A new realization of wave digital filters using GIC and fractional bilinear transform

Barsainya, Richa; Rawat, Tarun Kumar; Mahendra, Rachit

doi:10.1016/j.jestch.2015.08.008

Cited by 8 publications

(3 citation statements)

References 14 publications

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“…Step 3: Update the velocities and positions of each particle using fitness function given in (9), (12), (14), and (17), respectively. The particles are shifted towards g best after each iteration in order to reach to the best solution.…”

Section: Particle Swarm Optimisationmentioning

confidence: 99%

“…Step 3: Carry out Lévy flights given in (20) to get new nest's position x k + 1 . Compute fitness of new nest f k + 1 using fitness function given in (9), (12), (14), and (17), respectively.…”

Section: Cuckoo Search Algorithmmentioning

confidence: 99%

“…The LWDF structures exhibit various attractive properties such as low coefficient sensitivity and consequently, the low accuracy requirements for the register word length, higher dynamic range, higher overflow level, lower round-off noise, assurance of stability, and good non-linear properties under finitearithmetic conditions where the effects of rounding, truncation, and overflow are present [7][8][9]. LWDF structures are preferent for realisation of notch-comb filter, LP-highpass filter, integrator, differentiator, and Hilbert transformers [10][11][12][13][14] as their ensuing structures are highly modular, have low sensitivity to coefficient variation, and minimal hardware utilisation.…”

Section: Introductionmentioning

confidence: 99%

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Optimal design of minimum multiplier lattice wave digital lowpass filter using metaheuristic techniques

Barsainya¹,

Aggarwal

Rawat

2018

IET signal process.

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This study aims towards the efficient design of arbitrary-band and halfband lowpass (LP) filter based on lattice wave digital filter (LWDF) structure with the usage of minimal number of multipliers in its structural realisation. The designing of the LP filter is formulated as an optimisation problem where coefficients of LWDF transfer function are iteratively optimised by the evolutionary algorithms. The potential of four optimisation algorithms, real-coded genetic algorithm, particle swarm optimisation, differential evolution algorithm, and cuckoo search algorithm, are explored for determining the optimal LWDF coefficients by minimising the error objective function. The structural realisation of LP using LWDF structure enhances the design accuracy as the usage of multiplier prominently reduces. The simulation and statistical results of the proposed lattice wave digital lowpass filter (LWDLF) and bireciprocal lattice wave digital lowpass filter (BLWDLF) design show significant improvement in the mean square error, passband ripples, transition bandwidth, stopband attenuation, rate of convergence, and execution time. To manifest the efficient design of the proposed LWDLF and BLWDLF, the results are compared with the designed arbitrary-band, halfband canonic-LP filters and previous published works.

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Section: Particle Swarm Optimisationmentioning

confidence: 99%