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CMOS analog amplifier circuits are integral components in the signal-processing stages of consumer electronics. They also find applications in advanced imaging systems, augmented reality devices, smartphone audio applications, power management circuits, etc. The differential and two-stage operational amplifier circuits must be optimally designed for next-generation consumer electronics devices, where speed and sizing are important constraints. This nonlinear constrained optimization problem can be resolved using evolutionary optimization techniques. This article proposes an efficient design technique for a CMOS differential amplifier circuit and CMOS two-stage op-amplifier. A well-known optimization problem is the particle swarm optimization (PSO). PSO is a robust optimization method but may suffer from premature convergence and slow convergence speed. The evolutionary technique used here is the modified version of the PSO, named Levy flight, power function, and Singer map utilized PSO (LPSPSO). In PSO, the Levy flight can enhance the exploration capability and improve the convergence speed. The proposed evolutionary technique reduces the individual circuits’ area and design time while satisfying the design constraint. The LPSPSO-based results are authenticated with SPICE. SPICE results demonstrate that LPSPSO is an efficient evolutionary technique than formerly reported methods in designing analog amplifiers in terms of MOS area, gain, power dissipation, etc.

This paper deals with the optimal design of different VLSI circuits, namely, the CMOS voltage reference circuit and the CMOS ring oscillator (RO). The optimization technique used here is the multiobjective differential evolution algorithm (MDEA). All the circuits are designed for 90 nm technology. The main objective of the CMOS voltage reference circuit is to minimize the voltage variation at the output. The targeted value of the reference voltage is 550 mV. A CMOS ring oscillator (RO) is designed depending on the performance parameters such as power consumption and phase noise. The optimal transistor sizing of each circuit is obtained from MDEA. Each circuit is implemented in SPICE by taking the optimal dimensions of the transistors, and the performance parameters are achieved. The designed voltage reference circuit achieves a reference voltage of 550 mV with 600 nW power dissipation. The reference voltage variation of 8.18% is observed due to temperature variation from −40°C to + 125°C. The MDEA-based optimal design of RO oscillates at 2.001 GHz frequency, has a phase noise of −87 dBc/Hz at 1 MHz offset frequency, and consumes 71 μW power. This work mainly aims to optimize the MOS transistors’ sizes using MDEA for better circuit performance parameters. SPICE simulation has been carried out by using the optimal values of MOS transistor sizes to exhibit the performance parameters of the circuit. Simulation results establish that design specifications are closely met. SPICE results show that MDEA is a better technique for the optimal design of the above-mentioned VLSI circuits.

Abstract An efficient compensation method is proposed for the reduction of mutual coupling among the elements of an antenna array using the optimum current amplitude excitation weights. The performance of an antenna array degrades heavily due to mutual coupling. The mutual coupling effect can neither be eliminated nor be ignored in the context of the antenna array design. Several analytical and numerical techniques have been proposed in the past few decades for the calculation and compensation of mutual coupling effect. Here, the mutual coupling is compensated by reducing the driving impedance of each identical array element in the array by adopting grey wolf optimization and moth flame optimization algorithms, respectively. The sum of the driving impedances of each element of the antenna array is reduced efficiently by adjusting the feed current amplitudes of all the individual array elements. Compared to the existing known methods, the proposed method is less complex, cost‐effective and easy to implement for commercial and industrial applications to achieve better performance.

This paper introduces the generalization of the classical Transitional Butterworth-Butterworth Filter (TBBF) to the Fractional-Order (FO) domain. Stable rational approximants of the FO-TBBF are optimally realized. Several design examples demonstrate the robustness and modeling efficacy of the proposed method. Practical circuit implementation using the current feedback operational amplifier employed as an active element is presented. Experimental results endorse good agreement ( $\text {R}^{2} = 0.999968$ ) with the theoretical magnitude-frequency characteristic.

