Design of self-biased folded cascode CMOS op-amp using PSO algorithm for low-power applications

Motlak, Hassan Jassim; Mohammed, Mohammed Jasim

doi:10.1080/21681724.2018.1440422

Cited by 7 publications

(7 citation statements)

References 6 publications

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“…This model was developed by Kennedy and Eberhart in 1995 and called PSO. Currently, the PSO is used to solve optimization problems significantly and successfully because of a single goal algorithm [15]. The PSO algorithm is represented by a finite search space that contains a set of randomly distributed particles that have a certain velocity and position that are represented by simple mathematical models.…”

Section: Particle Swarm Optimization Algorithmmentioning

confidence: 99%

“…The values of c1 and c2 are important in improving performance depending on the type of problem. The best performance of the PSO algorithm is if the value of the constants c1=c2=2 is set as shown in Figure 3 [6], [15].…”

Section: Particle Swarm Optimization Algorithmmentioning

confidence: 99%

“…Operational Transparency According to their input and output, amplifiers are categorized into four groups [14]. The OTA with a single input and a single output, OTA with a differential input, and OTA with a balanced input and differential output [15], [16]. In addition, the current mode technique offers more potential, a wider dynamic range, a simpler circuit design, the lowest power consumption, and a wider signal bandwidth than the voltage mode approach, owing towards its enhanced linearity (bipolar and CMOS technologies) to establish the existing transport circuits [3], [4].…”

Section: Introductionmentioning

confidence: 99%

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Performance parameters optimization of CMOS analog signal processing circuits based on smart algorithms

Rasheed

Motlak

2023

Bulletin EEI

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Designing ideal analogue circuits has become difficult due to extremely large-scale integration. The complementary metal oxide semiconductor (CMOS) analog integrated circuits (IC) could use an evolutionary method to figure out the size of each device. The CMOS operational transconductance amplifier (CMOS OTA) and the CMOS current conveyor second generation (CMOS CCII) are designed using advanced nanometer transistor technology (180 nm). Both CMOS OTA and CMOS CCII have high performance, such as a wide frequency, voltage gain, slew rate, and phase margin, to include very wide applications in signal processing, such as active filters and oscillators. The optimization approach is an iterative procedure that uses an optimization algorithm to change design variables until the optimal solution is identified. In this study, different sorts of algorithms the genetic algorithm (GA), particle swarm optimization (PSO), and cuckoo search (CS) are employed to boost and enhance the performance parameters. While decreasing the time required to develop a conventional operation amplifier's settling time. Some studies decrease the value of the power utilized at various frequencies. Others operate at extremely high frequencies, but their power consumption is greater than that of those operating at lower frequencies.

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Section: Particle Swarm Optimization Algorithmmentioning

confidence: 99%

Section: Particle Swarm Optimization Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Performance parameters optimization of CMOS analog signal processing circuits based on smart algorithms

Rasheed

Motlak

2023

Bulletin EEI

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“…Several designs of CMOS op-amps can be found in Accepted Manuscript literature, all of which aim to optimize their performance parameters. Genetic algorithm, particle swarm optimization, simplex-PSO, modified cuckoo optimization algorithm, hybrid whale particle swarm optimization, aging leader and challenger PSO (ALC-PSO), and colliding bodies optimization (CBO) are just some of the methods utilized to optimize the dimensions of each transistor and enhance the performance of op-amps for design the analog and mixed-signal integrated circuit [4][5][6][7][8][9][10][11]. The improvements reported in more research papers demonstrate that certain performance parameters have been enhanced.…”

Section: Introductionmentioning

confidence: 99%

Design Optimization of CMOS Folded Cascode OTA Using Water Cycle Algorithm for Enhanced Performance

Rasheed,

Motlak

2024

JESA

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“…Thus, alternative methods that are robust and reliable, such as meta-heuristic optimization techniques, have gained popularity in solving complex circuit design problems [ 26 , 27 ]. Vural et al [ 28 ] and Motlak et al [ 29 ] have implemented particle swarm optimization (PSO) to minimize the area in a two-stage op-amp and power in a self-biased folded cascode. Moreover, there are other reported works, such as that by Kudikala et al [ 30 ], where the harmony search algorithm (HS) and differential evolution (DE) algorithm were applied for error minimization in a folded cascode structure.…”

Section: Introductionmentioning

confidence: 99%

Optimized Design of a Self-Biased Amplifier for Seizure Detection Supplied by Piezoelectric Nanogenerator: Metaheuristic Algorithms versus ANN-Assisted Goal Attainment Method

et al. 2022

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This work is dedicated to parameter optimization for a self-biased amplifier to be used in preamplifiers for the diagnosis of seizures in neuro-diseases such as epilepsy. For the sake of maximum compactness, which is obligatory for all implantable devices, power is to be supplied by a piezoelectric nanogenerator (PENG). Several meta-heuristic optimization algorithms and an ANN (artificial neural network)-assisted goal attainment method were applied to the circuit, aiming to provide us with the set of optimal design parameters which ensure the minimal overall area of the preamplifier. These parameters are the slew rate, load capacitor, gain–bandwidth product, maximal input voltage, minimal input voltage, input voltage, reference voltage, and dissipation power. The results are re-evaluated and compared in the Cadence 180 nm SCL environment. It has been observed that, among the metaheuristic algorithms, the whale optimization technique reached the best values at low computational cost, decreased complexity, and the highest convergence speed. However, all metaheuristic algorithms were outperformed by the ANN-assisted goal attainment method, which produced a roughly 50% smaller overall area of the preamplifier. All the techniques described here are applicable to the design and optimization of wearable or implantable circuits.

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Design of self-biased folded cascode CMOS op-amp using PSO algorithm for low-power applications

Cited by 7 publications

References 6 publications

Performance parameters optimization of CMOS analog signal processing circuits based on smart algorithms

Performance parameters optimization of CMOS analog signal processing circuits based on smart algorithms

Design Optimization of CMOS Folded Cascode OTA Using Water Cycle Algorithm for Enhanced Performance

Optimized Design of a Self-Biased Amplifier for Seizure Detection Supplied by Piezoelectric Nanogenerator: Metaheuristic Algorithms versus ANN-Assisted Goal Attainment Method

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