Noise Cancellation Research Papers - Academia.edu (original) (raw)

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- by
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- Image Analysis, Probability, Parameter estimation, Signal Analysis
- by Panos Karaivazoglou
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- Signal Processing, Iterative Methods, Convergence, Algorithm
- by Kambiz Zangi
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- Stochastic Process, Computer Science, Parameter estimation, Stochastic processes
- by Ralf Schlüter
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- Neural Network, Databases, Low Frequency, Recurrent Neural Network
- by Akash Bhoi and +1
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- Biomedical Engineering, Image Processing, Noise Cancellation, Gaussian noise
- by Georgi Iliev
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- Computational Complexity, Adaptation, Speech Recognition, Adaptive Signal Processing

Sound-n.1. Physics. mechanical vibrations that travel in waves through the air, water, etc. 2. the sensation produced by such vibrations in the organs of hearing. 3. anything that can be heard. 4. impression or implication. 5. music~vb.... more

- by Dave Edwards
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- Music, Music Theory, Music Psychology, Audiology
- by D. Pulsipher
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- Speech enhancement, Noise reduction, Noise Cancellation, Adaptive Filter

This paper considers an implementation of Least
Mean Square (LMS) adaptive filter for noise cancellation. In this
paper, the adaptive filter is used to create a “Zone of Silence”.
The paper considers the use of LMS adaptive filter to cancel
engine noise in a target area by generating a signal that will
interfere destructively with the noise signal, hence cancels the
noise introduced in the target area. The proposed model is
simulated using LabView software. The resuts show that the
proposed model can cancel out noise average power up to 7900
times.

This paper reviews the past and the recent research on Adaptive Filter algorithms based on adaptive noise cancellation systems. In many applications of noise cancellation, the change in signal characteristics could be quite fast which requires the utilization of adaptive algorithms that converge rapidly. Algorithms such as LMS and RLS proves to be vital in the noise cancellation are reviewed including principle and recent modifications to increase the convergence rate and reduce the computational complexity for future implementation. The purpose of this paper is not only to discuss various noise cancellation LMS algorithms but also to provide the reader with an overview of the research conducted.

- by Muhammad AB
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- Process Control, Circuits and Systems, Convergence, Computer Simulation

In this paper, a new efficient adaptive filtering algorithm belonging to the Quasi-Newton (QN) family is proposed. In the new algorithm, the autocorrelation matrix is assumed to be Toeplitz. Due to this assumption, the algorithm can be implemented in the frequency domain using the fast Fourier transform (FFT). The proposed algorithm turns out to be particularly suitable for adaptive channel equalization in wireless burst transmission systems. The algorithm exhibits a faster convergence rate and less computational ...

- by Mohammad Salman X-E-A
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- Mathematics, Computer Science, Signal Processing, Convergence
- by Paolo Peretti and +1
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- Applied Mathematics, Adaptive Control, Active noise control, Air Conditioning
- by Sathis Kumar
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- Signal Processing, Speech Recognition, Multidisciplinary, Beamforming

The recursive least squares (RLS) algorithm was introduced as an alternative to least mean square (LMS) algorithm with enhanced performance. Computational complexity and instability in updating the autocolleltion matrix are some of the drawbacks of the RLS algorithm that were among the reasons for the introduction of the second-order recursive inverse (RI) adaptive algorithm. The 2 nd order RI adaptive algorithm suffered from low convergence rate in certain scenarios that required a relatively small initial step-size. In this paper, we propose a new second-order RI algorithm that projects the input signal to a new domain namely discrete wavelet transform (DWT) as pre step before performing the agorthim. This transformation overcomes the low convergence rate of the second-order RI algorithm by reducing the self-correlation of the input signal in the mentioned scenatios. Expeirments are conducted using the noise cancellation setting. The performance of the proposed algorithm is compared to those of the RI, original second-order RI and RLS algorithms in different Gaussian and impulsive noise environments. Simulations demonstrate the superiority of the proposed algorithm in terms of convergence rate compared to those algorithms. 1. INTRODUCTION Adaptive filtering techniques can promote accurate solutions and high convergence rates in many signal processing problems [1-3]. Some of these well-known problems; such as, noise cancellation [4, 5], channel equalization [6], and system identification [7, 8], have been addressed by many researchers for many decades. The straightforward steps of the least mean square (LMS) adaptive algorithm in weights update together with its fast convergence (if optimum step-size is selected), made it a very popular filtering algorithm. However, its convergence rate is easily affected by the spread of the eigenvalue of the autocorrelation matrix of the tap-input vector [9-13]. The recursive least square (RLS) algorithm [9] was introduced as an alternative to LMS algorithm with a superior performance. Particularly, in highly correlated environments with the possibility of high eigenvalue spread of the autocorrelation matrix. However, the RLS algorithm has its own drawbacks such as; high computational complexity, and updating the inverse autocorrelation matrix that may raise numerical stability problems [14]. To overcome such problems of the RLS algorithm, many other algorithms have been proposed.

