A variable step-size filtered-x gradient adaptive lattice algorithm for active noise control

Kim, Seong-Woo; Park, Young-Cheol; Youn, Dae Hee

doi:10.1109/icassp.2012.6287849

Cited by 7 publications

(4 citation statements)

References 8 publications

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“…Such structure can attenuate multiple sinusoidal interferences in ANC systems and its corresponding algorithm, i.e., the gradient adaptive lattice (GAL) algorithm, can provide a reliable performance as compared with the known algorithm [213,214]. In the past decade, two VSS strategies have been suggested for the GAL algorithm, resulting in two VSS filtered-x GAL (VSS-FxGAL) algorithms [214,215]. These algorithms exhibit good attenuation performance for hybrid narrowband and broadband noise.…”

Section: Lattice Anc Algorithmsmentioning

confidence: 99%

A survey on active noise control in the past decade—Part I: Linear systems

et al. 2021

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Active noise control (ANC) is an effective way for reducing the noise level in electroacoustic or electromechanical systems. Since its first introduction in 1936, this approach has been greatly developed. This paper focuses on discussing the development of ANC techniques over the past decade. Linear ANC algorithms, including the celebrated filtered-x least-mean-square (FxLMS)based algorithms and distributed ANC algorithms, are investigated and evaluated. Nonlinear ANC (NLANC) techniques, such as functional link artificial neural network (FLANN)-based algorithms, are pursued in Part II. Furthermore, some novel methods and applications of ANC emerging in the past decade are summarized. Finally, future research challenges regarding the ANC technique are discussed.

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Section: Lattice Anc Algorithmsmentioning

confidence: 99%

A survey on active noise control in the past decade—Part I: Linear systems

et al. 2021

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“…A GALL filter is used because it wraps time in filter coefficients, i.e., requires less time to calculate and obtain filter coefficients. It also has a lower delay, reduced-order modeling, and requires a smaller number of coefficients and fewer computational operations [64]. It has a fast convergence response and can attain stability in less time.…”

Section: Gall Filtermentioning

confidence: 99%

On Self-Interference Cancellation and Non-Idealities Suppression in Full-Duplex Radio Transceivers

et al. 2021

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One of the major impediments in the design and operation of a full-duplex radio transceiver is the presence of self-interference (SI), that is, the transceiver’s transmitted signal, 60–100 dB stronger than the desired signal of interest. To reduce the SI signal below the receiver’s sensitivity before coupling it to the receiver, radio frequency (RF)/analog domain cancellation is carried out. Even after SI cancellation to the required level in the analog domain, the residual SI signal still exits and lowers the transceiver’s performance. For residual SI cancellation, a digital domain cancellation is carried out. RF impairments are the major obstacle in the residual SI cancellation path in the digital domain. Linearization of RF impairments such as IQ mixer imbalance in the transmitter and receiver chain, non-linear PA with memory, and non-linear LNA are also carried out. Performance evaluation of the proposed techniques is carried out based on SINR, the power of different SI signal components, PSD, output to input relationship, SNR vs. BER, spectrum analyzer, constellation diagram, and link budget analysis. The proposed techniques provide attractive RF/analog SI cancellation of up to 80–90 dB, digital residual SI cancellation of up to 35 to 40 dB, total SI cancellation of up to 110 to 130 dB, and an SINR improvement of up to 50 dB.

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“…In an effort to reduce the eigenvalue spread ratio and thus to improve the convergence speed, the filtered-x gradient adaptive lattice (FxGAL) algorithm [15,16] is applied to each two-weight adaptive filter of the simplified parallel form method. Consider a second-order lattice predictor that transforms the  th channel filtered reference signal into the orthogonal filtered backward prediction error.…”

Section: Parallel Form Fxgal Algorithmmentioning

confidence: 99%

“…Consider a second-order lattice predictor that transforms the  th channel filtered reference signal into the orthogonal filtered backward prediction error. This orthogonalization is carried out in the lattice through formulas [15,16] :…”

Section: Parallel Form Fxgal Algorithmmentioning

confidence: 99%

A New Parallel Method for Narrowband Active Noise Control

Kim¹,

Park²,

Seo³

et al. 2014

The Journal of the Acoustical Society of Korea

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ABSTRACT:In many practical active noise control applications, the primary noise contains multiple closely-spaced harmonics. A narrowband ANC system consists of adaptive filters excited by a composite reference signal, which is the set or sum of sinusoids. This paper analyzes and shows that the convergence speeds of the direct form, parallel form, and simplified parallel form narrowband ANC systems are affected by the fundamental frequency and frequency separation between two adjacent sinusoids in the reference signal. This paper also proposes the new simplified parallel form narrowband ANC system whose convergence speed is independent on the frequency of the reference signal. Computer simulations are conducted to verify the analysis presented in the paper and to compare the proposed narrowband ANC system with the conventional narrowband ANC system.

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A variable step-size filtered-x gradient adaptive lattice algorithm for active noise control

Cited by 7 publications

References 8 publications

A survey on active noise control in the past decade—Part I: Linear systems

A survey on active noise control in the past decade—Part I: Linear systems

On Self-Interference Cancellation and Non-Idealities Suppression in Full-Duplex Radio Transceivers

A New Parallel Method for Narrowband Active Noise Control

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