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Clinically, electrocardiogram (ECG) is a powerful tool for determining the health and functioning of the human heart. Faster detection and diagnosis of heart functioning would aid cardiologists to provide appropriate treatment to the patients (subjects). In this paper, the concept of fractional-order calculus is employed for noise cancellation and artifacts removal in ECG signal as fractional-order differentiator proved to provide more peculiar details about signals than an integer-order differentiator. In the proposed method, R-peaks are detected using Riesz fractional-order digital differentiator (RFODD) based on the differencing method. The differentiation operation enhances the high-frequency components of the signal. So, QRS complex which is a high-frequency component in ECG is accentuated and the R-peaks are detected using appropriate threshold technique. The proposed method is tested on Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH) arrhythmia database, and the experimental results of the proposed method have achieved a sensitivity of 99.95%, positive predictivity of 99.949% and an error rate of 0.095%. ECG waveforms are analyzed on various fractional orders of RFODD, and their performance parameters, i.e., sensitivity, positive predictivity and error rate, are also calculated.

Optimal designs of finite impulse response (FIR) digital filters with prescribed magnitude and phase responses have found many applications in signal processing. To deal with the nonconvexity of the constraint region in the phase-error and magnitude-error constrained design, a new error constraint method based on a modified annulus sector (MAS) is proposed. With the new constraint method, the phase-error and magnitude-error constrained least squares, phase-error constrained minimax, and iterative reweighted phase-error constrained minimax designs of FIR filters are studied. Analyses and design examples demonstrate the higher accuracy of the MAS constraint and better filter performance by the constraint method than existing constraint methods. An application in the design of digital differentiators with flatness constraints is also provided.

This paper proposes a Novel least mean square algorithm using First order Al-Alaoui differentiator.The performance of the proposed Algorithm is compared with existing algorithms by taking an example. The results prove the efficacy of the proposed Algorithm.

This paper presents all-digital time-mode $$\Delta \Sigma$$ modulators. The proposed modulators consist of a voltage-to-time integrator, a seven-stage gated ring oscillator functioning as a 3-bit quantizer, and seven digital differentiators. A detailed analysis of the nonlinear characteristics of the modulators is provided. Designed in IBM 130 nm 1.2 V CMOS technology with a 100 mV 100 kHz sinusoidal input and a 4.4 MHz frequency clock, the first-order modulator provides 47 dB SNR over 0–150 KHz bandwidth while consuming 1.1 mW while the second-order modulator provides 55 dB SNR over the same bandwidth while consuming consumes 1.45 mW.

A new efficient algorithm for calculating the weighting coefficients of maximally linear, FIR digital differentiators is presented. Simple closed-form explicit and recursive formulas are derived in a very straightforward manner. Moreover, a simple recursive equation is established, relating coefficients of two digital differentiators of adjacent ranks.

An efficient design of digital differentiators (DD), with a variable frequency range of operation at low and midband frequencies, has been proposed. Implemented as a Taylor structure, a DD designed for orderN can be made to function as a universal configuration giving optimal transfer functions for all possible ordersN, without changing the coefficients.