Adaptive filters: stable but divergent

Rupp, Markus

doi:10.1186/s13634-015-0289-8

Cited by 10 publications

(6 citation statements)

References 73 publications

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“…where 0 ) ) 2 *+, ⁄ , and & = 3/; *+, is the maximum value of the auto correlation matrix of input x(k) and / is the standard deviation of the error signal. One of the adaptive IIR filtering LMS algorithms that has been found to be relatively stable and simple to implement is the Feintuch's LMS algorithm (Rupp, 2015;Stewart, 2006). The adaptive filter based on this algorithm is easily implemented using an IIR filter realization based on two transversal FIR filters as illustrated in Figure 1.…”

Section: Review Of Related Workmentioning

confidence: 99%

Development of an Adaptive IIR Filter Based on Modified Robust Mixed-Norm Algorithm for Adaptive Noise Cancellation

2019

CEIS

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Noise cancellation is one of the most important applications of adaptive filters. The employment of adaptive filtering in most digital signal processing tasks is currently an area of growing interest as adaptive filters, due to their dynamic nature, perform better than the traditional filters in compensating for random noise in their environment. However, the compensation for impulsive interference or noise is desired since most adaptive algorithms earlier proposed modelled noise as a random process of the White Gaussian distribution. A modified robust mixed-norm (MRMN) algorithm recently proposed to compensate for impulsive interference has been found to be hardware efficient, however the MRMN algorithm has only been tested on adaptive FIR system identification task. In this paper, an adaptive IIR filter based on MRMN adaptive algorithm is proposed and tested for noise cancellation task. The developed filter structure was modelled and simulated in MATLAB environment. The results obtained showed that the MRMN algorithm does in fact compensate for the presence of impulsive interference, however, at a higher computational complexity relative to the LMS algorithm.

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Section: Review Of Related Workmentioning

confidence: 99%

Development of an Adaptive IIR Filter Based on Modified Robust Mixed-Norm Algorithm for Adaptive Noise Cancellation

2019

CEIS

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“…An adaptive filter is a filter that self-adjusts its transfer function according to requirements, in our case, the load. However, such techniques are generally computationally expensive and sometimes, cause non-converging [20]. In our work, a simplified adaptive digital LPF structure is proposed that is guaranteed to converge and is practical to implement.…”

Section: B Algorithm Developmentmentioning

confidence: 99%

An innovative control strategy for a hybrid energy storage system (HESS)

Sun

Zhang

Awadallah

et al. 2017

2017 IEEE International Conference on Mechatronics (ICM)

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Abstract-Electric Vehicles (EVs) adopting both batteries and supercapacitors have attracted a significant amount of attention in research communities due to its unique power sharing capabilities. A Hybrid Energy Storage System (HESS) can effectively reduce power stress that would otherwise be applied to batteries alone, and whose weight and size is still a common concern when competing against conventional ICEpowered cars. In this paper, a high-level control strategy is developed to adaptively split the load between two sources for an electric vehicle adopting HESS under real-life load fluctuations. A converter -Supercapacitor Pack (SP) coupled HESS upon which such an algorithm is deployed on, is proposed to divert excess power that would otherwise overdraw from or damage the Battery Pack (BP) into the SP via a smart Power Converter (PC) which is located in between in order to regulate both behaviors. Such a power split strategy (PSS) is designed in such a way to track real-time load profiles and determines one important variable -the cut-off frequency. As a consequence, relatively higher frequency portion of the load power gets channeled to the SP and the remaining lessvarying power demand is sent to the BP based on the fundamental energy balancing equation. A simplified HESS model is first developed. The power split algorithm is coded in Matlab and then applied to this HESS model. Finally, the overall system is tested comprehensively over 4 EPA driving cycles. Simulation results prove its effectiveness in coping with even the harshest driving scenarios in real life.

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“…At the same time, it was shown that the recursive leastsquares (RLS) filter can be derived by relaxing the same criterion. Moreover, the H ∞ approach led to a so-called energy-conservation law, which has been extensively used to analyze the robustness of various kinds of adaptive filters (e.g., [2][3][4]). Thus, it established a unified framework for understanding the fundamental properties of adaptive filters [5,6].…”

Section: Introductionmentioning

confidence: 99%

An Order-Recursive Lattice Algorithm for H<sup>∞</sup> Adaptive Filtering

Matsuzaki¹

2020

Journal of Signal Processing

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We present an order-recursive lattice algorithm for H ∞ adaptive filtering. The standard H ∞ filter algorithm is expressed in an alternative formula that is closed in a relaxed sense. On the basis of this formula, the algorithm is reformulated as an indefinite least-squares problem that can be solved by a two-dimensional block recursive least-squares (RLS) algorithm. Then an H ∞ lattice filter is derived by transforming the block RLS algorithm into its multivariable least-squares lattice form. The resulting computational complexity is still proportional to the filter order, although 2 × 2 matrix computations are involved. The equivalence between the standard H ∞ filter and its lattice version is verified by numerical experiments. Keywords: adaptive filtering, H ∞ filter, lattice filter This paper is organized as follows. Section 2 introduces a typical H ∞ adaptive filtering problem and its recursive solution. Section 3 derives a pseudo-closed-form expression for the standard solution, which is used to reformulate H ∞ adaptive filtering as an indefinite least-squares problem. In Sec. 4, the indefinite least-squares problem is solved by employing a two-dimensional block RLS algo-

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Adaptive filters: stable but divergent

Cited by 10 publications

References 73 publications

Development of an Adaptive IIR Filter Based on Modified Robust Mixed-Norm Algorithm for Adaptive Noise Cancellation

Development of an Adaptive IIR Filter Based on Modified Robust Mixed-Norm Algorithm for Adaptive Noise Cancellation

An innovative control strategy for a hybrid energy storage system (HESS)

An Order-Recursive Lattice Algorithm for H<sup>∞</sup> Adaptive Filtering

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