Accurate Noise Characterization Research Articles

Nonlocal Band-Weighted Iterative Spectral Mixture Model for Hyperspectral Imagery Denoising

Although efficient hyperspectral image (HSI) denoising relies on complete and accurate description and modeling the spatial-spectral signal in HSI, the current approaches do not fully account for key characteristics of HSI, i.e., the mixed spectra effect, the spatial nonstationarity effect, and noise variance heterogeneity effect. To address this issue, this article presents a linear spectral mixture model with nonlocal means constraint (LSMM-NLMC), with the following advantages. First, LSMM-NLMC can effectively learn the signal in mixed pixels in HSI by estimating clean endmembers and abundances for image restoration. Second, LSMM-NLMC can efficiently address nonstationary spatial correlation effect by imposing NLMC on the latent scene signal. Last, LSMM-NLMC provides accurate noise characterization by accounting for noise variance heterogeneity effect using a band-dependent noise model and a band-weighted Mahalanobis distance for similarity measurement. A novel optimization method based on the expectation-maximization (EM) algorithm and the purified means approach is used to efficiently solve the resulting maximum a posterior (MAP) problem. The experiments on both simulated and real HSI data sets demonstrate that the visual quality and denoising accuracy are significantly improved by the proposed LSMM-NLMC compared with previous methods.

Efficient continuous-wave noise spectroscopy beyond weak coupling

The optimization of quantum control for physical qubits relies on accurate noise characterization. Probing the spectral density $S(\omega)$ of semi-classical phase noise using a spin interacting with a continuous-wave (CW) resonant excitation field has recently gained attention. CW noise spectroscopy protocols have been based on the generalized Bloch equations (GBE) or the filter function formalism, assuming weak coupling to a Markovian bath. However, this standard protocol can substantially underestimate $S(\omega)$ at low frequencies when the CW pulse amplitude becomes comparable to $S(\omega)$. Here, we derive the coherence decay function more generally by extending it to higher orders in the noise strength and discarding the Markov approximation. Numerical simulations show that this provides a more accurate description of the spin dynamics compared to a simple exponential decay, especially on short timescales. Exploiting these results, we devise a protocol that uses an experiment at a single CW pulse amplitude to extend the spectral range over which $S(\omega)$ can be reliably determined to $\omega=0$.

Noise Budget and Interstellar Medium Mitigation Advances in the NANOGrav Pulsar Timing Array

Gravitational wave (GW) detection with pulsar timing arrays (PTAs) requires accurate noise characterization. The noise of our Galactic-scale GW detector has been systematically evaluated by the Noise Budget and Interstellar Medium Mitigation working groups within the North American Nanohertz Observatory for Gravitational Waves (NANOGrav) collaboration. Intrinsically, individual radio millisecond pulsars (MSPs) used by NANOGrav can have some degree of achromatic red spin noise, as well as white noise due to pulse phase jitter. Along any given line-of-sight, the ionized interstellar medium contributes chromatic noise through dispersion measure (DM) variations, interstellar scintillation, and scattering. These effects contain both red and white components. In the future, with wideband receivers, the effects of frequency-dependent DM will become important. Having anticipated and measured these diverse sources of detector noise, the NANOGrav PTA remains well-poised to detect low-frequency GWs.

Accurate noise characterization of wavelength converters based on XGM in SOAs

Wavelength conversion (WCR) has recently emerged as an important technique that can be used to manage the spectacular increase in traffic in dense wavelength division multiplexing (DWDM) networks. WCR is extremely useful to solve contention, reduce wavelength blocking and a wide range of WCR methods have been reported. The optimum placement of these devices within a network remains an unexplored area and accurate models to measure the performance of the system are becoming vital. Therefore, this paper presents an original noise characterization of a class of WCRs based on cross-gain modulation (XGM) in semiconductor optical amplifiers (SOAs) when the components from spontaneous emission of the SOAs at the receiver are dominant over thermal and shot noise terms. A new and simple expression for the error probability (P <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">e</sub> ) is presented offering considerable additional accuracy in sensitivity assessment compared with the Gaussian approach when ASE noise is dominant. Simulation comparisons are presented in different scenarios for a standard system working at 2.5 Gb/s in a metropolitan area network taking into account the key parameters when such systems are designed.

Accurate noise characterization of short gate length GaAs mesfets and hemts for use in low‐noise optical receivers

AbstractAccurate noise characterization of MESFETs and HEMTs is required for the design of high‐frequency optical receivers. Here we consider a technique that extracts the intrinsic noise parameters P, R, C from measured noise data. Novel analytic expressions are presented as well as results that prove the validity of the technique. © 1993 John Wiley &amp; sons, Inc.