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![Figure 1. MMIC low noise amplifier circuit [10]](profile/Wei-Jer-Lim/publication/241627714/figure/fig1/AS:393307789250563@1470783292288/MMIC-low-noise-amplifier-circuit-10_Q320.jpg)
This paper presents a Genetic Algorithm (GA) based optimization approach for assisting circuit design. The GA is developed to optimize the parameter setting for circuit design in order to achieve the required specifications in terms of noise figure, power gain, power loss, current, and circuit stability factors. Two case studies are presented in th...
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Context 1
... schematic diagram of MMIC amplifier circuit is depicted in Figure 1. A two-stage RC feedback amplifier is used with M1 and M2 refer to the transistors with unit gate width of 50μm. ...
Similar publications
In this paper, focuses on the design of Low Noise Amplifier circuitry in the frequency band L. This circuit is designed using the 0.18 nm CMOS transistor technology, which consists of two transistor Stage. The purpose of this research is to improve the cost of: Increase Gain - Increase circuit linearization - Create an integrative matching network...
Citations
... Analog circuit design optimization refers to the improvement of the performance of an analog circuit by adjusting its parameters or components to meet specific performance goals, such as increased accuracy, stability, power efficiency, or reduced noise [2]. This process involves using mathematical models, simulation tools, and optimization algorithms to identify the best combination of circuit components and parameters to achieve the desired performance characteristics. ...
... This process involves using mathematical models, simulation tools, and optimization algorithms to identify the best combination of circuit components and parameters to achieve the desired performance characteristics. Optimization may be iterative, with multiple design iterations being evaluated until the desired performance criteria are met [2]. ...
... Simulation-based design can be very effective at identifying design flaws and optimizing circuit performance, but it can be time-consuming and computationally expensive. (iv) Optimization algorithms: optimization algorithms such as genetic algorithms can optimize circuit designs by generating a population of candidate solutions and evaluating their performance using simulations [2]. ...
Circuit design plays a pivotal role in engineering, ensuring the creation of efficient, reliable, and cost-effective electronic devices. The complexity of modern circuit design problems has led to the exploration of multi-objective optimization techniques for circuit design optimization, as traditional optimization tools fall short in handling such problems. While metaheuristic algorithms, especially genetic algorithms, have demonstrated promise, their susceptibility to premature convergence poses challenges. This paper proposes a pioneering approach, the chaotic multi-objective Runge–Kutta algorithm (CMRUN), for circuit design optimization, building upon the Runge–Kutta optimization algorithm. By infusing chaos into the core RUN structure, a refined balance between exploration and exploitation is obtained, critical for addressing complex optimization landscapes, enabling the algorithm to navigate nonlinear and nonconvex optimization challenges effectively. This approach is extended to accommodate multiple objectives, ultimately generating Pareto Fronts for the multiple circuit design goals. The performance of CMRUN is rigorously evaluated against 11 multiobjective algorithms, encompassing 15 benchmark test functions and practical circuit design scenarios. The findings of this study underscore the efficiency and real-world applicability of CMRUN, offering valuable insights for tailoring optimization algorithms to the real-world circuit design challenges.
Gravitational search algorithm (GSA) is a recent introduced algorithm which is inspired by
law of gravity and mass interactions. In this paper, a novel version of GSA, named Clustered-
GSA, is proposed to reduce complexity and computation of the standard GSA. This
algorithm is originated from calculating central mass of a system in nature and improves
the ability of GSA by reducing the number of objective function evaluations. Clustered-
GSA is evaluated on two sets of standard benchmark functions and the results are compared
with several heuristic algorithms and a deterministic optimization algorithm.
Experimental results show that by using Clustered-GSA, better results are achieved with
lower complexity. Moreover, the proposed algorithm is used to optimize the parameters
of a Low Noise Amplifier (LNA) in order to achieve the required specifications. LNA is the
first stage in a receiver after the antenna. The main performance characteristics of receivers
are dictated by the LNA performance. It is necessary to study, design, and optimize all the
elements included in the structure, simultaneously. The comparative results show the efficiency
of the proposed algorithm.
In order to optimize and simulate the design variables for a Fourth-order Sallen-Key low-pass filter, a genetic algorithm (GA) based optimization approach is proposed in this paper. The Fourth-order Sallen-Key low-pass filter design is synthesized using LTSpice whereas the GA model is developed by Matlab. The aims of the design include gain maximization, pass-band ripple minimization, and cut-off satisfaction. From the results obtained, the desired filter design that satisfies the specification constraints and required goals is produced.
Manual design of integrated circuits has lately become obsolete, given the fact that time constraints are more and more present. Hence, designers have shifted towards automatic approaches, using various software tools, which not only ensure a speedy result, but also provide a fertile environment for further designs. Many automated design processes that address integrated circuits include one or more computational intelligence techniques, such as genetic algorithms, multi-objective optimization, neural networks or fuzzy logic. The paper presents a survey on how these techniques are used in low noise amplifiers (LNA) design. The LNA is a crucial block in the structure of a communications receiver and must meet some strict specifications. A literature review of the up-to-date papers available on the subject classifies them, based on the design technique used, and comments the main categories. The paper also identifies some issues that have not been approached so far and indicates possible future directions.
