Noniterative design of IIR multiple‐notch filters with improved passband magnitude response

Nikolić, Saša V.; Krstić, Ivan; Stančić, Goran

doi:10.1002/cta.2525

Cited by 3 publications

(3 citation statements)

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“…10 Various IIR multi-notch filter design methods can be found in the literature, while great majority of them can be classified into one of the following three approaches: cascading, 11,12 optimal poles placement, [13][14][15] and allpass based. [16][17][18][19] Transfer function of the IIR multi-notch filter, when the cascading approach is considered, is obtained by cascading several IIR single-notch filters. This approach is known to provide good results if notch frequencies are well separated and notch bandwidths are narrow.…”

Section: Introductionmentioning

confidence: 99%

“…[16][17][18] On the other hand, if the order of the IIR multi-notch filter is not minimal, unknown filter coefficients can be determined by solving the quadratic programming optimization problem. 19 The practical success of the minimum-order IIR multi-notch filter allpass-based design methods lies in a fact that these methods are characterized by simple expressions for the coefficients values. Additionally, allpass-based IIR multi-notch filters can be realized using efficient lattice structures.…”

Section: Introductionmentioning

confidence: 99%

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The least‐square design of minimum‐order allpass‐based infinite impulse response multi‐notch filters

Krstić

2021

Circuit Theory & Apps

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The paper investigates the least-square design of minimum-order infinite impulse response multi-notch filters. Monotonically decreasing nature of the stable allpass filter's phase response, characterizing the allpass-based multinotch filter, along with the simple relation between coefficients and the phase response of the allpass filter, allows the formulation of the multi-notch filter's magnitude response specifications as the linear equality constraints regarding the positions of notch, left-and right-hand cutoff frequencies. Since the number of such constraints equals triple the number of notch frequencies,

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The least‐square design of minimum‐order allpass‐based infinite impulse response multi‐notch filters

Krstić

2021

Circuit Theory & Apps

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“…There are a few ways to deal with the IIR multiple‐notch filter. The All‐pass‐based IIR filter technique initially changed the particulars of multiple‐notch filter magnitude response into those of the stage response of a comparing all‐pass channel 10 …”

Section: Introductionmentioning

confidence: 99%

An efficient priority‐based convolutional auto‐encoder approach for electrocardiogram signal compression in Internet of Things based healthcare system

Mahendran

Parthasarathy

Parthasarathy³

et al. 2020

Trans Emerging Tel Tech

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Due to advancements in healthcare monitoring systems, the Internet of Things concepts are proficiently utilized in the medical field to detect and diagnose the physical health problems. The compression of more substantial medical information is a significant issue that requires ample data storage space and takes longer transmission time. Though several compression algorithms are actualized in past cases, there is an absence of an upgraded approach to achieve improved signal compression without influencing signal quality. Hence a proficient signal compression algorithm is proposed in our work to provide an enhanced electrocardiogram (ECG) signal compression without any data loss and to acquire increased compression ratio (CR) and zero construction error. In this proposed approach, the input ECG signal dataset from the MIT‐BIH arrhythmia database gets influenced by noise because of the electrical measuring gadget. Hence, preprocessing is done by the proposed multi‐scoop notch filter (MSNF) to denoise this signal by removing the specified noise frequency range of around (1‐50) Hz. This proposed MSNF is designed with adaptiveness that has achieved the enhanced denoising by adjusting the notch frequency. In addition, to extricate the sophisticated ECG signal features, Fast Fourier Transform is being utilized, and that performs and decomposes the signal elegantly and obtains characteristics of the signal in the frequency domain. After feature extraction, optimal signal compression is performed by our proposed priority‐based convolutional auto‐encoder (PCAE) that provides better compression with almost zero reconstruction error by encoding the signals into lower‐dimensional vectors in convolutional layers which are again reconstructed using a decoding approach. The experimental results are then assessed using the performance metrics that include signal to noise ratio (SNR), CR, and percentage root‐mean‐square difference (PRD). The attained results are 1.83% as average PRD value, average SNR is about 33 dB, and average CR is about 35.2% whereas the traditional CAE approach has average values of 2.05% PRD, 23.45 dB SNR, and 32.2% CR.

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Design of minimum-order allpass-based IIR multi-notch filters

Krstić¹,

Jovanović²

2022

Digital Signal Processing

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Noniterative design of IIR multiple‐notch filters with improved passband magnitude response

Cited by 3 publications

References 8 publications

The least‐square design of minimum‐order allpass‐based infinite impulse response multi‐notch filters

The least‐square design of minimum‐order allpass‐based infinite impulse response multi‐notch filters

An efficient priority‐based convolutional auto‐encoder approach for electrocardiogram signal compression in Internet of Things based healthcare system

Design of minimum-order allpass-based IIR multi-notch filters

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