Abstract
An artificial neural network approach for the automated design of a positive type second generation current conveyor is presented in this paper. A multi-layer perceptron structure is successfully employed to estimate the corresponding transistor dimensions for a given set of desired performance criteria of the circuit. Data generated by a circuit simulation program (SPICE) is used to train the artificial neural network. The excellent agreement between the desired specifications and the actual results from SPICE simulation results approves that neural networks are powerful tools for automated analog circuit sizing.
Keywords
Spice
Artificial neural network
Perceptron
Computer science
Automation
Current conveyor
Sizing
Set (abstract data type)
Multilayer perceptron
Electronic engineering
Electronic design automation
Artificial intelligence
Control engineering
Engineering
Voltage
Electrical engineering
Embedded system
Capacitor
Subject Areas
Analog and Mixed-Signal Circuit Design
·Biomedical Engineering ·Physical Sciences
VLSI and Analog Circuit Testing
·Hardware and Architecture ·Physical Sciences
Advancements in Semiconductor Devices and Circuit Design
·Electrical and Electronic Engineering ·Physical Sciences
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