Electronically Tunable Fully-Differential Fractional-Order Low-Pass Filter

Langhammer, Lukáš; Dvořák, Jan; Šotner, Roman; Jeřábek, Jan

doi:10.5755/j01.eie.23.3.18332

Cited by 11 publications

(3 citation statements)

References 30 publications

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“…Due to heat voltage V T , capacitance C and current sync. On the off chance that the impact of temperature on the corner recurrence is additionally shown as appeared within the condition (7). Subsequently, Table 1 shows the affectability.…”

Section: Sensitivitiesmentioning

confidence: 97%

“…The filter circuit can be further divided into four functional types, Low pass filter: LPF, High pass filter: HPF, Band pass filter: BPF, Notch filter or Eliminate filter: BEF and Low-pass filters are important and have a wide range of applications. For example, in mobile communication systems analog signal processing and in biomedical systems [2][3][4][5][6][7][8]. The low-pass filter to detect biological signals generally uses a voltage in the range of 1V-100 mV and a cut-off frequency below 100 Hz [9][10][11][12][13].…”

Section: Introductionmentioning

confidence: 99%

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The development a fully-balanced current-tunable first-order low-pass filter with Caprio technique

Lertkonsarn

Sa-ngiamvibool

2022

Eureka: PE

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This paper presents the development and design of a fully-balanced current-tunable first-order low-pass filter with Caprio technique, which could include the design and implementation of a first-order low-pass filter circuits. The filter consists of six bipolar junction transistor (BJT) and a single capacitor. The filter construction uses a bipolar junction transistor (BJT) as the main device and a single capacitor. A fully-balanced current-tunable first-order low-pass filter with Caprio technique developed. The architecture of the circuit is quite simple and proportional, symmetrical with signs of difference. Circuits developed into integrated circuits act like basic circuits for frequency filter circuits, current modes with Caprio techniques, obtained by improving the first-order low-pass filter for signal differences with incoming impedances. Adjusting the parameters of the circuit with the caprio technique achieves the optimal parameter value for correcting the total harmonic distortion value. The results of testing the operation of the circuit, a fully-balanced current-tunable first-order low-pass filter with Caprio technique developed and designed using the PSpice program. The simulation results showed good results in line with predicted theoretical analysis. The sensitivity of the device to the center frequency (ω0) response is low and independent of variables, the angular frequency is linear with wide current adjustment throughout the sweeping range of a wide frequency range, with a wide range of over tree orders of magnitude. Therefore, fully-balanced current-tunable first-order low-pass filter developed is very suitable to apply various applications regarding low frequency signal filtration, for example in biomedical systems, for example.

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Section: Sensitivitiesmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

The development a fully-balanced current-tunable first-order low-pass filter with Caprio technique

Lertkonsarn

Sa-ngiamvibool

2022

Eureka: PE

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“…The distribution of these non-Gaussian signals, featuring a finite variance and long tails, can be described as processes with a finite or infinite variance. In engineering applications, non-Gaussian signals often obey alpha (α)-stable distribution [1][2][3][4][5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

An Adaptive Filtering Algorithm for Non-Gaussian Signals in Alpha-Stable Distribution

Yang¹

2020

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Currently, many adaptive filtering algorithms are available for the non-Gaussian environment, namely, least mean square (LMS) algorithm, recursive least square (RLS) algorithm, least mean fourth (LMF) algorithm, and subspace minimum norm (SMN) algorithm. Most of them can converge to the steady-state, but face various constraints in the presence of alpha (α)-stable noises. To solve the problem, this paper aims to develop an adaptive filtering algorithm for non-Gaussian signals in α-stable distribution, drawing on the merits of existing adaptive filtering algorithms. Firstly, the authors introduced the theory of α-stable distribution, the central limit theorem and fractional lower-order statistics (FLOS). Next, two classic adaptive filtering algorithms, RLS and LMS, were summarized, and compared through tests. On this basis, the FLOS-SMN algorithm was designed in the light of the features of the LMS and the SMN, which applies to the filtering of non-Gaussian signals in αstable distribution. Finally, the proposed algorithm was proved as faster, more stable and more adaptable than the traditional method.

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Fractional Order Elliptic Filter Implemented Using Optimization Technique

Soni

Gupta²

2021

Cognitive Informatics and Soft Computing

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Electronically Tunable Fully-Differential Fractional-Order Low-Pass Filter

Cited by 11 publications

References 30 publications

The development a fully-balanced current-tunable first-order low-pass filter with Caprio technique

The development a fully-balanced current-tunable first-order low-pass filter with Caprio technique

An Adaptive Filtering Algorithm for Non-Gaussian Signals in Alpha-Stable Distribution

Fractional Order Elliptic Filter Implemented Using Optimization Technique

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