28 results on '"George, Nithin V."'
Search Results
2. Swarm and evolutionary computing algorithms for system identification and filter design: A comprehensive review
- Author
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Gotmare, Akhilesh, Bhattacharjee, Sankha Subhra, Patidar, Rohan, and George, Nithin V.
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- 2017
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3. Compensating acoustic feedback in feed-forward active noise control systems using spline adaptive filters
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Patel, Vinal and George, Nithin V.
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- 2016
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4. Nonlinear Spline Adaptive Filters based on a Low Rank Approximation
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Bhattacharjee, Sankha Subhra, Patel, Vinal, and George, Nithin V
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- 2022
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5. Fast and efficient acoustic feedback cancellation based on low rank approximation
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Bhattacharjee, Sankha Subhra and George, Nithin V.
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- 2021
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6. Two microphone acoustic feedback cancellation in digital hearing aids: A step size controlled frequency domain approach.
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Pradhan, Somanath, George, Nithin V., Albu, Felix, and Nordholm, Sven
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MICROPHONES , *HEARING aids , *ACOUSTICS , *DIGITAL technology , *MATHEMATICAL domains - Abstract
The feedback cancellation performance of behind the ear hearing aids can be improved by employing two microphones in the feedback cancellation process. A frequency domain implementation of feedback cancellation in a two microphone behind the ear hearing aid has been proposed in this paper. A frequency domain step size control scheme has been further introduced to improve the convergence behaviour. The implementation of a the frequency domain step size control method requires the microphone input signal as well as the loudspeaker output signal to be uncorrelated. In order to reduce the correlation effects and enable such an implementation, we have incorporated frequency shifting in the forward path. The proposed approach has been shown to provide improved convergence behaviour as well as offer enhanced speech quality. Further, the proposed scheme is expected to offer a reduced computational load for longer feedback paths. [ABSTRACT FROM AUTHOR]
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- 2018
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7. Robust modeling of acoustic paths using a sparse adaptive algorithm.
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Maheshwari, Jyoti and George, Nithin V.
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ROBUST control , *ACOUSTIC field , *MEAN square algorithms , *FINITE impulse response filters , *HEARING aids - Abstract
Acoustic impulse response functions are generally sparse in nature and traditionally these are modeled by adaptive finite impulse response (FIR) filters trained using a least mean square (LMS) algorithm. The conventional LMS algorithm is not effective in modeling sparse systems and sparse LMS algorithms have been recently developed to improve the modeling in such scenarios. However, the traditional sparse LMS algorithms are not robust to disturbances at the error sensor and may diverge in some scenarios. With an objective to overcome this limitation of conventional sparse adaptive algorithm, this paper presents a robust sparse adaptive algorithm. The new algorithm has been shown to effectively model sparse systems in a robust manner. In addition, the algorithm has been successfully applied in modeling the acoustic feedback path in a behind the ear digital hearing aid. [ABSTRACT FROM AUTHOR]
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- 2016
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8. Nonlinear active noise control using spline adaptive filters.
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Patel, Vinal and George, Nithin V.
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NONLINEAR control theory , *ACTIVE noise control , *ADAPTIVE filters , *INTERPOLATION , *SIMULATION methods & models - Abstract
A spline adaptive filter (SAF) based nonlinear active noise control (ANC) system is proposed in this paper. The SAF consists of a linear network of adaptive weights in cascade with an adaptive nonlinear network. The nonlinear network, in-turn consists of an adaptive look-up table followed by a spline interpolation network and forms an adaptive activation function. An update rule has been derived for the proposed ANC system, which not only updates the weights of the linear network, but also updates the nature of the activation function. An extensive simulation study has been conducted to evaluate the noise mitigation performance of the proposed scheme and the new method has been shown to provide improved noise cancellation efficiency with a lesser computational load in comparison with other popular ANC systems. [ABSTRACT FROM AUTHOR]
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- 2015
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9. Convex combination of nonlinear adaptive filters for active noise control.
