Performance Evaluation of Evolutionary Algorithms for Optimal Filter Design

Vural, Revna Acar; Yıldırım, Tülay; Kadioğlu, Tevfik; Basargan, A.

doi:10.1109/tevc.2011.2112664

Cited by 98 publications

(43 citation statements)

References 21 publications

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“…Since chaotic motion [2] can traverse all states within the specified range without repetition by its own "laws", we fully extract and capture the solution space by chaotic mapping to enhance diversity in the bee population.…”

Section: Improved Abc Algorithmmentioning

confidence: 99%

“…Since the ABC algorithm is simple in concept and structure, is easy to implement, has few control parameters, and has outstanding performance, it has been widely used in many fields, such as optimal filters, chaotic systems, optimal power flow, and blind source separation [2][3][4][5]. It was also applied to classify remote sensing images, constraint multi-objective evolutionary, and SVM parameter optimization [6][7][8].…”

Section: Introductionmentioning

confidence: 99%

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An improved artificial bee colony algorithm

Wang

2018

The 2nd World Conference on Humanities and Social Sciences (WCHSS 2017)

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Abstract.To improve the performance of artificial bee colony algorithm, a modified artificial bee colony algorithm is proposed. The modified ABC algorithm takes advantage of chaotic mapping to enhance diversity in the bee population, uses information of a better solution to guide the search of candidate solutions toward a promising direction that improves exploitation, and introduces a global solution into the scout stage in order to jump out of the local optimal value. The modified ABC algorithm balances exploration and exploitation, which contradict each other, so that it can achieve optimal performance. Simulation results show the proposed method has more accuracy than the other methods.

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Section: Improved Abc Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An improved artificial bee colony algorithm

Wang

2018

The 2nd World Conference on Humanities and Social Sciences (WCHSS 2017)

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“…As is well known, various evolutionary algorithms have been presented and have been applied to optimization problems in various systems. For example, analog/digital filters, switching power converters, and neural networks [11][12][13][14][15][16][17][18][19]. The design of dynamic digital circuit is an important/effective object in the applications.…”

Section: Introductionmentioning

confidence: 99%

Realization of desired digital spike-trains by a simple evolutionary algorithm

Saito

Yamaoka

Hamaguchi

2017

NOLTA

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This paper studies realization of desired digital spike-trains based on a simple evolutionary algorithm. First, the dynamics of spike-trains is visualized by a digital spike map. The map is defined on a set of points and is represented by a characteristic vector of integers. Second, in order to realize desired spike-trains, we present a simple evolutionary algorithm that aims at optimization of the characteristic vector for a cost function. We also present a simple method to super-stabilize desired spike-trains. Third, in order to implement the digital spike map, we introduce a digital spiking neuron consisting of two shift registers and a wiring between them. An elementary FPGA-based circuit is presented and a super-stable spike-train is demonstrated.

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“…This method uses a SPICE-type netlist to describe the circuit and SPICE-based simulations to evaluate their fitness. In [5] an extended state of the art for analog filter synthesis based on genetic programming can be found. This paper takes as starting point the work developed in [4] and aims to prove the capability of genetic programming to create new structures of power processing circuits.…”

Section: Introductionmentioning

confidence: 99%

Generation of new power processing structures exploiting genetic programming

Doménech‐Asensi

Kázmierski

2017

2017 IEEE 26th International Symposium on Industrial Electronics (ISIE)

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Abstract-This paper describes the use of genetic algorithms to generate power processing circuits. In order to speed up the algorithm, the fitness of the circuits is evaluated using an explicit integration method based on the 4 th order Adams-Bashforth formula. Different combinations of genetic primitives for the crossover and mutation processes have been tested. The algorithm is demonstrated by generating new structures of voltage multipliers, which specifically focus on energy harvesting systems. These systems require low input voltages, usually under the diode threshold value. The Adams-Bashforth method allows to achieve a simulation time that is about five times faster than that of SPICE-based simulations.

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Performance Evaluation of Evolutionary Algorithms for Optimal Filter Design

Cited by 98 publications

References 21 publications

An improved artificial bee colony algorithm

An improved artificial bee colony algorithm

Realization of desired digital spike-trains by a simple evolutionary algorithm

Generation of new power processing structures exploiting genetic programming

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