The Experts below are selected from a list of 4656 Experts worldwide ranked by ideXlab platform
Javad Poshtan - One of the best experts on this subject based on the ideXlab platform.
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a new adaptive recursive rls based fast array IIR filter for active noise and vibration control systems
Signal Processing, 2011Co-Authors: Allahyar Montazeri, Javad PoshtanAbstract:Infinite impulse response Filters have not been used extensively in active noise and vibration control applications. The problems are mainly due to the multimodal error surface and instability of adaptive IIR Filters used in such applications. Considering these, in this paper a new adaptive recursive RLS-based fast-array IIR filter for active noise and vibration control applications is proposed. At first an RLS-based adaptive IIR filter with computational complexity of order O(n^2) is derived, and a sufficient condition for its stability is proposed by applying passivity theorem on the equivalent feedback representation of this adaptive algorithm. In the second step, to reduce the computational complexity of the algorithm to the order of O(n) as well as to improve its numerical stability, a fast array implementation of this adaptive IIR filter is derived. This is accomplished by extending the existing results of fast-array implementation of adaptive FIR Filters to adaptive IIR Filters. Comparison of the performance of the fast-array algorithm with that of Erikson's FuLMS and SHARF algorithms confirms that the proposed algorithm has faster convergence rate and ability to reach a lower minimum mean square error which is of great importance in active noise and vibration control applications.
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a new adaptive recursive rls based fast array IIR filter for active noise and vibration control systems
Signal Processing, 2011Co-Authors: Allahyar Montazeri, Javad PoshtanAbstract:Infinite impulse response Filters have not been used extensively in active noise and vibration control applications. The problems are mainly due to the multimodal error surface and instability of adaptive IIR Filters used in such applications. Considering these, in this paper a new adaptive recursive RLS-based fast-array IIR filter for active noise and vibration control applications is proposed. At first an RLS-based adaptive IIR filter with computational complexity of order O(n^2) is derived, and a sufficient condition for its stability is proposed by applying passivity theorem on the equivalent feedback representation of this adaptive algorithm. In the second step, to reduce the computational complexity of the algorithm to the order of O(n) as well as to improve its numerical stability, a fast array implementation of this adaptive IIR filter is derived. This is accomplished by extending the existing results of fast-array implementation of adaptive FIR Filters to adaptive IIR Filters. Comparison of the performance of the fast-array algorithm with that of Erikson's FuLMS and SHARF algorithms confirms that the proposed algorithm has faster convergence rate and ability to reach a lower minimum mean square error which is of great importance in active noise and vibration control applications.
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a computationally efficient adaptive IIR solution to active noise and vibration control systems
IEEE Transactions on Automatic Control, 2010Co-Authors: Allahyar Montazeri, Javad PoshtanAbstract:In spite of special advantages of IIR Filters in active noise and vibration control (ANVC) applications, the multimodal error surface and instability problem of adaptive IIR Filters has prevented its extensive use. To alleviate these problems, in this paper, a new RLS-based fast array adaptive IIR Filters in ANVC applications is proposed. The algorithm is developed with slow adaptation assumption and by transforming the active noise and vibration control problem to an output-error identification problem. By derivation of the fast-array equivalent form both computational complexity and numerical stability of the proposed algorithm are improved. The geometrical illustration of the algorithm, in a simple case, is also given to unify and complete its mathematical formulation. In spite of low computational complexity of the order , simulation results confirm high convergence speed of the proposed algorithm and also its ability to reach the lower minimum mean square error in comparison with commonly used adaptive IIR algorithms in ANVC systems.
Allahyar Montazeri - One of the best experts on this subject based on the ideXlab platform.
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a new adaptive recursive rls based fast array IIR filter for active noise and vibration control systems
Signal Processing, 2011Co-Authors: Allahyar Montazeri, Javad PoshtanAbstract:Infinite impulse response Filters have not been used extensively in active noise and vibration control applications. The problems are mainly due to the multimodal error surface and instability of adaptive IIR Filters used in such applications. Considering these, in this paper a new adaptive recursive RLS-based fast-array IIR filter for active noise and vibration control applications is proposed. At first an RLS-based adaptive IIR filter with computational complexity of order O(n^2) is derived, and a sufficient condition for its stability is proposed by applying passivity theorem on the equivalent feedback representation of this adaptive algorithm. In the second step, to reduce the computational complexity of the algorithm to the order of O(n) as well as to improve its numerical stability, a fast array implementation of this adaptive IIR filter is derived. This is accomplished by extending the existing results of fast-array implementation of adaptive FIR Filters to adaptive IIR Filters. Comparison of the performance of the fast-array algorithm with that of Erikson's FuLMS and SHARF algorithms confirms that the proposed algorithm has faster convergence rate and ability to reach a lower minimum mean square error which is of great importance in active noise and vibration control applications.