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George, Nithin V. and Gonzalez, Alberto
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CONVEX surfaces , *ADAPTIVE filters , *ACTIVE noise control , *NONLINEAR systems , *ARTIFICIAL neural networks , *PERFORMANCE evaluation - Abstract
Abstract: This paper proposes a nonlinear active noise control (ANC) system based on convex combination of a functional link artificial neural network (FLANN) and a Volterra filter. Simulation study reveals enhanced noise cancelation performance of the proposed ANC system over the ones based on its component filters. [Copyright &y& Elsevier]
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- 2014
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10. Advances in active noise control: A survey, with emphasis on recent nonlinear techniques
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George, Nithin V. and Panda, Ganapati
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ACTIVE noise & vibration control , *NONLINEAR theories , *SIGNAL processing , *SOFT computing , *NONLINEAR control theory , *SIGNAL theory - Abstract
Abstract: This paper discusses the evolution of active noise control systems over the past 75 years. The focus of this study is on the use of signal processing and some recent soft computing tools on the development of active noise control systems. Special attention has been paid to the advances in nonlinear active noise control achieved during the past decade. [Copyright &y& Elsevier]
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- 2013
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11. Active control of nonlinear noise processes using cascaded adaptive nonlinear filter
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George, Nithin V. and Panda, Ganapati
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ACTIVE noise & vibration control , *NONLINEAR theories , *ADAPTIVE filters , *FUNCTIONAL analysis , *ARTIFICIAL neural networks , *COMPARATIVE studies - Abstract
Abstract: A novel nonlinear adaptive filter based on a cascade combination of a functional link artificial neural network (FLANN) and a Legendre polynomial has been proposed in this paper for nonlinear active noise control (ANC). The performance of the new controller has been compared with that obtained by a FLANN based ANC system trained using a filtered-s least mean square (FsLMS) algorithm as well as with a Legendre neural network (LeNN) based ANC system trained using a filtered-l LMS (FlLMS) algorithm. The training of the cascaded controller has been achieved using a filtered-sl LMS (FslLMS) algorithm, which simultaneously adapts the weights of both the component adaptive controllers. The new controller has been shown to achieve improved noise mitigation capability in comparison to its constituent filters. [Copyright &y& Elsevier]
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- 2013
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12. A robust filtered-s LMS algorithm for nonlinear active noise control
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George, Nithin V. and Panda, Ganapati
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LEAST squares , *ALGORITHMS , *ACTIVE noise & vibration control , *MICROPHONES , *ARTIFICIAL neural networks , *SIMULATION methods & models , *PERFORMANCE evaluation - Abstract
Abstract: The performance of a nonlinear active noise control (ANC) system based on the recently developed filtered-s least mean square (FsLMS) algorithm deteriorates when strong disturbances in the ANC system are acquired by the microphones. To surmount this shortcoming, a novel robust FsLMS (RFsLMS) algorithm is proposed for a functional link artificial neural network (FLANN) based ANC system. The new ANC system is least sensitive to such disturbances and does not call for any prior information on the noise characteristics. The results obtained from simulation study establish the effectiveness of this new ANC scheme. [Copyright &y& Elsevier]
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- 2012
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13. A robust evolutionary feedforward active noise control system using Wilcoxon norm and particle swarm optimization algorithm
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George, Nithin V. and Panda, Ganapati
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ROBUST control , *EVOLUTIONARY computation , *FEEDFORWARD control systems , *ACTIVE noise & vibration control , *PARTICLE swarm optimization , *ALGORITHMS , *SIMULATION methods & models - Abstract
Abstract: The conventional filtered-x least mean square (FxLMS) algorithm commonly employed for active noise control (ANC) is sensitive to disturbances acquired by the error microphone and yields poor performance in such scenario. To circumvent this problem, in this paper, a Wilcoxon FxLMS (WFxLMS) algorithm is proposed and used in the design of an efficient ANC which is robust to outliers in the secondary path and immune to burst noise acquired by the error microphone. It is demonstrated through simulation study that under such situation the proposed algorithm outperforms the traditional FxLMS algorithm. A particle swarm optimization (PSO) algorithm based robust ANC system, which does not require the modeling of the secondary path is also derived in the paper. Improved performance of the robust evolutionary ANC system over L2 norm based evolutionary ANC system is also shown. [Copyright &y& Elsevier]
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- 2012
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14. On the development of adaptive hybrid active noise control system for effective mitigation of nonlinear noise
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George, Nithin V. and Panda, Ganapati
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ADAPTIVE control systems , *ACTIVE noise & vibration control , *NONLINEAR theories , *FEEDBACK control systems , *PERFORMANCE evaluation , *ARTIFICIAL neural networks , *SIMULATION methods & models - Abstract
Abstract: The presence of nonlinearities as well as acoustic feedback deteriorates the cancellation performance of the conventional filtered-x LMS (FxLMS) algorithm based active noise control (ANC) systems. With an objective to improve the performance, a novel filtered-su LMS (FsuLMS) algorithm based ANC system which employs a convex combination of an adaptive IIR filter with a functional link artificial neural network (FLANN) is proposed in this paper. The corresponding learning algorithm of the ANC system is derived and used in the simulation study for performance evaluation. Simulation study reveals enhanced performance of the proposed system over that of its component filters. [Copyright &y& Elsevier]
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- 2012
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15. Weibull M-transform least mean square algorithm.
