Journal ArticleDOI
A new modified particle swarm optimization algorithm for adaptive equalization
TLDR
A novel modification to the standard particle swarm optimization (PSO) technique is presented and the superiority of the proposed modified technique over other PSO-based techniques is illustrated, with an application to the important area of adaptive channel equalization.About:
This article is published in Digital Signal Processing.The article was published on 2011-03-01. It has received 67 citations till now. The article focuses on the topics: Multi-swarm optimization & Particle swarm optimization.read more
Citations
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Journal ArticleDOI
Identification of unknown parameters of a single diode photovoltaic model using particle swarm optimization with binary constraints
Sangram Bana,R.P. Saini +1 more
TL;DR: A particle swarm optimization (PSO) technique with binary constraints has been presented to identify the unknown parameters of a single diode model of solar PV module and it has been found that PSO algorithm yields a high value of accuracy irrespective of temperature variations.
Journal ArticleDOI
Solar cell parameters identification using hybrid Nelder-Mead and modified particle swarm optimization
TL;DR: In this paper, an application of the hybrid Nelder-Mead simplex search method and modified Particle Swarm Optimization technique for identifying the parameters of solar cell and photovoltaic module models is presented.
Journal ArticleDOI
EEG/ERP Adaptive Noise Canceller Design with Controlled Search Space (CSS) Approach in Cuckoo and Other Optimization Algorithms
TL;DR: A new approach is proposed in the form of controlled search space to stabilize the randomness of swarm intelligence techniques especially for the EEG signal, which is found to be more accurate and powerful.
Journal ArticleDOI
Adaptive filtering of EEG/ERP through Bounded Range Artificial Bee Colony (BR-ABC) algorithm
TL;DR: A comparative study of the performance of conventional gradient based methods like LMS, RLS, and ABC algorithm is made which reveals that ABC algorithm gives better performance in highly noisy environment.
Journal ArticleDOI
Adaptive filtering of EEG/ERP through noise cancellers using an improved PSO algorithm
TL;DR: A comparative study of the performance of conventional gradient based methods like LMS, NLMS and RLS, and swarm intelligence based PSO, BFO, GA and ABC techniques is made which reveals that PSO technique gives better performance in average cases of noisy environment with minimum computational complexity.
References
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Journal ArticleDOI
Particle swarm optimization
TL;DR: A snapshot of particle swarming from the authors’ perspective, including variations in the algorithm, current and ongoing research, applications and open problems, is included.
Book
Adaptive Filter Theory
TL;DR: In this paper, the authors propose a recursive least square adaptive filter (RLF) based on the Kalman filter, which is used as the unifying base for RLS Filters.
Proceedings ArticleDOI
A modified particle swarm optimizer
Yuhui Shi,Russell C. Eberhart +1 more
TL;DR: A new parameter, called inertia weight, is introduced into the original particle swarm optimizer, which resembles a school of flying birds since it adjusts its flying according to its own flying experience and its companions' flying experience.
Journal ArticleDOI
The particle swarm - explosion, stability, and convergence in a multidimensional complex space
M. Clerc,James Kennedy +1 more
TL;DR: This paper analyzes a particle's trajectory as it moves in discrete time, then progresses to the view of it in continuous time, leading to a generalized model of the algorithm, containing a set of coefficients to control the system's convergence tendencies.
Proceedings ArticleDOI
Comparing inertia weights and constriction factors in particle swarm optimization
Russell C. Eberhart,Yuhui Shi +1 more
TL;DR: It is concluded that the best approach is to use the constriction factor while limiting the maximum velocity Vmax to the dynamic range of the variable Xmax on each dimension.