A High-Performance Feedback FxLMS Active Noise Cancellation VLSI Circuit Design for In-Ear Headphones

Feedback Controller Optimization for Active Noise Control Headphones Considering Frequency Response Mismatch between Microphone and Human Ear

“…In order for a better NR performance, the FR of the controller C(z) should be enlarged as much as possible within the frequency band where active control of noise is expected to be effective, and should be attenuated as the frequency gets higher so that the noise enhancement could be limited according to the waterbed effect. Various optimization and control methods have been proposed with different kinds of controllers [2][3][4][5][6][7][8][9][10][11][12][13][14] and generally a good NR performance could be expected at the feedback microphone position. However, the actual NR performance would be perceived by the human ear, whose position is different from the one of the feedback microphone.…”

“…However, the computational burden would be greatly enhanced with the above methods where FIR controllers are used. Specially designed very large scale integration circuits [12] might be necessary in this case. This problem could be alleviated with the usages of a warped FIR filter [13] or cascade biquad filters [14], the latter of which is particularly advantageous for commercial products since the controller cost could be greatly lowered and the battery lifetime could also be lengthened.…”

A survey on active noise control in the past decade–Part II: Nonlinear systems

“…A number of (in-ear) headphones based on the feedback ANC system were implemented [224,225]. Their performance comparison of feedback ANC system with different circuit implementations can be seen in [226]. In [227], a hybrid feedback ANC scheme was presented by making use of the combination of classical and adaptive feedback ANC techniques.…”

Two-gradient direction FXLMS: An adaptive active noise control algorithm with output constraint

“…Computational burden is a critical issue that should be taken into account when referring to the practical implementation of an adaptive algorithm. For a real-time platform, such as the digital 14 signal processor (DSP) [47], the microcontroller unit (MCU) [48,49], the field programmable gate array (FPGA) [50] and so on, the burden is mainly brought on by multiplication/division, addition/subtraction in the execution of the algorithm. Compared to the conventional FXLMS algorithm, the 2GD-FXLMS algorithm has the same computational complexity (regarding the multiplication and addition), as illustrated in Table 1.…”