The notion of low-noise channels was recently proposed and analyzed in detail in order to describe noise-processes driven by environment [M. Hotta, T. Karasawa and M. Ozawa, Phys. Rev. A72, 052334 (2005) ]. An estimation theory of low-noise parameters of channels has also been developed. In this report, we address the low-noise parameter estimation problem for the N -body extension of low-noise...

Noise spectrum estimation from a noisy speech signal forms a critical part of such applications as single channel speech enhancement and robust automatic speech recognition (ASR). The two-pass quantile based noise estimation algorithm presented in this paper has the ability to track slow changing non-stationary noise and obtains good estimates for various noise types over a wide range of SNR le...

In this paper, a novel method based on a combination of Extended Kalman Filter (EKF) with Self-adaptive Differential Evolution (SaDE) algorithm to estimate rotor position, speed and machine states for a Permanent Magnet Synchronous Motor (PMSM) is proposed. In the proposed method, as a first step SaDE algorithm is used to tune the noise covariance matrices of state noise and measurement noise i...

Quantifying frequency converters’ residual phase noise is essential in various applications, including radar systems, high-speed digital communication, or particle accelerators. Multi-input signal source analyzers can perform such measurements out of the box, but high cost limits their accessibility. Based on an analysis transmission theory and capabilities popular instrumentation, we propose a...

This paper addresses the problem of noise power spectrum estimation. Existing noise estimation methods cannot perform quite reliably when noise level increasing abruptly (e.g., narrowband noise bursts). To overcome this problem, we improve the time-recursive averaging algorithm based on speech presence probability (SPP), by exploiting the sparseness of speech spectrum. Firstly, we utilize the S...

Automatic speech recognition performance tends to be degraded in noisy conditions. Spectral subtraction is a simple, popular approach of noise compensation. In conventional spectral subtraction [1, 2], noise statistics are updated during speech gaps and subtracted from a corrupt signal during speech intervals. Some means of explicit speech, non-speech detection is therefore essential. Recent pr...

Estimation of noise contained within a remote sensing image is essential in order to counter the effects of noise contamination. The application of convolution data-masking techniques can effectively portray the influence of noise. In this paper, we describe the performance of a developed noise-estimation technique using data masking in the presence of simulated additive and multiplicative nois...