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A partially decoupled rls algorithm for Volterra filters

IEEE TRANSACTIONS ON SIGNAL PROCESSING 1999年第2期47卷 579-582页

作者： Griffith, DW Arce, GR Raytheon Syst Co Command Control & Commun Div Marlborough MA 01752 USA Univ Delaware Dept Elect & Comp Engn Newark DE 19716 USA

In this correspondence, we consider a partially decoupled variation of the rls algorithm. It is based on a constrained optimization of the cumulative filter error using the higher order sets of filter weights to improve on the performance of the lower order weight sets whose values are already established. From this constrained optimization, a recursive algorithm is developed whose form closely resembles the standard Volterra rls algorithm hut with structural differences that arise from eliminating the dependence of the lower order weight sets on the higher order weight sets while retaining the dependence of the higher order weights on the lower order weights. The resulting algorithm, while suboptimal, requires less computational effort than the fully coupled version, converges to steady state in the same amount of time, and is shown by example not to exhibit a substantial degradation in performance.

关键词： rls algorithm Volterra filters

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Numeric Variable Forgetting Factor rls algorithm for Second-Order Volterra Filtering

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CIRCUITS SYSTEMS AND SIGNAL PROCESSING 2013年第1期32卷 223-232页

作者： Kohli, Amit Kumar Rai, Amrita Thapar Univ Dept Elect & Commun Engn Patiala 147004 Punjab India RIET Dept Elect & Commun Engn Faridabad 0121007 Haryana India

Nonlinear adaptive filtering techniques for system identification (based on the Volterra model) are widely used for the identification of nonlinearities in many applications. In this correspondence, the improved tracking capability of a numeric variable forgetting factor recursive least squares (NVFF-rls) algorithm is presented for first-order and second-order time-varying Volterra systems under a nonstationary environment. The nonlinear system tracking problem is converted into a state estimation problem of the time-variant system. The time-varying Volterra kernels are governed by the first-order Gauss-Markov stochastic difference equation, upon which the state-space representation of this system is built. In comparison to the conventional fixed forgetting factor recursive least squares algorithm, the NVFF-rls algorithm provides better channel estimation as well as channel tracking performance in terms of the minimum mean square error (MMSE) for first-order and second-order Volterra systems. The NVFF-rls algorithm is adapted to the time-varying signals by using the updating prediction error criterion, which accounts for the nonstationarity of the signal. The demonstrated simulation results manifest that the proposed method has good adaptability in the time-varying environment, and it also reduces the computational complexity.

关键词： Gauss-Markov model rls algorithm Volterra filter NVFF-rls Volterra filter Minimum mean square error Polynomial filters

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Convergence characteristics of the adaptive array using rls algorithm

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IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES 1997年第1期E80A卷 148-158页

作者： Asano, F Suzuki, Y Sone, T Electrotechnical Laboratory Tsukuba-shi 305 Japan R.I.E.C. Tohoku University Sendai-shi 980-77 Japan

The convergence characteristics of the adaptive beamformer with the rls algorithm are analyzed in this paper. In case of the rls adaptive beamformer, the convergence characteristics are significantly affected by the spatial characteristics of the signals/noises in the environment. The purpose of this paper is to show how these physical parameters affect the convergence characteristics. In this paper, a typical environment where a few directional noises are accompanied by background noise is assumed, and the influence of each component of the environment is analyzed separately using rank analysis of the correlation matrix. For directional components, the convergence speed is faster for a smaller number of noise sources since the effective rank of the input correlation matrix is reduced. In the presence of background noise, the convergence speed is slowed down due to the increase of the effective rank. However, the convergence speed can be improved by controlling the initial matrix of the rls algorithm. The latter section of this paper focuses on the physical interpretation of this initial matrix, in an attempt to elucidate the mechanism of the convergence characteristics.

关键词： adaptive beamformer rls algorithm spatial/temporal correlation matrix effective rank convergence characteristics

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A Nonlinear Acoustic Echo Canceller Using Sigmoid Transform in Conjunction With rls algorithm

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS 2008年第10期55卷 1056-1060页

作者： Fu, Jing Zhu, Wei-Ping Concordia Univ Dept Elect & Comp Engn Ctr Commun & Signal Proc Montreal PQ H3G 1M8 Canada

Nonlinearity of amplifiers and/or loudspeakers gives rise to nonlinear echo in acoustic systems, which seriously degrades the performance of speech and audio communications. Many nonlinear acoustic echo cancellation (AEC) methods have been proposed. In this paper, a simple yet efficient nonlinear echo cancellation scheme is presented by using an adaptable sigmoid function in conjunction with a conventional transversal adaptive filter. The new scheme uses the least mean square (LMS) algorithm to update the parameters of sigmoid function and the recursive least square (rls) algorithm to determine the coefficient vector of the transversal filter. The proposed AEC is proved to be convergent under some mild assumptions. Computer simulations show that the proposed scheme gives a superior echo cancellation performance over the well known Volterra filter approach when the echo path suffers from the saturation-type nonlinear distortion. More importantly, the new AEC has a much lower computational complexity than the Volterra-filter-based method.

关键词： Acoustic echo cancellation rls algorithm sigmoid function

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Adaptive Turbo Equalization with Sparse Homotopy DCD-rls algorithm with Variable Forgetting Factor for Underwater Acoustic Communication

Adaptive Turbo Equalization with Sparse Homotopy DCD-RLS Alg...