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a new adaptive recursive rls based fast array IIR filter for active noise and vibration control systems
Signal Processing, 2011Co-Authors: Allahyar Montazeri, Javad PoshtanAbstract:Infinite impulse response Filters have not been used extensively in active noise and vibration control applications. The problems are mainly due to the multimodal error surface and instability of adaptive IIR Filters used in such applications. Considering these, in this paper a new adaptive recursive RLS-based fast-array IIR filter for active noise and vibration control applications is proposed. At first an RLS-based adaptive IIR filter with computational complexity of order O(n^2) is derived, and a sufficient condition for its stability is proposed by applying passivity theorem on the equivalent feedback representation of this adaptive algorithm. In the second step, to reduce the computational complexity of the algorithm to the order of O(n) as well as to improve its numerical stability, a fast array implementation of this adaptive IIR filter is derived. This is accomplished by extending the existing results of fast-array implementation of adaptive FIR Filters to adaptive IIR Filters. Comparison of the performance of the fast-array algorithm with that of Erikson's FuLMS and SHARF algorithms confirms that the proposed algorithm has faster convergence rate and ability to reach a lower minimum mean square error which is of great importance in active noise and vibration control applications.
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a computationally efficient adaptive IIR solution to active noise and vibration control systems
IEEE Transactions on Automatic Control, 2010Co-Authors: Allahyar Montazeri, Javad PoshtanAbstract:In spite of special advantages of IIR Filters in active noise and vibration control (ANVC) applications, the multimodal error surface and instability problem of adaptive IIR Filters has prevented its extensive use. To alleviate these problems, in this paper, a new RLS-based fast array adaptive IIR Filters in ANVC applications is proposed. The algorithm is developed with slow adaptation assumption and by transforming the active noise and vibration control problem to an output-error identification problem. By derivation of the fast-array equivalent form both computational complexity and numerical stability of the proposed algorithm are improved. The geometrical illustration of the algorithm, in a simple case, is also given to unify and complete its mathematical formulation. In spite of low computational complexity of the order , simulation results confirm high convergence speed of the proposed algorithm and also its ability to reach the lower minimum mean square error in comparison with commonly used adaptive IIR algorithms in ANVC systems.
Nurhan Karaboga - One of the best experts on this subject based on the ideXlab platform.
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elimination of noise on transcranial doppler signal using IIR Filters designed with artificial bee colony abc algorithm
Digital Signal Processing, 2013Co-Authors: Nurhan Karaboga, Fatma LatifogluAbstract:Biomedical signals are usually contaminated by noise generated from sources such as power line interference and disturbances produced by the movement of the recording electrodes. Also the signal-to-noise ratio of biomedical signals is usually quite low. In addition, biomedical signals often interfere with each other. Therefore, the Filters employed for eliminating noise and interference are significant in the medical practice. Digital infinite impulse response (IIR) Filters have shorter filter length than the finite impulse response (FIR) Filters with the same frequency characteristic. Therefore, in this work, an approach based on digital IIR Filters are described for the elimination of noise on transcranial Doppler by using artificial bee colony (ABC) which is a popular swarm based optimization algorithm introduced recently. Moreover, the performance of the proposed approach is compared to particle swarm optimization algorithm.
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a new design method based on artificial bee colony algorithm for digital IIR Filters
Journal of The Franklin Institute-engineering and Applied Mathematics, 2009Co-Authors: Nurhan KarabogaAbstract:Digital Filters can be broadly classified into two groups: recursive (infinite impulse response (IIR)) and non-recursive (finite impulse response (FIR)). An IIR filter can provide a much better performance than the FIR filter having the same number of coefficients. However, IIR Filters might have a multi-modal error surface. Therefore, a reliable design method proposed for IIR Filters must be based on a global search procedure. Artificial bee colony (ABC) algorithm has been recently introduced for global optimization. The ABC algorithm simulating the intelligent foraging behaviour of honey bee swarm is a simple, robust, and very flexible algorithm. In this work, a new method based on ABC algorithm for designing digital IIR Filters is described and its performance is compared with that of a conventional optimization algorithm (LSQ-nonlin) and particle swarm optimization (PSO) algorithm.