- by Alaa Eleyan
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- Wavelet Transform, Noise Cancellation, Recursive Inverse Algorithm, Impulsive noise
- by Ghafar Darvish
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- Distortion, Impedance Matching, PMOs, Noise Cancellation

This paper reviews the past and the recent research based on adaptive noise cancellation system using Adaptive filter algorithms. Adaptive noise cancellation is a wide area of research in the field of communication and is used for noise reduction in speech signals. In many applications, the change in the received signals could be very fast which requires the use of adaptive algorithms that converge rapidly. This paper deals with cancellation of noise in speech signal using Least Mean Square (LMS) adaptive algorithms that provides efficient performance with less computational complexity.

- by Deepanjali jain
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- LMS, Noise reduction, Noise Cancellation, Matlab/Simulink
- by ming wu
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- Engineering, Signal Processing, Audio Signal Processing, Quality Control

—Due to the radical environmental changes, in terms of sound pollution and global warming that the world is subject to, today's climate (noise, temperature, and humidity) impacts new-borns and babies environments. In order to achieve better living conditions in a baby room, monitoring and control systems became very important. Existing systems only monitor and control the temperature, humidity, and light in baby rooms. This paper intends to build on the existing related work and suggests an enhanced noise cancelling system for a comprehensive monitoring and control to overcome the sound pollution and make the baby rooms more comfortable. The proposed system design and implementation are discussed and the corresponding components are detailed with their interactions. Additionally, a draft cost estimation is presented.

- by Mohammed El Kihal
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- Safety Engineering, Mechatronics, Mechatronics & Robotics, Control Systems
- by Doris Schmitt-Landsiedel
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- Switching, Sampling methods, Noise reduction, Radio Frequency

Dada os prejuízos sociais causados pela perda auditiva infantil se torna necessário viabilizar um aumento de acesso aos diagnósticos por meio da audiometria. O projeto visa aprimorar a tecnologia da triagem audiométrica em tablets com o desenvolvimento de um sistema de supressão de interferências acústicas acoplado ao fone de ouvido circumaural usado de forma a deixar a tecnologia mais portátil e acessível financeiramente. O sistema é um ANR (Redutor Ativo de Ruído), duas soluções de processamento de sinais foram analisadas: Filtragem Adaptativa (LMS) e Subtração Espectral. Após a validação dos modelos por meio de simulações no MATLAB, o sistema foi embarcado na placa de desenvolvimento BeagleBone Black(BBB) com sensores analógicos de som DF0034 e uma placa de USB Sound Card de hardware e com software desenvolvido em linguagem Python e C. As formas de onda e a alteração de potência dos sinais aproximados gerados pelos dois algoritmos foram os métodos de avaliação objetiva dos resultados.

- by Marc Botha
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- Critical Theory, Cultural Studies, Aesthetics, Spirituality
- by Sharon Gannot
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- Acoustics, Room Acoustics, Multidisciplinary, Sensor Arrays
- by Yahong Zheng
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- Noise Cancellation, System Development, Acoustic Noise, Teleconferencing
- by Dwi Handoko
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- Noise reduction, Noise Cancellation, Cmos Image Sensor, High Sensitivity
- by Muhammad AB
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- Engineering, Computational Complexity, Modeling, Convergence

This paper describes the development of an adaptive noise cancellation algorithm for effective recognition of speech signal and also to improve SNR for an adaptive step size input. An adaptive filter with Fast Block Least Mean square Algorithm is designed for noise free audio (speech/music) signals. The signal input used is a audio speech signal which could be in the form of a recorded voice. The filter used is adaptive filter and the algorithm used is Fast Block LMS algorithm. A Gaussian noise is added to this input signal and given as a input to the Fast Block LMS. The algorithm is implemented in Matlab and was tested for noise cancellation in speech signals. A Simulink model is designed which results in a noise free audio speech signal at the output. The FBLMS algorithm is computationally efficient in noise cancellation. The noise level in speech signal can be 1) mild, 2) moderate, 3) severe. The SNR is estimated by varying the adaptive step size.

Digital noise reduction technique, to enhance the quality of speech is a vast area of research now-a-days. This investigation focuses on the noise reduction methods employing the technique of adaptive filtering, using a popular LMS algorithm. The simplicity and relative effectiveness of this noise reduction algorithm has resulted in explosive growth in its use for a variety of speech communications applications. In this paper a comparative study by varying the parameters of LMS algorithm is done. Implementation and analysis of the filters are done by taking different step sizes on same orders of the filters.

