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Filters
Flower Pollination Algorithm Approach Towards IIR System Identification
2016
International Journal of Artificial Intelligence and Applications for Smart Devices
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In [12], Chen and Luk used the particle swarm optimization for designing of the digital IIR filter. ...
., reported an IIR system identification problem in which the filter coefficients are optimized using firefly algorithm. ...
system, FPA based optimization algorithm is used. ...
doi:10.14257/ijaiasd.2016.4.2.01
fatcat:k3rt3jdm2jej3n6d66k4ecfr6i
Comprehensive Optimal Fir Filter Design Procedures With Various Impacts
2019
International journal of recent technology and engineering
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Here, a exhaustive scrutiny use of complex optimization algorithms towards the digital-filter construction is conferred. ...
Finally, this review suggested that the swarm intelligence based researchers improved the constraints and its attributes. ...
In recent days, evolutionary algorithms such as (PSO) Particle-Swarm-Optimization,(GA)Genetic-Algorithm, (ACO)Ant-Colony-Optimization,Craziness-based-(CRPSO ) Particle-Swarm-Optimization, Cat Swarm Optimization ...
doi:10.35940/ijrte.c4279.098319
fatcat:bgezgzhttjgcvjmzoeaw4a4rbe
Mathematical Modeling Method of the Improved Genetic Algorithm for Random Power Fluctuation
2022
International Transactions on Electrical Energy Systems
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Finally, the power function optimization experiment and the IIR digital filter optimization design are carried out, and the standard GA, NQGA, CAGA, and LARES algorithms are carried out compared. ...
In order to solve the problem that the traditional genetic algorithm has a slow search speed and is easy to fall into the local optimal solution, a mathematical modeling method of an improved genetic algorithm ...
IIR Digital Filter Optimization Design. e following uses CGA to directly optimize the design of the IIR digital filter in the frequency domain. e IIR digital filter adopts the cascade structure of the ...
doi:10.1155/2022/1889952
fatcat:lo76rvo5pzfnvjolinsqmcsof4
IIR system identification using differential evolution with wavelet mutation
2014
Engineering Science and Technology, an International Journal
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plant coefficients and mean square error (MSE) values produced for both the same order and reduced order models of adaptive IIR filters. ...
Apart from this, the proposed technique DEWM has alleviated from inherent drawbacks of premature convergence and stagnation, unlike Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). ...
In the present work adaptive IIR filter is considered for identifying/modelling an unknown plant. ...
doi:10.1016/j.jestch.2014.02.002
fatcat:d4b2cjcce5gj5gqibz5a3asylq
Application of Tissue P Systems in Optimal IIR Filter Design
2016
ICIC Express Letters
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To overcome the shortcomings in IIR filter design, this paper proposes a novel P systems-based method for optimal IIR filter design. ...
Based on the ring structure, an evolution mechanism is developed for the objects in cells. ...
Unknown IIR system Adaptive IIR filter x(k) ¦ d(k) y(k) Optimization algorithm e(k) Figure 1 . IIR system identification based on an adaptive IIR filter 3. Proposed Design Method Based on P Systems. ...
doi:10.24507/icicel.10.03.613
fatcat:kgd4ujib75ei3evqdzbvaia27a
Structure Evolution Based Optimization Algorithm for Low Pass IIR Digital Filter Design
2017
International Journal of Computational Intelligence Systems
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It is a promising way for optimized and automated design of digital filters. ...
This paper proposes a structure-evolution based optimization algorithm (SEOA) which allows the integrated consideration of structure issues and frequency response specifications in design stage. ...
However, its disadvantages are lack of good local search ability and premature convergence. 16 Particle Swarm Optimization (PSO) algorithm 17 has been used in the digital IIR filter design. ...
doi:10.2991/ijcis.2017.10.1.69
fatcat:qmd2qdcd6jak5e7c2upk7jzvp4
Adaptive Particle Swarm Optimization Algorithm Ensemble Model Applied to Classification of Unbalanced Data
2021
Scientific Programming
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This paper proposes a random forest-based adaptive particle swarm optimization on data classification, and an adaptive particle swarm used to optimize the hyperparameters in the random forest to ensure ...
Aiming at the premature convergence that appears in the particle swarm optimization algorithm, the population is adaptively divided according to the population fitness and the adaptive update strategy ...
RF, as an ensemble learning method, is usually used to solve the problem of unbalanced data classification. is paper proposes a particle swarm optimization strategy based on adaptive partitioning, which ...
doi:10.1155/2021/7589756
fatcat:v3blvvhlczcirod3g3okcyny7u
Design of optimal linear phase FIR high pass filter using craziness based particle swarm optimization technique
2012
Journal of King Saud University: Computer and Information Sciences
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In this paper, an optimal design of linear phase digital high pass FIR filter using Craziness based Particle Swarm Optimization (CRPSO) approach has been presented. ...
Genetic Algorithm (RGA), and conventional Particle Swarm Optimization (PSO). ...
