2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI) 2016
DOI: 10.1109/icacci.2016.7732460
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Design of linear phase low pass FIR filter using restart particle swarm optimization

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Cited by 5 publications
(3 citation statements)
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“…The performances of PSD and BER about different prototype filters using optimization based techniques are given in Figure 9e and Figure 9f, respectively. The evolutionary algorithms in References [131][132][133][134][135] are used for linear phase FIR filter design in recent years, and they could be taken into account in multicarrier modulation applications. In this paper, FBMC based systems using five different evolutionary algorithms are simulated, as shown in Figure 9e,f.…”
Section: Optimization Based Methodsmentioning
confidence: 99%
“…The performances of PSD and BER about different prototype filters using optimization based techniques are given in Figure 9e and Figure 9f, respectively. The evolutionary algorithms in References [131][132][133][134][135] are used for linear phase FIR filter design in recent years, and they could be taken into account in multicarrier modulation applications. In this paper, FBMC based systems using five different evolutionary algorithms are simulated, as shown in Figure 9e,f.…”
Section: Optimization Based Methodsmentioning
confidence: 99%
“…In Reference [133], the restart PSO (RPSO) is used to design the FIR filter. Compared with PSO, the RPSO algorithm depends on the two following criteria:…”
Section: Gupta's Methodsmentioning
confidence: 99%
“…The performances of PSD and BER about different prototype filters using optimization based techniques are given in Figure 9e,f, respectively. The evolutionary algorithms in References [131][132][133][134][135] are used for linear phase FIR filter design in recent years, and they could be taken into account in multicarrier modulation applications. In this paper, FBMC based systems using five different evolutionary algorithms are simulated, as shown in Figure 9e,f.…”
Section: Optimization Based Methodsmentioning
confidence: 99%