Allpass-based design, multiplierless realization and implementation of IIR wavelet filter banks with approximate linear phase

Abdul–Jabbar, Jassim M.; Hmad, Rasha W.

doi:10.1109/isiict.2011.6149606

Cited by 8 publications

(8 citation statements)

References 8 publications

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“…A down sampler to alter the sampling rate and to divide the order of the all-pass filters and the delay by 2 [16], [20]. This makes the design more simpler.…”

Section: Matlab Simulation Results Of the Overall Designed Systemmentioning

confidence: 99%

Genetic-Based IIR Filter Design for Efficient QRS Complex Detection using Neuro-Based Classifier

Abdul–Jabbar¹,

Saadi²

2015

(AREJ)

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In this paper, a new method is proposed for QRS complex detection using a special kind of IIR filter called bi-reciprocal lattice wave digital filter (WDF). This filter has some attractive features that make it more efficient than other types of filters. One of these features is its sufficient linear phase in the passband, thus yielding a perfect reconstraction condition. Therefore, it is not required to cascade the designed filter with an all-pass filter for correcting the phase distortion. The coefficients of the designed filter are achieved by simulating the FIR response suggested in [1]. A least square method solution is used in such simulation with a genetic-based algorithm. A simplified structure for the designed filter is accomplished with less-complex realization. 50 records of European ST -T ECG database is classified into four classes (Normal, Left Bundle Branch Block (LBBB), ST segment elevation, and Left Ventricular Hypertrophy (LVH)). By applying the designed filter coefficients into neural network classifier, the results show that the accuracy of the classification process is 95.9 %.

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“…A down sampler to alter the sampling rate and to divide the order of the all-pass filters and the delay by 2 [16], [20]. This makes the design more simpler.…”

Section: Matlab Simulation Results Of the Overall Designed Systemmentioning

confidence: 99%

Genetic-Based IIR Filter Design for Efficient QRS Complex Detection using Neuro-Based Classifier

Abdul–Jabbar¹,

Saadi²

2015

(AREJ)

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“…The idea of LIFO register in Ref. [12] is used for anticausal implementation of advancing element ( ) in the analysis and synthesis structures. The implementation results for analysis and synthesis sides are presented in Tables1 and 2, respectively.…”

Section: Fpga Implementationmentioning

confidence: 99%

A Novel Design and FPGAImplementation of TheBiorthogonal 5/3 Filter Bank-eng

Abdul–Jabbar¹,

Alomari²,

Hmad³

et al. 2013

(AREJ)

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In this paper, the DWT introduced through the design of the biorthogonal 5/3 filter bank using the lattice structure. The lattice coefficients of the proposed structure are very suitable for implementation using shift-only operations (with a single shift and add operation) instead of multipliers to perform multiplications. This results in a recognizable hardware saving when implementing such lattice structure hardwarly. The designed filter bank implemented using Matlab programming for verification. Matlab programs are also used to find the PSNR values that are taken for a group of standard gray scale images as objective criteria for efficiency, resulting in high PSNR values of around 55dB. The efficiency of the results also measured subjectively, for some standard gray scale images by comparing the original input images with the resulting ones from combining both analysis and synthesis sides of the proposed DWT structure. The efficient FPGA implementation of such design is considered to show its simplicity.

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“…coif 4) [1]- [3]. On the other hand, the use of IIR wavelet filter banks are less extensive and limited to image processing and compressing applications [4], since the synthesis filter bank requires anticausal filters for cancelling out the phase distortion caused by the phase non-linearity. The casual implementation of an anticausal filter is only possible if the data fed to the system is finite and can be time-reversed for signal reconstruction which is a restriction for continuous infinite data.…”

Section: Introductionmentioning

confidence: 99%

Hybrid IIR/FIR Wavelet Filter Banks for ECG Signal Denoising

Eminaga

Coskun

Kale

2018

2018 IEEE Biomedical Circuits and Systems Conference (BioCAS)

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ElectroCardioGram (ECG) signals are usually corrupted with various types of noise/artifacts such as baseline wander and muscle contraction artifacts which degrade the signal quality and might lead to misdiagnosis of the patient. The wavelet denoising technique is widely studied in the artifact removal literature which employs conventional Finite Impulse Response (FIR) wavelet filter banks for decomposing, thresholding and reconstructing the noisy signal to obtain high fidelity and clean ECG signal. However, the use of high order FIR wavelet filters increases the hardware complexity and cost of the system. This paper presents novel hybrid Infinite Impulse Response (IIR)/FIR Discrete Wavelet Transform (DWT) filter banks that can be employed in ambulatory health monitoring applications for denoising purposes. The proposed systems are evaluated and compared to the conventional FIR based DWT systems in terms of the computational complexity as well as the denoising performance. For this purpose, raw ECG data from MIT-BIH arrhythmia database are contaminated with synthetic noise and denoised with the aforementioned filter banks. The results from 100 Monte Carlo simulations demonstrated that the proposed filter banks provide better denoising performance with fewer arithmetic operations than those reported in the open literature.

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Allpass-based design, multiplierless realization and implementation of IIR wavelet filter banks with approximate linear phase

Cited by 8 publications

References 8 publications

Genetic-Based IIR Filter Design for Efficient QRS Complex Detection using Neuro-Based Classifier

Genetic-Based IIR Filter Design for Efficient QRS Complex Detection using Neuro-Based Classifier

A Novel Design and FPGAImplementation of TheBiorthogonal 5/3 Filter Bank-eng

Hybrid IIR/FIR Wavelet Filter Banks for ECG Signal Denoising

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