This modified PSO is termed as Craziness based Particle Swarm Optimization (CRPSO). ...
doi:10.1016/j.jksuci.2011.10.007
fatcat:6ykvf3ulf5asjnwdcas7zdr6h4
Adaptive IIR Filter Design Using Self-Adaptive Search Equation based Artificial Bee Colony Algorithm
2019
Turkish Journal of Electrical Engineering and Computer Sciences
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This work deals with the self-adaptive search-equation-based artificial bee colony (SSEABC) algorithm that is adapted to optimal IIR filter design. ...
In order to demonstrate the performance of the SSEABC algorithm on IIR filter design, we have also used canonical ABC, modified ABC (MABC), best neighbor-guided ABC, and an ABC with an adaptive population ...
Improved particle swarm optimization (IPSO) is proposed by Zou et al. and it is applied to the IIR system identification problem [5] . ...
doi:10.3906/elk-1809-83
fatcat:scob6gw3e5h6pccti7hvbl3iii
Digital FIR Filter Design Using Hybrid Random Particle Swarm Optimization with Differential Evolution
2013
International Journal of Computational Intelligence Systems
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search direction but sometime causes instability problem; whereas, PSO is a robust, population based stochastic search technique but has the problem of sub-optimality . ...
In this paper, the Random PSO is used which utilises the weighted particle to guide the search direction for both explorative and exploitative searches. ...
In Figure 6 , the Digital Filter 2 block serves the designed LP filter using the RPSODE based optimal filter coefficients of Table 2 . ...
doi:10.1080/18756891.2013.808427
fatcat:dduc5yuyyzbw5nzynocxjmepby
Design of 2-D Recursive Filters Using Self-adaptive Mutation Differential Evolution Algorithm
2011
International Journal of Computational Intelligence Systems
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This paper investigates a novel approach to the design of two-dimensional recursive digital filters using differential evolution (DE) algorithm. ...
The design task is reformulated as a constrained minimization problem and is solved by an Self-adaptive Mutation DE algorithm (SAMDE), which adopts an adaptive mutation operator that combines with the ...
Acknowledgements The authors would like to thank the reviewers for their useful comments for improving the paper quality. ...
doi:10.1080/18756891.2011.9727819
fatcat:gru44ttuxvfk7biyvupawgkuou
Design of 2-D Recursive Filters Using Self-adaptive Mutation Differential Evolution Algorithm
2011
International Journal of Computational Intelligence Systems
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This paper investigates a novel approach to the design of two-dimensional recursive digital filters using differential evolution (DE) algorithm. ...
The design task is reformulated as a constrained minimization problem and is solved by an Self-adaptive Mutation DE algorithm (SAMDE), which adopts an adaptive mutation operator that combines with the ...
Acknowledgements The authors would like to thank the reviewers for their useful comments for improving the paper quality. ...
doi:10.2991/ijcis.2011.4.4.20
fatcat:4judyqnwtncqxhnum4aq3jbrdq
Optimal design and low noise realization of digital differentiator
2022
Journal of Electrical Engineering
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It manifests the minimization of the L1 -error objective function by using a hybrid optimization technique consisting of the particle swarm and simulated annealing optimization algorithm. ...
This manuscript presents a design of a differentiator in the digital domain with its low noise realization. ...
Hybrid optimization for the design of digital differentiator This section gives a short description of the hybrid optimization consisting of particle swarm optimization (PSO) and simulated annealing optimization ...
doi:10.2478/jee-2022-0044
fatcat:l5obmo2xundwdnwzttx3imzjvu
Particle Swarm Optimization and Differential Evolution Algorithms: Technical Analysis, Applications and Hybridization Perspectives
[chapter]
2008
Studies in Computational Intelligence
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This chapter provides two recent algorithms for evolutionary optimization -well known as particle swarm optimization (PSO) and differential evolution (DE). ...
Unfortunately, these derivative based optimization techniques can no longer be used to determine the optima on rough non-linear surfaces. ...
This type of filter is hence said to be nonrecursive. On the other hand, an IIR filter is one whose impulse response (theoretically) continues for ever in time. ...
doi:10.1007/978-3-540-78297-1_1
fatcat:4vrohifuinbu3atpbnm5vrrdqu
An Efficient Adaptive System Identification Technique Based on Wind Driven Optimization Method
2016
Indian Journal of Science and Technology
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Objectives: This paper presents a novel methodology for estimating the parameters of an unknown system or a plant using Wind Driven Optimization (WDO) based adaptive identification model. ...
Application/Improvements: The proposed adaptive identification model can be widely used in instrumentation, acoustic noise and vibration control, power system, telecommunication, adaptive guidance or fault ...
Weights are initialized to any random values learning particle swarm optimization (CLPSO) 16 . ...
doi:10.17485/ijst/2016/v9i38/94883
fatcat:jhzqtiokpneuncqyczu5jefnbm
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