In this article, the performance of n-type junctionless (JL) double-gate (DG) MOSFET-based biosensors with and without gate stack (GS) has been studied. Here, the dielectric modulation (DM) method is applied to detect biomolecules in the cavity. The sensitivity of n-type JL-DM-DG-MOSFET and n-type JL-DM-GSDG-MOSFET-based biosensors have also been evaluated. The sensitivity (ΔVth) improved in JL-DM-GSDG MOSFET/JL-DM-DG-MOSFET-based biosensors for neutral/charged biomolecules is 116.66%/66.66% and 1165.78%/978.94%, respectively, compared with the previously reported results. The electrical detection of biomolecules is validated using the ATLAS device simulator. The noise and analog/RF parameters are compared between both biosensors. A lower threshold voltage is observed in the GSDG-MOSFET-based biosensor. The Ion/Ioff ratio is higher for DG-MOSFET-based biosensors. The proposed GSDG-MOSFET-based biosensor demonstrates higher sensitivity than the DG-MOSFET-based biosensor. The GSDG-MOSFET-based biosensor is suitable for low-power, high-speed, and high sensitivity applications.

This article introduces a new design of an optimised zero-phase response fractional order digital differentiator (FODD) called Riesz FODD of half order by employing a recently developed Manta-Ray Foraging Optimisation (MRFO) for improved and precise electrocardiogram QRS detection. A new weighted cost function is developed that precisely considers the characteristics of an ideal Riesz fractional-order differentiator. Simulation tests of the rational approximations of the Riesz FODD based on the MRFO algorithm ensure close correspondence with the theoretical zero-phase and near-ideal magnitude responses and sensibly supersede the Least-squares method, Convex optimisation, Flower Pollination Algorithm, and Artificial Bee Colony based Riesz FODD designs. The Zero-phase response of the proposed Riesz FODD assists in preserving the features of the differentiated ECG precisely at the same time instant where they occur in the unfiltered signal. Additionally, the optimal magnitude characteristics of the proposed Riesz FODD help to obtain highly accurate differentiated ECG. These two indigenous properties of the proposed Riesz FODD accommodate the QRS detector to precisely identify the R-peak location and thus sensibly escalate the QRS detection accuracy when tested against several real electrocardiogram (ECG) signals of the PhysioNet ECG repository.

Optimal pulse shifting in timed antenna array for the reduction of sidelobe and sideband using improved harmony search algorithm (IHSA) dealt in this paper. The essence of `Time-modulation' lies in the fact that `Time' can be used as an additional control parameter in antenna array synthesis. The proposed approach demonstrates the controlling nature of periodic time sequences through pulse shifting. The undesired sideband radiations (SRs) generated in time modulated linear array (TMLA) is controlled by minimizing the sideband levels (SBLs) with an optimal pulse shifting scheme applied to the outer elements of the array. Evolutionary algorithm-based design is considered to optimize the time sequences and the excitation coefficients of the array along with the inter-element spacing between the array elements for sidelobe level (SLL) reduction at the fundamental frequency. Pulse shifting with optimized switch-ON instants and switch-ON time intervals of outer elements is responsible for the minimization of SBL only, as the fundamental pattern does not depend on pulse shifting. Thus, a combined approach is developed with optimized excitation coefficients and controlled pulse switching to reduce the SLL and SBL of TMLA simultaneously. 16 and 30 isotropic elements of TMLA structures are considered with a music-inspired IHSA to get the optimal solution. IHSA based numerical results are compared with the results obtained from other applied algorithms such as harmony search algorithm (HSA), particle swarm optimization (PSO), and real-coded genetic algorithm (RGA) with the proposed pulse shifting scheme. The obtained numerical results are also compared with previously published literature results to show the superior performance achieved by the proposed approach.

This paper presents the optimal rational approximation of (1+α) order Butterworth filter, where α ∊ (0,1) under the continued fraction expansion framework, by employing a new cost function. Two simple techniques based on the constrained optimization and the optimal pole-zero placements are proposed to model the magnitude-frequency response of the fractional-order lowpass Butterworth filter (FOLBF). The third-order FOLBF approximants achieve good agreement to the ideal characteristic for six decades of design bandwidth. Circuit realization using the current feedback operational amplifier is presented, and the modelling efficacy is validated in the OrCAD PSPICE platform.