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a new method for adaptive IIR filter design based on tabu search algorithm
Aeu-international Journal of Electronics and Communications, 2005Co-Authors: Adem Kalinli, Nurhan KarabogaAbstract:Abstract Adaptive digital Filters have proven their worth in a wide range of applications such as channel equalisation, noise reduction, echo cancelling, and system identification. These Filters can be broadly classified into two groups: finite impulse–response (FIR) and infinite impulse–response (IIR) Filters. IIR Filters have become the target of increasing interest because these Filters can reduce the filter order significantly as compared to FIR Filters. Tabu search is a heuristic optimisation algorithm which has been originally developed for combinatorial optimisation problems. It simulates the general rules of intelligent problem solving and has the ability of discovering the global minima in a multi-modal search space. In this work, a novel method based on tabu search is described for the design of adaptive IIR Filters.
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design of minimum phase digital IIR Filters by using genetic algorithm
Nordic Signal Processing Symposium, 2004Co-Authors: Nurhan Karaboga, Bahadir CetinkayaAbstract:Genetic Algorithm (GA) based design techniques are widely proposed for IIR Filters. However, the unstability problem and the phase distortion occurring during the design process are important disadvantages for IIR Filters. In this work, an effective design method using GA for minimum phase and stable digital IIR Filters is presented.
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designing digital IIR Filters using ant colony optimisation algorithm
Engineering Applications of Artificial Intelligence, 2004Co-Authors: Nurhan Karaboga, Adem Kalinli, Dervis KarabogaAbstract:Abstract In order to transform and analyse signals that have been sampled from analogue sources, digital signal processing (DSP) algorithms are employed. The advantages of DSP are based on the fact that the performance of the applied algorithm is always predictable. There is no dependence on the tolerances of electrical components as in analogue systems. DSP algorithms can be reasonably described as a digital filter. Digital Filters can be broadly divided into two-sub classes: finite impulse-response Filters and infinite impulse-response (IIR) Filters. Because the error surface of IIR Filters is generally multi-modal, global optimisation techniques are required in order to avoid local minima and design efficient digital IIR Filters. In this work, a new method based on the ant colony optimisation algorithm with global optimisation ability is proposed for digital IIR filter design. Simulation results show that the proposed approach is accurate and has a fast convergence rate, and the results obtained demonstrate that the proposed method can be efficiently used for digital IIR filter design.
Varun Bajaj - One of the best experts on this subject based on the ideXlab platform.
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a new design method for stable IIR Filters with nearly linear phase response based on fractional derivative and swarm intelligence
IEEE Transactions on Emerging Topics in Computational Intelligence, 2017Co-Authors: N Agrawal, Anil Kumar, Varun BajajAbstract:In this paper, a new design method based on fractional derivative (FD) is proposed for designing digital stable infinite impulse response (IIR) Filters with nearly linear-phase response. In this method, the design problem is formulated as a phase error optimization of an all-pass filter connected in parallel with a pure delay function. FD is employed to improve the frequency response of the filter at some reference point $(\omega _{{0}})$ in the passband. Optimal values of FD constraints and reference points in passband are determined by minimizing the sum of error in passband $(E_{p})$ and stopband $(E_{s})$ of an IIR filter, using different evolutionary techniques such as particle swarm optimization (PSO), constraint factor inertia PSO (CFI-PSO), quantum PSO, artificial bee colony algorithm, and cuckoo search technique. Comparative study provides evidence that the proposed method, based on CFI-PSO, gives the best performance amongst the employed swarm-based techniques. Experimental results show the impact of the proposed method as compared to earlier reported techniques in terms of improved response in passband and sharper transition width. However, small reduction in stopband attenuation $(A_{s})$ is observed within the allowable limit when compared to nonfractional design approaches.
A Djebbari - One of the best experts on this subject based on the ideXlab platform.
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noise reduction in high order IIR Filters using optimal error feedback based upon a chebyshev criterion
Signal Processing, 1998Co-Authors: A Djebbari, J M Rouvaen, M F BelbachirAbstract:Abstract An efficient method is proposed to design error feedback to reduce quantization noise in canonical direct form realization of IIR Filters. The method is based on minimizing the weighted Chebyshev error derived between the noise-free desired filter and the designed one using a Remez loop. The noise power of the obtained filter is significantly lower than the initial one and better than Filters corrected using other proposed methods, without significantly increasing implementation cost.