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Kumar, Krishna and George, Nithin V.
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LEAST squares , *MEAN square algorithms , *ALGORITHMS , *SYSTEM identification , *LEARNING strategies - Abstract
This paper proposes a new robust learning strategy, which is based on a Weibull M-transform function. The suitability of the Weibull M-transform function as a robust norm has been investigated for different shape and scale parameters, and a Weibull M-transform least mean square (WMLMS) algorithm has been developed. Further, the bound of learning rate has been derived for the proposed algorithm. The proposed WMLMS algorithm has been evaluated for the problem of system identification and simulation studies carried out demonstrate its robustness. In addition, a filtered-x WMLMS (Fx-WMLMS) algorithm has been developed for robust room equalization and has been shown to offer stable room equalization even in the presence of strong disturbances picked up by the microphone. [ABSTRACT FROM AUTHOR]
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- 2020
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16. Multi-channel spline adaptive filters for non-linear active noise control.
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Patel, Vinal and George, Nithin V.
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ACTIVE noise control , *ADAPTIVE filters , *FINITE impulse response filters , *SPLINES , *IMPULSE response , *NOISE control - Abstract
• Multi-channel non-linear active noise control system. • Lower complexity over conventional schemes. • The nonlinearity of the filter is adaptive. • Improved noise cancellation over other schemes. This paper presents a non-linear multi-channel active noise control (ANC) scheme based on a set of adaptive spline filters as the component controllers. An adaptive spline filter comprises an adaptive finite impulse response (FIR) structure, which is followed by an adaptive spline activation function. A suitable learning rule is developed that updates the parameters of the adaptive FIR filter as well as of the adaptive spline function. Bounds on the learning rates for the proposed method are estimated and a detailed analysis on the computational complexity of the proposed scheme is presented. The proposed method is shown to offer good noise mitigation under non-linear ANC scenarios at a significantly lower computational load in comparison with other methods. In addition, due to the adaptive nature of the activation function, the proposed controller can transform itself from a non-linear to a linear one depending on the noise control scenario. [ABSTRACT FROM AUTHOR]
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- 2020
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17. A generalized maximum correntropy criterion based robust sparse adaptive room equalization.
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Kumar, Krishna and George, Nithin V.
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IMPULSE response , *ADAPTIVE filters , *MEAN square algorithms , *ROOMS , *LEARNING strategies - Abstract
An adaptive room equalization scheme is usually employed to compensate for the distortion of sound produced by the room impulse response, thereby offering an improved listening experience. In a conventional adaptive room equalizer, an adaptive filter updated using a filtered-x least mean square (FxLMS) algorithm is used to achieve room equalization. Conventional FxLMS algorithm based room equalizers are not robust to strong disturbances picked up by the reference microphone. A robust adaptive room equalization scheme based on a generalized maximum correntropy criteria has been developed in this paper. The performance has been further enhanced by using a proportionate learning strategy to take advantage of the sparse nature of the room impulse response. The proposed algorithm has been shown to provide enhanced room equalization performance over other methods compared, for various types of noise distributions. [ABSTRACT FROM AUTHOR]
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- 2020
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18. Speech quality enhancement using a two channel sparse adaptive filtering approach.
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Kajla, Priyanka and George, Nithin V.
