University of New Hampshire
Computer Science & Mathematics
Mentor: Dr. L.G. Kraft, Department of Electrical & Computer Engineering
Improving the Effectiveness of Active Noise Canceling Headsets
This project will investigate the performance limitations in Active Noise Canceling (ANC) headsets. The project will study two ANC approaches in headsets in order develop an enhanced performance.
The Bose Quiet Comfort acoustic headset was designed to actively reduce unwanted noise while permitting the desired sound to reach the ear. Bose applies the feedforward control system approach, which uses an external microphone to detect any external noise source .The microphone signal is amplified and used to produce a similar noise that is 180º out of phase to cancel out the undesired noise. In contrast to the Bose feedforward approach, this project will use a feedback control by utilizing an internal microphone to find the error between the desired sound source and the actual sound that approaches the ear.
I will focus on learning more about the differences as well as the limitations that exist between the feedforward and feedback control systems using simulations in MATLAB to investigate the important parameters that affect the performance of the headsets. The long-term goal of the project is to make the ANC headset more adaptive by using an artificial neural network called CMAC (Cerebellar Model Arithmetic Computer).