Nearest Neighbor Distributions and Noise Variance Estimation
نویسندگان
چکیده
In this paper, we address the problem of deriving bounds for the moments of nearest neighbor distributions. The bounds are formulated for the general case and specifically applied to the problem of noise variance estimation with the Delta test and the Gamma test. For this problem, we focus on the rate of convergence and the bias of the estimators and validate the theoretical achievements with experimental results.
منابع مشابه
Edge Detection Based On Nearest Neighbor Linear Cellular Automata Rules and Fuzzy Rule Based System
Edge Detection is an important task for sharpening the boundary of images to detect the region of interest. This paper applies a linear cellular automata rules and a Mamdani Fuzzy inference model for edge detection in both monochromatic and the RGB images. In the uniform cellular automata a transition matrix has been developed for edge detection. The Results have been compared to the ...
متن کاملEdge Detection Based On Nearest Neighbor Linear Cellular Automata Rules and Fuzzy Rule Based System
Edge Detection is an important task for sharpening the boundary of images to detect the region of interest. This paper applies a linear cellular automata rules and a Mamdani Fuzzy inference model for edge detection in both monochromatic and the RGB images. In the uniform cellular automata a transition matrix has been developed for edge detection. The Results have been compared to the ...
متن کاملروشی نوین در کاهش نوفه رایسین از مقدار بزرگی سیگنال دیفیوژن در تصویربرداری تشدید مغناطیسی (MRI)
The true MR signal intensity extracted from noisy MR magnitude images is biased with the Rician noise caused by noise rectification in the magnitude calculation for low intensity pixels. This noise is more problematic when a quantitative analysis is performed based on the magnitude images with low SNR(<3.0). In such cases, the received signal for both the real and imaginary components will fluc...
متن کاملSoftware Cost Estimation by a New Hybrid Model of Particle Swarm Optimization and K-Nearest Neighbor Algorithms
A successful software should be finalized with determined and predetermined cost and time. Software is a production which its approximate cost is expert workforce and professionals. The most important and approximate software cost estimation (SCE) is related to the trained workforce. Creative nature of software projects and its abstract nature make extremely cost and time of projects difficult ...
متن کاملAsymptotic Behaviors of Nearest Neighbor Kernel Density Estimator in Left-truncated Data
Kernel density estimators are the basic tools for density estimation in non-parametric statistics. The k-nearest neighbor kernel estimators represent a special form of kernel density estimators, in which the bandwidth is varied depending on the location of the sample points. In this paper, we initially introduce the k-nearest neighbor kernel density estimator in the random left-truncatio...
متن کامل