Performance analysis of industrial noise cancellation with pso based wiener filter using adaptive LMS & NLMS
03 Apr 2014-pp 363-368
TL;DR: A particle swarm optimization (PSO) based wiener filter for enhancement of filtering and a comparative analysis is performed on these algorithms and generated the MSE and PSNR values of signals.
Abstract: Industrial noise is generated due to the number of sources that interferes with the signals. The source and weight of noise signals are hard to analyze hence a collective form of noise called Gaussian Noise is considered in this paper. This noise is collective form of noise signals that arise in industrial and transmission scales of signal processing. We have implemented wiener filter, least-mean-square algorithm, normalized LMS algorithm for denoising the noisy signals. In this paper we propose a particle swarm optimization (PSO) based wiener filter for enhancement of filtering. A comparative analysis is performed on these algorithms and generated the MSE and PSNR values of signals..
Citations
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TL;DR: A hybrid adaptive scheme by combining particle swarm optimization (PSO) with conventional LMS algorithm, where PSO is utilized to search the optimal solution during the iterative process, and LMS is employed to avoid the local convergence, which is usually caused in PSO.
Abstract: This paper proposes an adaptive equalization algorithm for asynchronous cooperative communications in ad hoc networks, where amplify-and-forward relays are adopted, each of which is equipped with single antenna. Adaptive equalization technique is carried out at the destination node in this paper to remove inter-symbol interference, which is caused by the retransmissions of the asynchronous relays. Least mean squares (LMS) has been regarded as an effective adaptive method, but it has difficulty in obtaining the optimal solution. In this paper, we present a hybrid adaptive scheme by combining particle swarm optimization (PSO) with conventional LMS algorithm, where PSO is utilized to search the optimal solution during the iterative process, and LMS is employed to avoid the local convergence, which is usually caused in PSO. Numerical simulation results show that, the proposed scheme outperforms conventional LMS algorithm in convergence performance over Rayleigh flat fading channel, and meanwhile, a signal–noise-ratio gain of 6 dB or so is obtained when BER is 10−3.
4 citations
TL;DR: In this paper, the authors proposed an efficient design of adaptive filters which uses enhanced NLMS algorithm for eliminating noise added by mean of various communication media or any other noise sources, the concept of memory preallocation for variables has been introduced to enhance the computational speed of filtering system.
Abstract: This paper presents an efficient design of Adaptive filters which uses enhanced NLMS algorithm for eliminating noise added by mean of various communication media or any other noise sources. By using the appropriate weights, Adaptive filter estimates and remove the estimated noise signal from the available information. LMS and Normalized LMS are two most efficient algorithm for noise cancelation. Normalized form of LMS algorithm is considered more effective as it normalizes with the power of the input. The concept of memory preallocation for variables has been introduced to enhance the computational speed of filtering system. The proposed algorithm is successfully implemented using M Code and performance measures like SNR and MSE are calculated for varying step size and filter order. The SNR value ranges from 8.26 dB to 7.22 dB and MSE ranges from 0.087 to 0.1173.
3 citations
01 Jan 2018
TL;DR: The paper presents a novel algorithm that is hybrid of Nelder Mead algorithm and gradient method for the solution of Multimodal Optimization problems and was applied for the design of three tap Wiener filter.
Abstract: The paper presents a novel algorithm for the solution of Multimodal Optimization problems. The proposed method is hybrid of Nelder Mead algorithm and gradient method. The algorithm has direct application to problems encountered in the area of signal processing. The proposed method is applied for the estimation of taps in the design of adaptive filters. The convergence of the proposed algorithm is compared with the convergence trajectories of Steepest Descent method and found to be superior. The algorithm is presented for second order optimization problem and was applied for the design of three tap Wiener filter.
2 citations
01 Sep 2015
TL;DR: This paper presents the application of Adaptive filters in noise cancellation during various communication processes, where non-stationary signals are transmitted, and an efficient design using NLMS algorithm is implemented.
Abstract: This paper presents the application of Adaptive filters in noise cancellation during various communication processes, where non-stationary signals are transmitted. Adaptive filter estimates the noise signal and by applying the appropriate weights the estimated noise signal is eliminated from the information. For noise cancellation applications most efficient Adaptive filter Algorithms LMS and its normalized form NLMS are used and their comparative analysis is done in form of their output power, error power and SNR. In both of the algorithms concept of negative feedback is utilized in the cancellation of noise from the signal and thus both of these are also called negative feedback algorithms. Implementation and analysis is done by applying different step sizes on different order of filter. Order of filter is taken as 4, 8, 12 and then by changing the values of coefficients the graphical and computational analysis is done. Finally an efficient design using NLMS algorithm is implemented where order is taken as 8 and step size 0.2. This results as a low error power (11.7221 db) and a high value of SNR (1.1445) than that of LMS algorithms.
1 citations
Cites background from "Performance analysis of industrial ..."
...Therefore, in the area of Telecommunication and other Communication systems the transmission and processing of signals is of major concern....
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References
More filters
Book•
08 Feb 1996
TL;DR: For practicing engineers, researchers, and advanced students in signal processing, Active Noise Control Systems: Algorithms and DSP Implementations will serve as a comprehensive, state-of-the-art text/reference on this important and rapidly changing area of signal processing.
