Low Power VLSI Implementation of Adaptive Noise Canceller Based on Least Mean Square Algorithm

Vakulabharanam, Ramakrishna; Kumar, Tipparti Anil

doi:10.1109/isms.2013.84

Cited by 8 publications

(5 citation statements)

References 13 publications

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“…The least-mean-squares (LMS) algorithm is the most-popular adaptive algorithm because of its simplicity and robustness [5]; the objective of the algorithm is to generate an adaptive filter, whose coefficients are continuously modified in a way that the unwanted noise is removed from the audio signal [2]. An ordinary least-squares regression powered with a stochastic gradient descent method [6] estimates the error at the current time, and the new filter values are calculated in each iteration, given by…”

Section: Noise-cancellation Algorithmsmentioning

confidence: 99%

Application-Specific Integrated Circuit of an Inter-IC Sound Digital Filter for Audio Systems

et al. 2023

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In digital audio systems, filters and equalizers are essential modules for audio improvement at the input and output stages. Due to their computational complexity, most audio tasks are processed with digital signal processors. Due to the fact that latency in audio systems is a critical specification and audio trends require higher sample rates, noise canceling, and bigger data sizes, having an independent high-resolution equalizer would reduce the computational power needed for audio systems. This research had the goal of designing and implementing a hardware architecture for a configurable filter bank based on finite impulse response (FIR) filters and a noise-cancellation stage with an inter-integrated circuit (I2C) communication interface, which allows the filter configuration. The system was implemented as a standalone integrated circuit (IC) for which its inputs were the inter-IC sound (I2S) bus control signals. The digital audio system was optimized to perform one-cycle convolutional operations by implementing a vector–vector arithmetic logic unit. Furthermore, this applied research provides the register transfer level description and the functional verification of the digital design, the system-on-chip (SoC) implementation in TSMC 180 nm technology, and the post-silicon validation with a printed circuit board for testing the output digital signals of the system.

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Section: Noise-cancellation Algorithmsmentioning

confidence: 99%

Application-Specific Integrated Circuit of an Inter-IC Sound Digital Filter for Audio Systems

et al. 2023

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“…So, when the filter is optimized, the output will be a clean speech information signal as shown in figure 2. Amongst others LMS algorithm can converge quickly and has good noise suppression ability [1][2]. In this research, different parameters are analyzed by considering order of the filter, its convergence speed & optimal hardware utilization.…”

Section: Proposed Approach: Adaptive Noise Cancellationmentioning

confidence: 99%

“…In year 1960, work related to ANC was carried out by Howells and Applebaum and their colleagues at the GE Company. A system was designed to cancel antenna side lobe by using reference input obtained from auxiliary antenna [2]. ANC technique was developed at Stanford University in 1959 by Widrow and Hoff.…”

Section: Proposed Approach: Adaptive Noise Cancellationmentioning

confidence: 99%

“…It consist of two main blocks, one is digital filter & second is adaptive evaluation. Corrupted information is effectively process by digital filter whereas algorithm is used for adaptation purpose by altering the coefficient & tries to optimize the desired weights [2][3]. The LMS algorithm [1] is undoubtedly the most popular algorithm for adapting the impulse response W = [W 0 …….W N-1 ] of an FIR filter so as to minimize the mean-square error (MSE) between its output signal y(n) and a desired response signal d(n).…”

Section: Introductionmentioning

confidence: 99%

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Performance Analysis of Adaptive Noise Canceller in Digital Filter for Human Voice Separation

Godbole¹

2018

Helix

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This Paper involves the performance analysis of Adaptive Noise Cancellation system (ANC) and its noise cancellation application by taking more realistic noises. Noise cancellation is a common occurrence in today's telecommunication environment. The main purpose of this research is to eliminate unwarranted noise that exists in incoming signal, which makes it difficult to understand. Adaptive Noise Cancellation is an alternative technique of estimating signals corrupted by additive noise or interference. This paper examines adaptive filtering, employing discrete signal processing in MATLAB. Simulation was utilized by using MATLAB software to eliminate the noise. The strategies & design methodologies of Adaptive Noise Canceller using the least mean square (LMS) algorithm is considered in this paper. Using the LMS algorithm, adaptive noise canceller has been implemented on MATLAB successfully by considering more realistic noises for suitable filter order and convergence factor. The results are analyzed for different input noises originating from refrigerators, vaccum cleaners, hair dryers, washing machines as reference signals and speech signal corrupted by these noises as primary signal. These signals are tested and analyzed and the filter performance of these noises is measured in terms of signal to noise ratio (SNR) improvement. From the experimentation it is clear that signal to noise ratio of primary signal earlier it was 3.468db which gets substantially improved by 49.921dB. It has also been observed that for filter order N =50 and for convergence factor µ = 0.03, the voice signal can still be recovered perfectly.

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“…Therefore, the adaptive noise canceller is designed adopting an improved LMS algorithm [1]. The ANC Based on Least Mean Square Algorithm has been extensively used in many researches [1][2][3][4][5][6]. The purpose of ANC is to remove the noise from a signal adaptively to improve the SNR.…”

Section: Introductionmentioning

confidence: 99%

A Modified Adaptive Line Enhancer for Noisy Speech Signals

2015

3rd International Conference on Advances in Engineering Sciences and Applied Mathematics (ICAESAM’2015), March 23-24, 2015 Lond

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Adaptive filter is a method for enhancing noisy speech signals. In this work, a refinement for the adaptive line enhancer proposed by Widrow and Sambur is introduced. The new algorithm is based on both the exact value of gradient and variable step-size. These values are computed and used for coefficient updating. The algorithm is applied on different cases of noisy speech signals as well as GSM signals. The new algorithm gave good results even when noise is greater than signal which is considered a novel achievement in the field. It avoids the drawbacks of LMS algorithm introduced by widrow and others. The adaptive line enhancer (ALE) design method updates the FIR filter coefficients in terms of the exact value of gradient and a variable step size.

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Low Power VLSI Implementation of Adaptive Noise Canceller Based on Least Mean Square Algorithm

Cited by 8 publications

References 13 publications

Application-Specific Integrated Circuit of an Inter-IC Sound Digital Filter for Audio Systems

Application-Specific Integrated Circuit of an Inter-IC Sound Digital Filter for Audio Systems

Performance Analysis of Adaptive Noise Canceller in Digital Filter for Human Voice Separation

A Modified Adaptive Line Enhancer for Noisy Speech Signals

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