GRASS: A Gradient-Based Random Sampling Scheme for Milano Retinex

A Random Sampling Scheme for Path Planning

Several randomized path planners have been proposed during the last few years. Their attractiveness stems from their applicability to virtually any type of robots, and their empirically observed success. In this paper we attempt to present a unifying view of these planners and to theoretically explain their success. First, we introduce a general planning scheme that consists of randomly samplin...

Using pixel intensity as a self-regulating threshold for deterministic image sampling in Milano Retinex: the T-Rex algorithm

An Intelligent Anti-Islanding Scheme for Synchronous-Based Distributed Generation Using Reduced-Noise Morphological Gradient

This paper presents a pattern recognition-based scheme for detection of islanding conditions in synchronous- based distributed generation (DG) systems. The main idea behind the proposed scheme is the use of spatial features of system parameters such as the frequency, magnitude of positive sequence voltage, etc. In this study, the system parameters sampled at the point of common coupling (PCC) w...

Gradient-based Sampling: An Adaptive Importance Sampling for Least-squares

In modern data analysis, random sampling is an efficient and widely-used strategy to overcome the computational difficulties brought by large sample size. In previous studies, researchers conducted random sampling which is according to the input data but independent on the response variable, however the response variable may also be informative for sampling. In this paper we propose an adaptive...

A conjugate gradient based method for Decision Neural Network training

Decision Neural Network is a new approach for solving multi-objective decision-making problems based on artificial neural networks. Using inaccurate evaluation data, network training has improved and the number of educational data sets has decreased. The available training method is based on the gradient decent method (BP). One of its limitations is related to its convergence speed. Therefore,...