Abstract: From the Publisher:
Active noise control (ANC) is rapidly becoming the most effective way to reduce noises that can otherwise be very difficult and expensive to control ANC is achieved by introducing a canceling "anti-noise" wave through an appropriate array of secondary sources When applied accurately, ANC can provide effective solutions to noise-related problems in a broad range of areas, including manufacturing and industrial operations as well as consumer products Consequently, ANC research and development has become an important focus of both industrial applications and engineering research Active Noise Control Systems: Algorithms and DSP Implementations introduces the basic concepts of ANC with an emphasis on digital signal processing (DSP) hardware and adaptive signal processing algorithms, both of which have come into prominence within the last decade The authors emphasize the practical aspects of ANC systems by combining the principles of adaptive signal processing with both experimental results and practical implementation Applications are cited in many fields and encompass all types of noise media, including air-acoustic, hydroacoustic, vibrations, and others The specific implementation stressed is based on the TMS320 family of signal processors from Texas Instruments, which are the most widely used worldwide Coverage of theory includes concise derivations and analyses of commonly used adaptive structures and algorithms for active noise control applications, which are enhanced by the inclusion of a floppy disk featuring C and assembly programs for implementing many ANC systems Mathematical representations are employed and the source code included on the disk is in a form that is easily accessible to anyone using the book For practicing engineers, researchers, and advanced students in signal processing, Active Noise Control Systems: Algorithms and DSP Implementations will serve as a comprehensive, state-of-the-art text/reference on this important and rapidly de
1,561 citations
Book•
31 May 1997
TL;DR: Adaptive Filtering: Algorithms and Practical Implementation may be used as the principle text for courses on the subject, and serves as an excellent reference for professional engineers and researchers in the field.
Abstract: From the Publisher:
Adaptive Filtering: Algorithms and Practical Implementation is a concise presentation of adaptive filtering, covering as many algorithms as possible while avoiding adapting notations and derivations related to the different algorithms. Furthermore, the book points out the algorithms which really work in a finite-precision implementation, and provides easy access to the working algorithms for the practicing engineer. Adaptive Filtering: Algorithms and Practical Implementation may be used as the principle text for courses on the subject, and serves as an excellent reference for professional engineers and researchers in the field.
1,294 citations
"Performance analysis of industrial ..." refers methods in this paper
...If the adaptive filter is combined with a linear combiner, the output signal is composed by linear combination of signals coming from array to direct fonn FIR-structure (fig-2) [14]. y(k) = If...
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...The downhill simplex numerical optimization algorithm [14] [15] [16] is the conventional method for tuning filters followed by new methods like neural network, genetic algorithm and fuzzy logic based approaches [17][18][19]....
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01 Jun 1999
TL;DR: The basic adaptive algorithm for ANC is developed and analyzed based on single-channel broad-band feedforward control, then modified for narrow-bandFeedforward and adaptive feedback control, which are expanded to multiple-channel cases.
Abstract: Active noise control (ANC) is achieved by introducing a cancelling "antinoise" wave through an appropriate array of secondary sources. These secondary sources are interconnected through an electronic system using a specific signal processing algorithm for the particular cancellation scheme. ANC has application to a wide variety of problems in manufacturing, industrial operations, and consumer products. The emphasis of this paper is on the practical aspects of ANC systems in terms of adaptive signal processing and digital signal processing (DSP) implementation for real-world applications. In this paper, the basic adaptive algorithm for ANC is developed and analyzed based on single-channel broad-band feedforward control. This algorithm is then modified for narrow-band feedforward and adaptive feedback control. In turn, these single-channel ANC algorithms are expanded to multiple-channel cases. Various online secondary-path modeling techniques and special adaptive algorithms, such as lattice, frequency-domain, subband, and recursive-least-squares, are also introduced. Applications of these techniques to actual problems are highlighted by several examples.
1,254 citations
TL;DR: The main idea of the principle of PSO is presented; the advantages and the shortcomings are summarized; and some kinds of improved versions ofPSO and research situation are presented.
Abstract: Particle swarm optimization is a heuristic global optimization method and also an optimization algorithm, which is based on swarm intelligence. It comes from the research on the bird and fish flock movement behavior. The algorithm is widely used and rapidly developed for its easy implementation and few particles required to be tuned. The main idea of the principle of PSO is presented; the advantages and the shortcomings are summarized. At last this paper presents some kinds of improved versions of PSO and research situation, and the future research issues are also given.
699 citations
TL;DR: In this paper, the authors proposed a method based on the complete normalization of the extended Kalman filter (EKF) algorithm representation, which can put the EKF drive much closer to an off-the-shelf product.
Abstract: The use of an extended Kalman filter (EKF) as a nonlinear speed and position observer for permanent-magnet synchronous motor drives is a mature research topic. Notwithstanding, the shift from research prototype to a market-ready product still calls for a solution to some implementation pitfalls. The major and still unsolved topic is the choice of the EKF covariance matrices. This paper replaces the usual trial-and-error method with a straightforward matrices choice. These matrices, possibly combined with a novel self-tuning procedure, should put the EKF drive much closer to an off-the-shelf product. The proposed method is based on the complete normalization of the EKF algorithm representation. Successful experimental results are included in the paper.
491 citations
"Performance analysis of industrial ..." refers methods in this paper
...For the choice of the covariance matrices the method of normalization of the system matrices has been used for online determining the speed of pennanent-magnet synchronous motor and rotor position [21]....
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