KEYWORDS: Particle swarm optimization, Signal generators, Error analysis, Analog to digital converters, Analog electronics, Signal processing, Particles, Digital electronics, Data communications, Computer hardware
Digital sine wave generators are widely used to provide high-precision analog sine wave signals in integrated devices for detection, communication, and control systems. In the working process of digital sine wave generator, various errors of circuit components, such as DAC, amplifier, and others are difficult to avoid, due to manufacturing defects and working environment, which will lead to corresponding distortions of the actual output signals and performance degradations of the systems. To overcome the error impacts of DAC and other circuit components on the output sine signals of digital sine wave generators, a novel error analysis method is proposed and compared with the traditional methods. A model is built to simulate the offset error, gain error, and nonlinear error of DAC, which will used to generate sine wave signals with different settable errors. The error curves of sine wave signals are extracted with average algorithm from the output signals with noise. A particle swarm optimization algorithm for a sine function is used to fit the error curves and compared with the traditional least squares fitting method for the polynomial error expression. The results demonstrate that the RMSE value of the proposed error fitting method is 23.4478, and the computational time of the algorithm is 0.37 seconds. These metrics are both lower than those of the polynomial error fitting method predicated on the traditional least squares approach. The findings validate the superior performance of the proposed method in the context of error fitting for digital sine signal generators.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.