Control of a hands-free telephone set

Abstract-Selective-tap algorithms employing the MMax tap selection criterion were originally proposed for low-complexity adaptive filtering. The concept has recently been extended to multichannel adaptive filtering and applied to stereophonic acoustic echo cancellation. This paper first briefly reviews least mean square versions of MMax selective-tap adaptive filtering and then introduces new recursive least squares and affine projection MMax algorithms. We subsequently formulate an analysis of the MMax algorithms for time-varying system identification by modeling the unknown system using a modified Markov process. Analytical results are derived for the tracking performance of MMax selective tap algorithms for normalized least mean square, recursive least squares, and affine projection algorithms. Simulation results are shown to verify the analysis.

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“…For a typical range [27], and since , it can be seen that the conditions (36) and consequently (35) are satisfied. Hence, reduces as .…”

Section: Settingmentioning

confidence: 92%

“…It is interesting, from a step-size control point of view, that we proceed to evaluate the step-size which achieves the lowest misalignment by letting (27) and differentiating (26) with respect to to obtain (28) …”

Section: B Steady-state Misalignment For mentioning

confidence: 99%

Selective-Tap Adaptive Filtering With Performance Analysis for Identification of Time-Varying Systems

Khong

Naylor

2007

IEEE Trans. Audio Speech Lang. Process.

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“…Here, and denote the approximation errors between the system (1) and the T-S fuzzy model (2). We assume that there exist and such that the following inequalities hold for all : …”

Section: The Modeling Of a Class Of Nonlinear Discrete-time Systementioning

confidence: 99%

“…In order to identify a fuzzy model for (1), we assume and are independent identically distributed random signals uniformly distributed in the interval [ 1,1] [26]. Then and in the fuzzy rules [see (2)] can be obtained using the following steps.…”

Section: Remark 42mentioning

confidence: 99%

“…It turns out that the noise attenuation level guaranteed by an filter design without considering nonnegligible time delays may become invalid in the presence of time delays. Time delays often arise in many signal-processing related problems, such as echo cancellation, local loop equalization, multipath propagation in mobile communications, and array signal processing [2], [11], [15]. Several robust filtering approaches for linear systems with multiple time delays have been developed over the past few years [4], [7], [17], [18], [27], [31].…”

Section: Introductionmentioning

confidence: 99%

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Fuzzy $H_\infty$ Filter Design for a Class of Nonlinear Discrete-Time Systems With Multiple Time Delays

Zhang

Lun

Liu

2007

IEEE Trans. Fuzzy Syst.

132

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This paper studies the fuzzy filter design problem for signal estimation of nonlinear discrete-time systems with multiple time delays and unknown bounded disturbances. First, the Takagi-Sugeno (T-S) fuzzy model is used to represent the state-space model of nonlinear discrete-time systems with time delays. Next, we design a stable fuzzy filter based on the T-S fuzzy model, which guarantees asymptotic stability and a prescribed index for the filtering error system, irrespective of the time delays and uncertain disturbances. A sufficient condition for the existence of such a filter is established by using the linear matrix inequality (LMI) approach. The proposed LMI problem can be efficiently solved with global convergence guarantee using convex optimization techniques such as the interior point algorithm. Simulation examples are provided to illustrate the design procedure of the present method.

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Fuzzy H ∞ Filter Design for Nonlinear Discrete-Time Systems with Multiple Time-Delays

Fuzzy Modeling and Fuzzy Control

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Control of a hands-free telephone set

Cited by 13 publications

References 6 publications

Selective-Tap Adaptive Filtering With Performance Analysis for Identification of Time-Varying Systems

Selective-Tap Adaptive Filtering With Performance Analysis for Identification of Time-Varying Systems

Fuzzy $H_\infty$ Filter Design for a Class of Nonlinear Discrete-Time Systems With Multiple Time Delays

Fuzzy H ∞ Filter Design for Nonlinear Discrete-Time Systems with Multiple Time-Delays

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