- by Mark Allie
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- System Identification, Signal Processing, Electronics, Process Control
- by Hamid Reza Abutalebi and +1
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- Evaluation, Digital Signal Processing, Speech Processing, Optimization
- by Tuan Ngo
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- Performance, Speed, Noise Cancellation, Accuracy
- by Peter Driessen
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- Speech Production, Nonlinear filters, Speech Processing, Kalman Filter

The paper deals with turbo detection techniques for Single User Multiple-Input-Multiple-Output (SU MIMO) antenna schemes. The context is on the uplink of the upcoming Long Term Evolution - Advanced (LTE-A) systems. Iterative approaches based on Parallel Interference Cancellation (PIC) and Successive Interference Cancellation (SIC) are investigated, and a low-complexity solution allowing to combine interstream interference cancellation and noise enhancement reduction is proposed. Performance is evaluated for Orthogonal Frequency Division Multiplexing (OFDM) and Single Carrier Frequency Division Multiplexing (SC-FDM) as candidate uplink modulation schemes for LTE-A. Simulation results show that, in a 2times2 antenna configuration, the turbo processing allows a consistent improvement of the link performance, being SC-FDM the one having higher relative gain with respect to linear detection. The turbo receiver's impact is however much reduced for both modulation schemes in a 2times4 configuration, due to the higher diversity gain provided by the additional receive antennas.

Digital model matching techniques are applied to design digital feedforward controllers for active noise cancellation in ducts. First, active noise control system in ducts that consist of primary and secondary paths is identified using the recursive least square algorithm. The mathematics of interpolation theory called the Nevanlinna-Pick problem (NP theory) is used to solve the model-matching problem. Therefore, by applying the model-matching concept a stable controller is designed that performs well in canceling the noise. Utilizing a certain weighting function in the design process gives a better performance.

- by Hasan Yousef
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- Mathematics, Controller Design, Digital Control, Control Systems

- by Mohammed El Kihal
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- Safety Engineering, Mechatronics, Mechatronics & Robotics, Control Systems
- by Hideaki Sakai
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- Convergence, Multidisciplinary, Frequency, Noise Cancellation
- by Ahmed Abutaleb
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- Signal Processing, Convergence, Nonlinear filters, Simulation
- by daniel graupe
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- Signal Processing, Adaptive Control, Algorithm, Adaptive Systems

In this paper, we consider the use of affine projection algorithm (APA) for interference suppression in direct sequence code-division multiple-access (DS-CDMA) system. We first derive the multiuser fixed step-size APA (FSS-APA) algorithm. The computational complexity offered by the APA algorithm is linear in terms of the number of taps with additional terms of O (L 2) and a matrix inversion of dimension L, where L is known as the order of the filter. The value of L is chosen very small as compared to the number of filter-taps N T . We next propose a novel variable step-size APA (VSS-APA) algorithm, which further improves the performance of the FSS-APA algorithm with very small increase in computational complexity as compared to the FSS-APA. It is demonstrated that the performance of the APA based minimum mean-square error (MMSE) receivers is far superior to that of the normalized least-mean-square (NLMS) based receivers. Though, the recursive-least-square (RLS) algorithm based adaptive receivers offer better performance but at the cost of much higher computational complexity.

- by Aditya Trivedi
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- Engineering, Mechanical Engineering, Distributed Computing, Information Technology
- by Babak Hassibi
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- Adaptive Control, Performance, Convergence, Multidisciplinary

Adaptive filters have become active area of research in the field of communication system. This paper explores the novel concept of adaptive noise cancellation (ANC) using least-mean-square (LMS) adaptive filters. The model of the LMS-ANC is designed and simulated in MATLAB environment. The proposed algorithm utilizes adaptive filters to evaluate gradients accurately which results in good adaptation, stability and performance. The objective of this investigation is to provide solution in order to improve the performance of noise canceller in terms of filter parameters. The results are obtained with the help of adaptive algorithm with variable step size and filter order in order to deliver high convergence speed and stability of the error signal.

- by Deepanjali jain
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- Adaptive Control, Matlab, Adaptive Filtering, LMS

This paper compares wavelet and short time Fourier transform based techniques for single channel speech signal noise reduction. Despite success of wavelet denoising of images, it has not yet been widely used for removal of noise in speech signals. We explored how to extend this technique to speech denoising, and discovered some problems in this endeavor. Experimental comparison with large amount test data has been performed. Our results have shown that although the Fourier domain methods still has the superiority, wavelet based alternatives can be very close, and enormous different configurations can still be tried out for possible better solutions.

- by Ningping Fan
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- Engineering, Mathematics, Wavelet, Speech enhancement
- by Gaurav Saxena
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- Civil Engineering, Information Technology, Statistics, Digital Signal Processing
- by Georgi Iliev
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- Computational Complexity, OFDM, Adaptive Systems, Bit Error Rate

Summer Internship Project report while working under the supervision of Prof. Jayanta Mukhopadhyay, Computer Science Engineering Department, IIT Kharagpur and Prof. Manjunatha Mahadevappa, School of Medical Science and Technology, IIT... more

- by Ritambhar Burman
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- EMG, Electromyography, Noise Cancellation, EMG signal processing

... aircraft noise, the algorithms were evalu-ated in a simulated environment to cancel the noise generated by a helicopter, a propeller airplane, and a jet airplane. Assuming that the canceling speaker and the microphone were three... more

- by Kambiz Zangi
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- Engineering, Stochastic Process, Parameter estimation, Stochastic processes