Noise measurement

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

Electronic Noise Modeling in Statistical Iterative Reconstruction

Abstract: We consider electronic noise modeling in tomographic image reconstruction when the measured signal is the sum of a Gaussian distributed electronic noise component and another random variable whose log-likelihood function satisfies a certain linearity condition. Examples of such likelihood functions include the Poisson distribution and an exponential dispersion (ED) model that can approximate the signal statistics in integration mode X-ray detectors. We formulate the image reconstruction problem as a maximum-likelihood estimation problem. Using an expectation-maximization approach, we demonstrate that a reconstruction algorithm can be obtained following a simple substitution rule from the one previously derived without electronic noise considerations. To illustrate the applicability of the substitution rule, we present examples of a fully iterative reconstruction algorithm and a sinogram smoothing algorithm both in transmission CT reconstruction when the measured signal contains additive electronic noise. Our simulation studies show the potential usefulness of accurate electronic noise modeling in low-dose CT applications.

Uncertainty Management in Differential Evolution Induced Multiobjective Optimization in Presence of Measurement Noise

Abstract: This paper aims to design new strategies to extend traditional multiobjective optimization algorithms to efficiently obtain Pareto-optimal solutions in presence of noise on the objective surfaces. The first strategy, referred to as adaptive selection of sample size, is employed to balance the tradeoff between quality measure of fitness and run-time complexity. The second strategy is concerned with determining statistical expectation, instead of conventional averaging, of fitness samples as the measure of fitness of the trial solutions. The third strategy attempts to extend Goldberg's method to compare slightly worse trial solutions with its competitor by a more statistically viable comparator to examine possible placement of the former solution in the Pareto optimal front. The traditional differential evolution for multiobjective optimization algorithm has been modified by extending its selection step with the proposed strategies. Experiments undertaken to study the performance of the extended algorithm reveal that the extended algorithm outperforms its competitors with respect to three performance metrics, when examined on a test suite of 23 standard benchmarks with additive noise of three statistical distributions. The extended algorithm has been applied on the well known box-pushing problem, where the forces and torques required to shift the box by two robots are evaluated to jointly satisfy the conflicting objectives on task-execution time and energy consumption in presence of noise on range estimates from the sidewalls of the workspace. The application justifies the importance of the proposed noise-handling strategies in practical systems.

Active vibration noise control device

Abstract: The disclosed active vibration noise control device is suitable for use in cancelling out vibration noise by outputting control noise from a plurality of speakers. When a vibration noise frequency is in a dip bandwidth, the active vibration noise control device alters the step size parameters used to update the filter coefficient at at least one filter coefficient update means from among a plurality of filter coefficient update means. Thus, the filter coefficient update speed can be retarded in unstable dip bandwidths, enabling loss in silencing effect which occurs during dip characteristics to be appropriately reduced.

Through-wall radar imaging using UWB noise waveforms

Abstract: This paper examines the results of our research on the use of ultrawideband noise waveforms for imaging objects behind walls. The advantages of using thermally generated noise as a probing signal are introduced. The technique of heterodyne correlation used to inject coherence in the random noise probing signal and to collapse the wideband reflected signal into a single frequency are presented. Central to successful imaging through building walls is the characterization of the wideband propagation properties of wall materials and these are discussed. The basic concepts of synthetic aperture radar image formation using noise waveforms and the unique problems associated with the random nature of the transmit waveform are analyzed. We also address issues related to locating, detection, and tracking humans behind walls, using new tools for human activity characterization, namely the Hilbert-Huang Transform approach. The results indicate that noise radar technology combined with modern signal processing approaches is indeed a viable technique for covert high-resolution imaging of obscured stationary and moving targets.

Efficient approximation of neural filters for removing quantum noise from images

Abstract: In this paper, efficient filters are presented that approximate neural filters (NFs) that are trained to remove quantum noise from images. A novel analysis method is proposed for making clear the characteristics of the trained NF. In the proposed analysis method, an unknown nonlinear deterministic system with plural inputs such as the trained NF can be analyzed by using its outputs when the specific input signals are input to it. The experiments on the NFs trained to remove quantum noise from medical and natural images were performed. The results have demonstrated that the approximate filters, which are realized by using the results of the analysis, are sufficient for approximation of the trained NFs and efficient at computational cost.