In this study, Particle Swarm Optimization(PSO) is proposed for change point (edge) detection on noisy ramped signals. By taking moving averages between detected edges, noise on ramped signals is filtered and desired piecewise constant signals are acquired. It is required to detect edges in the immediate vicinity of actual edges. Performance of PSO is measured by the difference between estimated and actual position of edges. It is not possible to satisfy such a condition by standard PSO. Hence, in this work, two modifications to standard PSO are proposed: "PSO with uniformly distributed position vectors" and "Cascading PSO". Throughout this work, all implementations are done on real signals which indicate generated powers by plants. © 2012 ...
Particle swarm optimization (PSO) is a search algorithm based on stochastic and population-based ada...
In this paper we describe results of a modified Particle Swarm Optimization (PSO) algorithm which ha...
We propose a novel generalized algorithmic framework to utilize particle filter for optimization inc...
Detection of continuous and connected edges is very important in many applications, such as detectin...
Piecewise smooth signal denoising is cast as a non-linear optimization problem in terms of transitio...
This paper presents a novel edge detection method based on Particle Swarm Optimization. Unlike class...
Nature inspired optimization methods have been finding many application areas in different disciplin...
This paper proposes a change point detection for electroencephalograms (EEG) signal application base...
This paper considers the problem of finding the position of a passive target using noisy time differ...
[[abstract]]The technique for point pattern matching (PPM) is essential to many image analysis and c...
In this paper we propose a robust lane detection and tracking method by combining particle filters w...
The modification of the Particle Swarm Optimizer has been shown to be effective in locating a changi...
The development of computer based sign language recognition system, for enabling communication with ...
One of the biggest drawbacks of the original Particle Swarm Optimization is the premature convergenc...
In the first part of this article, Particle Swarm Optimization (PSO) was applied to the problem of o...
Particle swarm optimization (PSO) is a search algorithm based on stochastic and population-based ada...
In this paper we describe results of a modified Particle Swarm Optimization (PSO) algorithm which ha...
We propose a novel generalized algorithmic framework to utilize particle filter for optimization inc...
Detection of continuous and connected edges is very important in many applications, such as detectin...
Piecewise smooth signal denoising is cast as a non-linear optimization problem in terms of transitio...
This paper presents a novel edge detection method based on Particle Swarm Optimization. Unlike class...
Nature inspired optimization methods have been finding many application areas in different disciplin...
This paper proposes a change point detection for electroencephalograms (EEG) signal application base...
This paper considers the problem of finding the position of a passive target using noisy time differ...
[[abstract]]The technique for point pattern matching (PPM) is essential to many image analysis and c...
In this paper we propose a robust lane detection and tracking method by combining particle filters w...
The modification of the Particle Swarm Optimizer has been shown to be effective in locating a changi...
The development of computer based sign language recognition system, for enabling communication with ...
One of the biggest drawbacks of the original Particle Swarm Optimization is the premature convergenc...
In the first part of this article, Particle Swarm Optimization (PSO) was applied to the problem of o...
Particle swarm optimization (PSO) is a search algorithm based on stochastic and population-based ada...
In this paper we describe results of a modified Particle Swarm Optimization (PSO) algorithm which ha...
We propose a novel generalized algorithmic framework to utilize particle filter for optimization inc...