Noise measurement

About: Noise measurement is a research topic. Over the lifetime, 19776 publications have been published within this topic receiving 308180 citations.

Noise Enhanced Parameter Estimation

Abstract: This paper investigates the phenomenon of noise enhanced systems for a general parameter estimation problem. When the estimator is fixed and known, the estimation performance before and after the addition of noise are evaluated. Performance comparisons are made between the original estimators and noise enhanced estimators based on different criteria. The form of the optimal noise probability density function (pdf) is determined. The results are further extended to the general case where the noise is introduced to the system via a transformation. For the case where the estimator is fixed and unknown, approaches are also proposed to find the optimum noise. Finally, two illustrative examples are presented where the performance comparison is made between the optimal noise modified estimator and Gaussian noise modified estimator.

Fluorescence-enhanced optical tomography using referenced measurements of heterogeneous media

Abstract: A three-dimensional image reconstruction for fluorescence-enhanced frequency-domain photon migration (FDPM) measurements in turbid media is developed and investigated for three different simulated measurement types: 1) absolute emission measurement, or emission measurements of phase and amplitude attenuation made for a given incident point source of excitation light; 2) referenced emission measurements made relative to an excitation measurement conducted at a single reference point away from the incident source; and 3) referenced emission measurements made relative to the excitation measurement conducted at identical points of detection. The image reconstruction algorithm employs a gradient-based constrained truncated Newton (CONTN) method which implements a bounding parameter, which can be used to govern the level of contrast used to discriminate tissue volumes from heterogeneous background tissues. Reverse differentiation technique is used to calculate the gradients. Using simulated data with superimposed noise to achieve a signal-to-noise ratio of 55 and 35 dB to mimic experimental excitation and emission FDPM measurements, respectively, we show the robustness of emission measurements referenced to excitation light. We investigate the performance of algorithm CONTN using these measurement techniques and show that the absorption coefficients due to fluorophore are reconstructed by CONTN accurately and efficiently. Furthermore, we demonstrate the performance of the bounding parameter for rejection of background artifacts owing to background tissue heterogeneity.

A new method for estimating the number of harmonic components in noise with application in high resolution radar

Abstract: In order to operate properly, the superresolution methods based on orthogonal subspace decomposition, such as multiple signal classification (MUSIC) or estimation of signal parameters by rotational invariance techniques (ESPRIT), need accurate estimation of the signal subspace dimension, that is, of the number of harmonic components that are superimposed and corrupted by noise. This estimation is particularly difficult when the S/N ratio is low and the statistical properties of the noise are unknown. Moreover, in some applications such as radar imagery, it is very important to avoid underestimation of the number of harmonic components which are associated to the target scattering centers. In this paper, we propose an effective method for the estimation of the signal subspace dimension which is able to operate against colored noise with performances superior to those exhibited by the classical information theoretic criteria of Akaike and Rissanen. The capabilities of the new method are demonstrated through computer simulations and it is proved that compared to three other methods it carries out the best trade-off from four points of view, S/N ratio in white noise, frequency band of colored noise, dynamic range of the harmonic component amplitudes, and computing time.