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SPEECH enhancement , *ADAPTIVE filters , *BLIND source separation , *IMPULSE response , *ACOUSTIC models , *LEARNING strategies , *ARCHITECTURAL acoustics - Abstract
A forward two channel blind source separation scheme can be used as a effective method for speech enhancement. In such a scheme, two mixed sound signals are used as inputs to estimate the original signals which created these mixtures. In an endeavour to enhance the speech quality, an attempt has been made in this paper to design a two channel blind source separation method based on a sparse learning strategy. The proposed approach takes advantage of the sparse nature of the acoustic path impulse responses of the mixing model and offers improved speech quality in comparison with traditional approach. Simulation study shows the improvement in speech quality in terms of perceptual evaluation of speech quality by the proposed sparse forward two channel blind source separation scheme. [ABSTRACT FROM AUTHOR]
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- 2020
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19. Generalized spline nonlinear adaptive filters.
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Rathod, Milan, Patel, Vinal, and George, Nithin V.
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GENERALIZATION , *NONLINEAR systems , *ADAPTIVE filters , *SPLINE theory , *RADIAL basis functions , *PARAMETER estimation - Abstract
A new nonlinear filter, which employs an adaptive spline function as the basis function is designed in this paper. The input signal to this filter is used to generate suitable parameters to update the control points in a spline function. The update rule for updating the control points have been derived and a mean square analysis has been carried out. The output of the spline functions are suitably combined together to obtain the filter response. This filter is called the generalized spline nonlinear adaptive filter (GSNAF). The proposed GSNAF is similar to a functional link artificial neural network (FLANN), considering a functional expansion using spline basis functions. GSNAF has been shown to offer improved accuracy in benchmark classification scenarios and provide enhanced modeling accuracy in single input single output as well as in multiple input multiple output dynamic system identification cases. [ABSTRACT FROM AUTHOR]
- Published
- 2017
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20. Robust equalizer design for adaptive room impulse response compensation.
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Jariwala, Rushi, Upadhyaya, Ishan, and George, Nithin V.
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EQUALIZERS (Electronics) , *IMPULSE response , *ACOUSTIC signal processing , *MEAN square algorithms , *ADAPTIVE filters , *ELECTRONIC equipment design - Abstract
Adaptive room equalization aims at providing a listener with an audio experience, which is very close to the original audio signal. The equalizer, which is an adaptive filter, compensates for the disturbance in the audio signal contributed by the impulse response of the room. One of the most popular algorithms employed for the design of an adaptive room equalizer is the filtered-x improved proportionate normalized least mean square (Fx-IPNLMS) algorithm. IPNLMS is effective in equalizing sparse as well as non-sparse room impulse responses. However, Fx-IPNLMS is not robust to strong disturbances picked up by the microphone used in the equalization process and the algorithm may even diverge in such scenarios. With an objective to overcome this limitation of IPNLMS based adaptive room equalization schemes, a robust Fx-IPNLMS algorithm has been developed in this paper. The new algorithm has been shown to provide robust room equalization and thus an enhanced audio experience. [ABSTRACT FROM AUTHOR]
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- 2017
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21. Robust active noise control: An information theoretic learning approach.
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Kurian, Nikhil Cherian, Patel, Kashyap, and George, Nithin V.
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ACTIVE noise control , *INFORMATION theory , *ROBUST control , *ADAPTIVE control systems , *ENTROPY (Information theory) - Abstract
Nonlinear active noise control (ANC) systems, which employ a nonlinear filter as the adaptive controller is not robust when the primary noise to be mitigated has a non-Gaussian distribution. The algorithm which updates the weights of the controller may even diverge for some higher magnitude primary noise signals. With an objective to improve the robustness of nonlinear ANC systems, a correntropy based nonlinear ANC system is developed in this paper. The proposed ANC scheme uses an information theoretic learning approach and has been shown to provide robust noise mitigation even for non-Gaussian primary noise signals. [ABSTRACT FROM AUTHOR]
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- 2017
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22. Nonlinear system identification using a cuckoo search optimized adaptive Hammerstein model.
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Gotmare, Akhilesh, Patidar, Rohan, and George, Nithin V.
