Affiliation:
1. Liberal Arts College of Hunan Normal University, P. R. China
2. School of Engineering and Design, Hunan Normal University, P. R. China
Abstract
Frequency weighting networks are a critical component of a sound level meter (SLM), and their error characteristics directly determine the performances of SLM. For reducing the high-frequency error of the [Formula: see text] frequency-weighting filters with the bilinear transformation method (BTM), a design method for [Formula: see text] frequency-weighting filters based on neural computing method (NCM) is proposed. A detailed algorithm for solving the filter coefficients is provided, and the amplitude-frequency characteristics of the [Formula: see text] frequency-weighting filters with BTM and NCM are compared in detail. The experimental results show that the amplitude-frequency characteristics of the [Formula: see text] frequency-weighting filters in SLM with NCM are significantly better than those of BTM. The filter meets the requirements of the first class SLM defined by IEC61672, which demonstrates the effectiveness of this proposed method.
Funder
National Natural Science Foundation of China
Publisher
World Scientific Pub Co Pte Ltd
Subject
General Physics and Astronomy,General Mathematics