G. Ramos and J. J. Lopez, “Direct Method with Random Optimization for Parametric IIR Audio Equalization - Applications to One Way and Multiway Systems,” in Proc. AES Convention 116, May 2004, Paper 6089. [Online]. Available: https://aes.org/publications/elibrary-page/?id=12703
Ramos G, Lopez JJ. Direct Method with Random Optimization for Parametric IIR Audio Equalization - Applications to One Way and Multiway Systems. In: AES Convention 116. Audio Engineering Society; 2004. Paper 6089. Available from: https://aes.org/publications/elibrary-page/?id=12703
@inproceedings{Ramos2004_12703,
author = {Ramos, German and Lopez, Jose Javier},
title = {{Direct Method with Random Optimization for Parametric IIR Audio Equalization - Applications to One Way and Multiway Systems}},
booktitle = {AES Convention 116},
note = {Paper 6089},
year = {2004},
month = may,
publisher = {Audio Engineering Society},
url = {https://aes.org/publications/elibrary-page/?id=12703}
}
TY - CPAPER
TI - Direct Method with Random Optimization for Parametric IIR Audio Equalization - Applications to One Way and Multiway Systems
AU - Ramos, German
AU - Lopez, Jose Javier
T2 - AES Convention 116
M1 - Paper 6089
PY - 2004
DA - 2004/05/06
UR - https://aes.org/publications/elibrary-page/?id=12703
PB - Audio Engineering Society
LA - en
AB - This paper presents a novel method for audio equalization using IIR (Infinite Impulse Response) filters. The algorithm is based on a direct method with a random parametric optimization process using second order sections (RaPOSOS). Given a loudspeaker response, and the definition of the desired electro-acoustical target response, an optimized filter is obtained. For full band loudspeakers, a bank of peak filters is designed to perform the equalization. For multiway systems, the process is repeated for each way with bandpass targets using lowpass, highpass and peak filters computing the combined response and performing time-align correction. The final result provides the parameters that define each filter (frequency, gain, Q) in correction order of importance; first the ones that perform deepest improvement, so scalable solutions with different degrees of correction could be derived.
ER -