The transients are modeled by short regions of transform coding. In ...

This paper investigates the multiplicative spread spectrum watermarking method for the image. The information bit is spreaded into middle-frequency Discrete Cosine Transform (DCT) coefficients of each block of an image using a generated pseudo-random sequence. Unlike the conventional signal modeling, we suppose that both signal and noise are distributed with Laplacian distribution, because the ...