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NONLINEAR systems , *SYSTEM identification , *SEARCH algorithms , *ADAPTIVE computing systems , *HAMMERSTEIN equations , *ARTIFICIAL neural networks - Abstract
An attempt has been made in this paper to model a nonlinear system using a Hammerstein model. The Hammerstein model considered in this paper is a functional link artificial neural network (FLANN) in cascade with an adaptive infinite impulse response (IIR) filter. In order to avoid local optima issues caused by conventional gradient descent training strategies, the model has been trained using a cuckoo search algorithm (CSA), which is a recently proposed stochastic algorithm. Modeling accuracy of the proposed scheme has been compared with that obtained using other popular evolutionary computing algorithms for the Hammerstein model. Enhanced modeling capability of the CSA based scheme is evident from the simulation results. [ABSTRACT FROM AUTHOR]
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- 2015
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23. A family of logarithmic hyperbolic cosine spline nonlinear adaptive filters.
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Patel, Vinal, Bhattacharjee, Sankha Subhra, and George, Nithin V.
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ADAPTIVE filters , *ACTIVE noise control , *SPLINES , *SPLINE theory , *COMPUTATIONAL complexity , *NONLINEAR systems - Abstract
• Robust non-linear active noise control system. • Lower complexity over conventional schemes. • The nonlinearity of the filter is adaptive. • Improved noise cancellation over other robust schemes. Spline nonlinear adaptive filters are well known for their ability to efficiently model nonlinear systems while having low computational complexity. However, the performance of traditional spline adaptive filter degrades in the presence of impulsive disturbances. For improving the performance of spline adaptive filters in impulsive noise scenarios, a logarithmic hyperbolic cosine spline adaptive filter is proposed in this paper. To improve the convergence rate while maintaining low steady-state error, a variable parameter approach for the logarithmic hyperbolic cosine spline adaptive filter is also proposed. In addition, a robust nonlinear active noise control approach is also designed based on the proposed logarithmic hyperbolic cosine spline adaptive filter. The computational complexity of the proposed algorithms is studied and two approximate versions of the logarithmic hyperbolic cosine spline adaptive filter are proposed to decrease computational cost without degrading performance. Bound on learning rates are also derived to ensure the stability of the proposed adaptive systems. The simulation studies conducted, demonstrate the enhanced performance achieved by the proposed algorithms. [ABSTRACT FROM AUTHOR]
- Published
- 2021
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24. Design of a class of zero attraction based sparse adaptive feedback cancellers for assistive listening devices.
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Bhattacharjee, Sankha Subhra, Pradhan, Somanath, and George, Nithin V.
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ASSISTIVE listening systems , *INTELLIGIBILITY of speech , *HEARING aids , *COMPUTATIONAL complexity , *ALGORITHMS , *PERCEIVED quality - Abstract
Acoustic feedback is a frequently encountered problem in assistive listening devices (ALDs). Feedback paths in ALDs are typically sparse in nature and sparsity aware adaptive feedback cancellers can improve perceived audio quality under such scenarios. In an endeavour to improve the feedback canceller performance, a decorrelated polynomial zero attraction (DPZA) normalized least mean square (NLMS) feedback canceller is proposed in this paper. DPZA-NLMS algorithm is seen to have higher computational complexity. Hence, in an attempt to reduce computational complexity, a decorrelated l 0 -NLMS (D- l 0 -NLMS) and a decorrelated Versoria zero attraction NLMS (DVZA-NLMS) based feedback canceller are also proposed. Feedback canceller performance in terms of convergence and tracking performance as well as speech/audio quality and speech intelligibility is compared. In addition, computational complexity and memory requirements of the algorithms are also compared thus providing a hearing aid designer with better trade off choices between computational requirements and feedback cancellation performance. [ABSTRACT FROM AUTHOR]
- Published
- 2021
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25. Corrosion detection in steel bar: A time-frequency approach.
