A study on using microcontroller to design active noise control systems

Shyu, Kuo-Kai; Ho, Chung-Ying; Chang, Cheng-Yuan

doi:10.1109/apccas.2014.7032814

Cited by 16 publications

(7 citation statements)

References 5 publications

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“…15 dB noise reduction and up to 600 Hz attenuation bandwidth compared to that of 15-20 dB at 350-400 Hz and 20 dB at 250-300 Hz in [6]; and that of around 10 dB at 200-350 Hz in [7]. In summary, the proposed work outperforms the works [6] and [7] in attenuating broadband noise with bandwidth of 100-600 Hz. Moreover, the characteristics of the proposed design, a PIC24H microcontroller, a floating-point DSP shown in Table I indicate that the proposed design only consumes a lowpower dissipation of 1.40 mW, i.e.…”

Section: Implementation Resultsmentioning

confidence: 74%

“…6 shows the measuring result of proposed design, i.e. 15 dB noise reduction and up to 600 Hz attenuation bandwidth compared to that of 15-20 dB at 350-400 Hz and 20 dB at 250-300 Hz in [6]; and that of around 10 dB at 200-350 Hz in [7]. In summary, the proposed work outperforms the works [6] and [7] in attenuating broadband noise with bandwidth of 100-600 Hz.…”

Section: Implementation Resultsmentioning

confidence: 88%

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A 1.4 mW low-power feed-back FxLMS ANC VLSI design for in-ear headphones

Chen

2016

2016 International Symposium on VLSI Design, Automation and Test (VLSI-DAT)

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This work proposes a dedicated VLSI hardware architecture design that considers both audio signal processing requirements and hardware costs to achieve critical real-time active noise cancellation (ANC) performance for in-ear headphones. This new approach allows ANC systems to be operated at lower operating frequency which results in lower power consumption, and facilitates higher performance than that achieved by conventional ANC headphones. Compared with the existing works, the proposed design outperforms in attenuating wider bandwidth of noises, and saves 99.41% power consumption.

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Section: Implementation Resultsmentioning

confidence: 74%

Section: Implementation Resultsmentioning

confidence: 88%

A 1.4 mW low-power feed-back FxLMS ANC VLSI design for in-ear headphones

Chen

2016

2016 International Symposium on VLSI Design, Automation and Test (VLSI-DAT)

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“…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.…”

Section: An Analysis On the Computational Complexity Of The Algorithmmentioning

confidence: 99%

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

Shi

Gan

Lam

et al. 2019

Mechanical Systems and Signal Processing

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“…Traditional ANC implementations usually involve Digital Signal Processing (DSP) due to their certain hardware computing units and capabilities to modify software, making ANC algorithms highly flexible without impeding computing speed, but DSP chips are costly and of high power consumption [3]. Therefore, some designs suggest using a universal Micro Control Unit (MCU) as a substitute for DSPs [4]. However, universal MCUs are not only subject to the serial instruction streams but also do not have a certain hardware computing units, making ANC applications difficult due to their computing inefficiency.…”

Section: Introductionmentioning

confidence: 99%

“…However, universal MCUs are not only subject to the serial instruction streams but also do not have a certain hardware computing units, making ANC applications difficult due to their computing inefficiency. Reference [4] proposes an implementation of the FxLMS algorithm using a STM32F407 microprocessor of Cortex-M4…”

Section: Introductionmentioning

confidence: 99%

Audio Denoising Coprocessor Based on RISC-V Custom Instruction Set Extension

et al. 2022

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As a typical active noise control algorithm, Filtered-x Least Mean Square (FxLMS) is widely used in the field of audio denoising. In this study, an audio denoising coprocessor based on Retrenched Injunction System Computer-V (RISC-V), a custom instruction set extension was designed and a software and hardware co-design was adopted; based on the traditional pure hardware implementation, the accelerator optimization design was carried out, and the accelerator was connected to the RISC-V core in the form of coprocessor. Meanwhile, the corresponding custom instructions were designed, the compiling environment was established, and the library function of coprocessor acceleration instructions was established by embedded inline assembly. Finally, the active noise control (ANC) system was built and tested based on Hbird E203-Core, and the test data were collected through an audio analyzer. The results showed that the audio denoising algorithm can be realized by combining a heterogeneous System on Chip (SoC) with a hardware accelerator, and the denoising effect was approximately 8 dB. The number of instructions consumed by testing custom instructions for specific operations was reduced by approximately 60%, and the operation acceleration effect was significant.

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A study on using microcontroller to design active noise control systems

Cited by 16 publications

References 5 publications

A 1.4 mW low-power feed-back FxLMS ANC VLSI design for in-ear headphones

A 1.4 mW low-power feed-back FxLMS ANC VLSI design for in-ear headphones

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

Audio Denoising Coprocessor Based on RISC-V Custom Instruction Set Extension

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