FIR and IIR digital filters

Litwin, L.

doi:10.1109/45.877863

Cited by 78 publications

(40 citation statements)

References 1 publication

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“…The signals were filtered by finite impulse filters (FIR), which are more stable and less sensitive to coefficient quantification errors than infinite impulse filters (IIR) [15], although they require higher computing power.…”

Section: Data Treatmentmentioning

confidence: 99%

Cardiorespiratory effects induced by vagus nerve stimulation in epileptic children

Pruvost¹,

Zaaimi²,

Grebe³

et al. 2006

Med Bio Eng Comput

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Vagus nerve stimulation (VNS) is used in pharmaco-resistant epilepsy to decrease the number of seizures. Although it is well known that VNS affects respiration, there are only a few reports concerning an effect of VNS on heart rate or heart rate variability (HRV). We investigated the relationship between respiratory frequency and the high frequency (HF) domain of the discrete Fourier transform (DFT) of the RR interval function during night sleep recordings of ten subjects treated with VNS. Our results show that VNS shifts the frequency of maximal power spectrum density (PSD) in the HF-band, decreases the related PSD and induces a partial cardiorespiratory decoupling.

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Section: Data Treatmentmentioning

confidence: 99%

Cardiorespiratory effects induced by vagus nerve stimulation in epileptic children

Pruvost¹,

Zaaimi²,

Grebe³

et al. 2006

Med Bio Eng Comput

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“…They have wide range of applications in communication, image processing, pattern recognition, etc. There are two major classes of digital filters, i.e., finite impulse response (FIR) filters and infinite impulse response (IIR) filters depending on the length of the impulse response [1] . FIR filter is an attractive choice because of the ease in design and stability.…”

Section: Introductionmentioning

confidence: 99%

Optimal linear phase finite impulse response band pass filter design using craziness based particle swarm optimization algorithm

Mandal

Sakti

Kar

et al. 2011

J. Shanghai Jiaotong Univ. (Sci.)

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An efficient method is proposed for the design of finite impulse response (FIR) filter with arbitrary pass band edge, stop band edge frequencies and transition width. The proposed FIR band stop filter is designed using craziness based particle swarm optimization (CRPSO) approach. Given the filter specifications to be realized, the CRPSO algorithm generates a set of optimal filter coefficients and tries to meet the ideal frequency response characteristics. In this paper, for the given problem, the realizations of the optimal FIR band pass filters of different orders have been performed. The simulation results have been compared with those obtained by the well accepted evolutionary algorithms, such as Parks and McClellan algorithm (PMA), genetic algorithm (GA) and classical particle swarm optimization (PSO). Several numerical design examples justify that the proposed optimal filter design approach using CRPSO outperforms PMA and PSO, not only in the accuracy of the designed filter but also in the convergence speed and solution quality.

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“…FIR filters are simple to design and they are guaranteed to be bounded-input, bounded-output; namely, they are always stable filters. By designing the filter taps to be symmetrical about the center tap position, an FIR filter can be guaranteed to have linear phase [15].…”

Section: Introductionmentioning

confidence: 99%

Design of Digital FIR Filters Using Differential Evolution Algorithm

Karaboğa

Cetinkaya

2006

Circuits Syst Signal Process

139

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The differential evolution (DE) algorithm is a new heuristic approach with three main advantages: it finds the true global minimum of a multimodal search space regardless of the initial parameter values, it has fast convergence, and it uses only a few control parameters. The DE algorithm, which has been proposed particularly for numeric optimization problems, is a population-based algorithm like the genetic algorithms and uses similar operators: crossover, mutation, and selection. In this work, the DE algorithm has been applied to the design of digital finite impulse response filters, and its performance has been compared to that of the genetic algorithm and least squares method.

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FIR and IIR digital filters

Cited by 78 publications

References 1 publication

Cardiorespiratory effects induced by vagus nerve stimulation in epileptic children

Cardiorespiratory effects induced by vagus nerve stimulation in epileptic children

Optimal linear phase finite impulse response band pass filter design using craziness based particle swarm optimization algorithm

Design of Digital FIR Filters Using Differential Evolution Algorithm

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