Sigma-Delta modulator self-adaptive mixing optimization method for improving signal to noise ratio

Abstract

The invention provides a Sigma-Delta modulator self-adaptive mixing optimization method for improving the signal to noise ratio. The method includes creating a noise transfer function of a Sigma-Delta modulator and performing dimensionality reduction on noise transfer function parameters, optimizing the noise transfer function parameters subjected to dimensionality reduction by a differential evolution method based on self-adaptive Cauchy distribution and chaotic mapping, calculating to acquire optimal values of the noise transfer function parameters according to to-be-optimized optimal parameter values, determining the optimal noise transfer function to complete self-adaptive mixing optimization of the Sigma-Delta modulator, taking a sinusoidal signal output by an interpolation filter of a Sigma-Delta digital-to-analog converter as the input of the Sigma-Delta modulator with the optimized noise transfer function, transforming an output value of the Sigma-Delta modulator to a frequency domain, and calculating the signal to noise ratio of the Sigma-Delta modulator. According to the method, ergodicity of chaotic mapping and high disturbance of self-adaptive Cauchy distribution are fully utilized, a target function is created and is optimized by the mixing differential evolution method, and the signal to noise ratio is remarkably increased while the stability of the modulator is kept.

Description

technical field [0001] The invention belongs to the technical field of electronic information, and in particular relates to a Sigma-Delta modulator self-adaptive mixing optimization method for improving the signal-to-noise ratio. Background technique [0002] The development of current communication technology has created a huge demand for digital-to-analog converters with high bandwidth and high resolution. Nyquist-based counting converters and integral converters can achieve relatively high precision, but it takes up to 2 N cycle, the processing speed is too slow to be easily implemented. Other types of Nyquist converters require high precision analog components. The Sigma-Delta digital-to-analog converter achieves a better balance between precision and speed, and has become the mainstream technology of digital-to-analog converters. Sigma-Delta digital-to-analog converter applies oversampling and noise shaping technology to shape low-frequency quantization noise to high...

AI Technical Summary

Problems solved by technology

[0011] The above methods have disadvantages such as easy to fall into local extremum, low precision, and low success rate.

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