This paper presents a global heuristic search optimization technique known as Gravitation Search Algorithm (GSA) for the design of 8th order Infinite Impulse Response (IIR), low pass (LP), high pass (HP), band pass (BP) and band stop (BS) filters considering various non-linear characteristics of the filter design problems. This paper also adopts a novel fitness function in order to improve the stop band attenuation to a great extent. In GSA, law of gravity and mass interactions among different particles are adopted for handling the non-linear IIR filter design optimization problem. In this optimization technique, searcher agents are the collection of masses and interactions among them are governed by the Newtonian gravity and the laws of motion. The performances of the GSA based IIR filter designs have proven to be superior as compared to those obtained by real coded genetic algorithm (RGA) and standard Particle Swarm Optimization (PSO). Extensive simulation results affirm that the proposed approach using GSA outperforms over its counterparts not only in terms of quality output, i.e., sharpness at cut-off, smaller pass band ripple, higher stop band attenuation, but also the fastest convergence speed with assured stability.

In this paper, the beam pattern of Linear Array Antennas with isotropic elements is examined. The design goal is to reduce the sidelobe level with a minimum beamwidth increase for the far field radiation pattern of the array by varying its electrical as well as its physical configuration. In this paper the cases of a uniformly excited and uniformly spaced array, uniformly excited and non-uniformly spaced array, and a non-uniformly excited and uniformly spaced array are examined for both symmetric as well as asymmetric array, and a comparison is done between them. Real Coded Genetic Algorithm (RGA) is used to find the optimal locations as well as the optimal excitations for the problem as per the cases considered.

This paper presents a novel approach of designing linear phase FIR low pass and high pass filter using Random PSO in hybrid with DE known as Random PSODE (RPSODE). In this paper, the Random PSO is used which utilises the weighted particle to guide the search direction for both explorative and exploitative searches. Differential evolution (DE) is one of the very fast and robust evolutionary algorithms which has shown superior performance for continuous global optimization; uses differential information to guide its search direction but sometime causes instability problem; whereas, PSO is a robust, population based stochastic search technique but has the problem of sub-optimality. This paper efficiently combines the Random PSO and DE so as to overcome the disadvantages faced by both the algorithms individually and is used for the design of linear phase low pass and high pass FIR filters. The simulation results show the superiority of RPSODE in global convergence properties and local search ability, and prove it to be a promising candidate for designing the FIR filters. RPSODE outperforms PSO, DE, and PSODE not only in magnitude response but in the convergence speed as well.

A novel optimization technique which is developed on mimicking the collective animal behaviour (CAB) is applied for the optimal design of hyper beamforming of linear antenna arrays. Hyper beamforming is based on sum and difference beam patterns of the array, each raised to the power of a hyperbeam exponent parameter. The optimized hyperbeam is achieved by optimization of current excitation weights and uniform interelement spacing. As compared to conventional hyper beamforming of linear antenna array, real coded genetic algorithm (RGA), particle swarm optimization (PSO), and differential evolution (DE) applied to the hyper beam of the same array can achieve reduction in sidelobe level (SLL) and same or less first null beam width (FNBW), keeping the same value of hyperbeam exponent. Again, further reductions of sidelobe level (SLL) and first null beam width (FNBW) have been achieved by the proposed collective animal behaviour (CAB) algorithm. CAB finds near global optimal solution unlike RGA, PSO, and DE in the present problem. The above comparative optimization is illustrated through 10-, 14-, and 20-element linear antenna arrays to establish the optimization efficacy of CAB.

In this paper a novel approach based on the Real coded Genetic Algorithm (RGA) is proposed to improve nulling performance as well as suppression of Side Lobe Level (SLL) of a Time Modulated Linear Antenna Arrays (TMLA). RGA adjusts the static excitation amplitudes as well as the location of each element from the origin to place deeper nulls in the desired direction. Three design examples are presented that illustrate the use of the RGA, and the optimization goal in each example is easily achieved.