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An Alpha-guided gray wolf algorithm and its application in the design of two-stage operational amplifier

An operational amplifier, gray wolf technology, used in CAD circuit design, special data processing applications, instruments, etc.

Active Publication Date: 2019-03-01
XIANGTAN UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to improve the convergence speed and precision of the gray wolf algorithm, reduce the computing time of the computer, and solve the optimal design problem of the two-stage unbuffered CMOS operational amplifier

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  • An Alpha-guided gray wolf algorithm and its application in the design of two-stage operational amplifier
  • An Alpha-guided gray wolf algorithm and its application in the design of two-stage operational amplifier
  • An Alpha-guided gray wolf algorithm and its application in the design of two-stage operational amplifier

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Embodiment Construction

[0061] An Alpha-guided gray wolf algorithm and its application in the design of two-stage operational amplifiers, the topological structure diagram of the application object two-stage unbuffered CMOS operational amplifiers is as follows figure 1 Shown, a kind of Alpha guiding gray wolf algorithm is characterized in that comprising the following steps:

[0062] Step 1: Take the open-loop gain A of the two-stage operational amplifier v In order to optimize the target, with the constraints of unity gain bandwidth UGB, slew rate SR, total transistor area TA, positive power supply rejection PSRR+, negative power supply rejection PSRR-, static power consumption Pdiss, phase margin PM and structural conditions, the following mathematics is established Model:

[0063] consider X = [x 1 , x 2 ,...,x 10 ]=[S 1 ,...,S 8 , I 6 , C c ]

[0064] min f(X)=E Av / A v =E Av / (201g(2g m1 g m6 / (x 9 I 6 (λ 2 +λ 4 )(λ 6 +λ 7 )))

[0065] s.t g 1 (X)=E UGB / UGB=E UGa / (g m1...

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Abstract

The invention relates to an Alpha-guided gray wolf algorithm and other applications in two-stage operational amplifier design, belonging to the improvement and application field of swarm intelligencealgorithm. It is characterized in that: Alpha guidance mechanism is introduced into the grey wolf algorithm, which provides the direction of potential prey for the wolf pack leading group, and furtherimproves the convergence speed of the algorithm; as that standard GWO fall into the local optimum for a long time, the population concentrates in the area near Alpha, Beta and Delta and is difficultto jump out of the area. The invention introduce Alpha mutation mechanism into the grey wolf algorithm, and provides a channel for the population to jump out of the local optimum; In the invention, the algorithm parameter adopts the scalar design, and the algorithm structure is simplified. In the optimization design of two-stage unbuffered CMOS operational amplifiers, it has a good effect of optimization.

Description

technical field [0001] The invention belongs to the field of improvement and application of swarm intelligence optimization algorithms, and relates to a novel gray wolf population guidance mechanism, a novel gray wolf variation mechanism and a novel gray wolf algorithm structural parameter. Background technique [0002] With the continuous development of analog integrated circuits, the complexity of design is gradually increasing, and the demand is increasing. Manual calculation design will become more and more difficult, and the design cycle will be longer. Multi-objective and multi-constraints make analog integrated circuit design a The multi-objective optimization problem with constraints requires circuit designers to have sufficient design experience in order to take into account the various requirements of analog integrated circuit design. However, this cannot meet the current market demand for fierce competition. Analog integrated circuit parameter optimization design a...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/50G06N3/00
CPCG06N3/006G06F30/36Y02D30/70
Inventor 胡拚陈思溢黄辉先
Owner XIANGTAN UNIV
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