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Majhi, Subhra, Mukherjee, Abhijit, George, Nithin V., and Uy, Brian
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STEEL bars , *STEEL corrosion , *ULTRASONIC waves , *WAVEGUIDES , *TENSILE tests , *MILD steel - Abstract
This paper presents a new technique for discerning corrosion in steel bars using guided ultrasonic waves with an improved signal processing technique. A mild steel bar has been subjected to accelerated corrosion. Information concerning variation in spectral traits associated with the spread of corrosion has been discerned. Dispersion curves for the steel bar have been deduced to understand and correlate the observed change in time-frequency spectra with shift in predominant modes with spread of corrosion. Theoretical and measured mass loss in the steel rebar is used as physical parameters to evaluate corrosion. Tensile tests of corroded specimen have also been undertaken to measure the residual strength of the corroded bars. The superiority of the proposed signal processing technique in clearly discerning the state of corrosion has been demonstrated. [ABSTRACT FROM AUTHOR]
- Published
- 2019
- Full Text
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26. Acoustic feedback cancellation in digital hearing aids: A sparse adaptive filtering approach.
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Pradhan, Somanath, Patel, Vinal, Patel, Kashyap, Maheshwari, Jyoti, and George, Nithin V.
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ACOUSTICS , *ELECTRONIC feedback , *HEARING aids , *ADAPTIVE filters , *STOCHASTIC convergence - Abstract
Cancelling the effect of acoustic feedback is a challenging task in the design of a behind the ear digital hearing aid. In traditional behind the ear digital hearing aids, feedback cancellation is usually achieved using an adaptive finite impulse response filter, the weights of which are updated using a suitable learning rule. However, the impulse response of the acoustic feedback path in a hearing aid is sparse in nature and traditional feedback cancellation systems are not designed to utilize this sparseness. An adaptive feedback canceller, which is trained using a set of sparse adaptive algorithms is designed in this paper to take advantage of the sparseness. Further, an attempt has been made to enhance the convergence of the feedback cancellation mechanism by introducing an adaptive de-correlation filter as well as using the concept of probe noise injection. The proposed feedback cancellation schemes are shown to provide improved and accurate feedback cancellation over traditional feedback cancellation mechanisms. [ABSTRACT FROM AUTHOR]
- Published
- 2017
- Full Text
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27. Hybrid feedback active noise control headset based on binaural signal utilization.
- Author
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Patel, Vinal, Bhattacharjee, Sankha Subhra, Cheer, Jordan, and George, Nithin V.
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ACTIVE noise control , *MICROPHONES , *HEADPHONES , *ACOUSTIC field , *HEADSETS , *NOISE control , *KRONECKER products - Abstract
• Hybrid binaural structure for active noise control headphone system. • Nearest Kronecker product decomposition is introduced to improve noise cancellation performance. • Improved noise cancellation over other FBANC schemes for headphone system. A standard feedback active noise control (FBANC) headset utilizes the estimate of a primary disturbance at the left-ear (right-ear) error microphone to control noise only at the left (right) ear-cup, i.e., each ear's controller works independently. In contrast to the FBANC headset, in this paper, a binaural hybrid feedback active noise control (HFBANC) headset is designed that uses the estimate of the primary disturbances at both the left and right-ear error microphones to achieve improved noise control at both the left and right ear-cups. To further improve noise cancellation performance, the nearest Kronecker product decomposition technique is incorporated into the algorithm. The performance of the proposed HFBANC headset is compared to the standard FBANC headset under a variety of different sound field conditions. Experimental results show an improvement of 3–5 dB in the noise cancellation using the proposed algorithms, where the benefits are more prominent for noise sources originating from the side of the user (left and right). [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
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28. Robust and sparsity-aware adaptive filters: A Review.
- Author
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Kumar, Krishna, Pandey, Rajlaxmi, Karthik, M.L.N.S., Bhattacharjee, Sankha Subhra, and George, Nithin V.
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ADAPTIVE signal processing , *ADAPTIVE filters , *IMPULSE response , *COST functions , *ALGORITHMS - Abstract
An exhaustive review of adaptive signal processing schemes which are robust, sparsity-aware and robust as well as sparsity-aware has been carried out in this paper. Conventional robust learning approaches as well as the ones based on information theoretic methods have been included in the review. Further, adaptive filtering schemes which take advantage of the sparse nature of the system impulse responses have been reviewed, including the ones which are also robust. The cost functions used in these algorithms have been summarized and a timeline of algorithm development in this area has been added to provide an excellent overview on the topic. [ABSTRACT FROM AUTHOR]
- Published
- 2021
- Full Text
- View/download PDF
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