The need for traffic noise prediction models that take traffic dynamics into account has been recently shown for urban areas. Such models couple a dynamic representation of traffic with noise emission laws. The contribution of the paper is to test different traffic and noise source representations for LAeq and statistical levels estimation. Tests on four scenarios that reflect urban traffic con...

This paper proposes frequency offset (FO) estimation schemes robust to the non-Gaussian noise for orthogonal frequency division multiplexing (OFDM) systems. A maximum-likelihood (ML) scheme and a low-complexity estimation scheme are proposed by applying the probability density function of the cyclic prefix of OFDM symbols to the ML criterion. From simulation results, it is confirmed that the pr...

In this paper, we propose a new blind spatial subtraction array (BSSA) which contains an accurate noise estimator based on independent component analysis (ICA) to realize a noise-robust hands-free speech recognition. First, a preliminary experiment suggests that the conventional ICA is proficient in the noise estimation rather than the direct speech estimation in real environments, where the ta...

In array signal processing a group of sensors located at distinct spatial locations is deployed to measure a propagating wave eld. The multichannel output is then processed to provide information about parameters of interest. Application areas include smart antennas in communications, radar, sonar and biomedicine. When deriving array signal processing algorithms the noise is typically modeled a...

original article     the aim of this study was to design and build a software for noise propagation prediction (indoor and from indoor to outdoor spaces) which is being commonly used in industry.  in this regard, firstly a mathematical complex model was created based on existing relationships about noise propagation in indoor spaces and transmission through the walls and propagation in outdoor ...

This paper introduces an extremely robust adaptive denoising filter in the spatial domain. The filter is based on non-parametric statistical estimation methods, and in particular generalizes an adaptive method proposed earlier by Fukunaga [1]. To denoise a pixel, the proposed filter computes a locally adaptive set of weights and window sizes, which can be proven to be optimal in the context of ...