Journal Forum

Synthetic Reverberator - January 1960

Sound Board: High-Resolution Audio - October 2015

Synchronized Swept-Sine: Theory, Application, and Implementation - October 2015

Access Journal Forum

AES E-Library

Multi-Frequency Noise Removal Based on Reinforcement Learning

Document Thumbnail

In this paper, a neuro-fuzzy system is proposed to remove multifrequency noise from audio signals. There are two major elements in our method. The first comprises a fuzzy cerebellar model articulation controller (FCMAC) that is used to quantize the signals. The second one is developed based on the theory of stochastic real values (SRV) that is used to search the optimal frequencies for the overall trained system. We present a DSP implementation of the SRV algorithm and results on its performance in removing spectral noise that is buried in audio signals.

AES Convention: Paper Number:
Publication Date:

Click to purchase paper or login as an AES member. If your company or school subscribes to the E-Library then switch to the institutional version. If you are not an AES member and would like to subscribe to the E-Library then Join the AES!

This paper costs $20 for non-members, $5 for AES members and is free for E-Library subscribers.

Learn more about the AES E-Library

E-Library Location:

Start a discussion about this paper!

Facebook   Twitter   LinkedIn   Google+   YouTube   RSS News Feeds  
AES - Audio Engineering Society