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IEEE/OES China Ocean Acoustics (COA)

作者： Zhang Youwen Liu Lu Sun Dajun Harbin Engn Univ Coll Underwater Acoust Engn Acoust Sci & Technol Lab Harbin Peoples R China

ISBN: (纸本)9781467399784

Underwater acoustic channels have the features of sparse and time varying. Adaptive filter has become a common and useful tool for underwater acoustic communications over the sparse and time-varying channels. In this paper, we propose a novel homotopy dichotomous coordinate descent (DCD) recursive least squares (rls) adaptive filtering algorithm, which incorporates the variable forgetting factor (VFF). Compared with the conventional rls-type algorithms, the proposed algorithm can obtain its performance via two aspects: 1) making a remarkable improvement in a sparse fast time varying underwater acoustic channel and 2) reducing the computational complexity by using Homotopy DCD iterations. Numerical and lake experimental results show that the proposed algorithm has better tracking ability and a lower steady-state normalized mean square error (NMSE).

关键词： rls algorithm Homotopy dichotomous coordinate descent algorithm variable forgetting factor adaptive filter

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Variable Forgetting Factor rls algorithm for Adaptive Echo Cancellation 14

Variable Forgetting Factor RLS Algorithm for Adaptive Echo C...

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14th International Conference on Control, Automation and Systems (ICCAS)

作者： Sukhumalchayaphong, Sethaphak Benjangkaprasert, Chawalit King Mongkuts Inst Technol Ladkrabang Fac Engn Bangkok Thailand

ISBN: (纸本)9788993215069

Adaptive algorithms are widely used for support a wide range of applications. The attractive one application is an echo canceller in the long distance telephone network. The performance improvement of the echo cancellers depends on the choice of the adaptive filtering algorithm. Therefore, in this paper the variable forgetting factor recursive least squares (rls) algorithm for adaptive lattice structure filter for the echo canceller in telephone network is presented. The proposed echo canceller provides high performance and low misadjustment in steady state for all considered noise distributions.

关键词： Echo canceller LMS algorithm rls algorithm Adaptive Lattice structure

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Research on Load Voltage Characteristics Based on Improved rls algorithm 9

Research on Load Voltage Characteristics Based on Improved R...

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IEEE 9th International Power Electronics and Motion Control Conference (IPEMC-ECCE Asia)

作者： Chen, Han Liu, Ying-ying Wang, Hui Wang, Tong-xun Hao, Rui-xiang Li, Da-lu Beijing Jiaotong Univ Sch Elect Engn Beijing Peoples R China Global Energy Interconnect Res Inst Co Ltd Inst Power Elect Beijing Peoples R China State Key Lab Adv Power Transmiss Technol Beijing Peoples R China North China Elect Power Univ Baoding Dept Elect Engn Baoding Peoples R China TBEA Xinjiang Int Co Dept Investments Beijing Peoples R China

ISBN: (纸本)9781728153018

The problems of power supply voltage quality, system losses and power demand are increasing serious, load voltage characteristics need to be studied to solve these problems. The time-varying ZIP model can represent voltage dependence of loads and capture the load characteristics. This paper proposes the improved recursive least square (rls) algorithm which based on cumulant and variable forgetting factor to estimate time-varying ZIP model parameters, the proposed method can suppress the influence of noise and track the change of parameters quickly, and the results of simulation show the method has good tracking performance and strong robustness.

关键词： distribution network load voltage characteristic time-varying ZIP load model parameter identification rls algorithm

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Adaptive lattice-hammerstein rls algorithm for wireless nonlinear equalizers

Adaptive lattice-hammerstein RLS algorithm for wireless nonl...

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1st IEEE/IFIP International Conference in Central Asia on Internet (ICI)

作者： Eghtedari, M. Kahaei, M. H. Poshtan, J. Iran Univ Sci & Technol Coll Elect Engn Tehran 16844 Iran

ISBN: (纸本)0780391799

In this paper, the adaptive Recursive Least-Squares algorithm is derived for the Lattice-Hammerstein filter leading to the proposed rls Lattice-Hammerstein nonlinear adaptive filter. The performance of the proposed algorithm is compared to both SG Lattice-Hammerstein and LMS Transversal-Hammerstein algorithms in a nonlinear channel modeling scenario. It is shown that the convergence rate of the rls Lattice-Hammerstein algorithm is much higher than the other two with a lower steady-state error. Simplicity of the Hammerstein structure compared to the Volterra expression makes is more appropriate for modeling and equalizing nonlinear channels.

关键词： volterra series hammerstein series rls algorithm lattice structure.

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A Regularized rls algorithm for the Identification of Third-Order Tensors 14

A Regularized RLS Algorithm for the Identification of Third-...

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14th International Symposium on Electronics and Telecommunications (ISETC)

作者： Elisei-Iliescu, Camelia Paleologu, Constantin Benesty, Jacob Stanciu, Cristian Anghel, Cristian Univ Politehn Bucuresti Dept Telecommun Bucharest Romania Univ Quebec INRS EMT Montreal PQ Canada

ISBN: (纸本)9781728189215

The recently proposed recursive least-squares (rls) algorithm for trilinear forms, namely rls-TF, was designed for the identification of third-order tensors of rank one. In this context, a high-dimension system identification problem can be efficiently addressed (gaining in terms of both performance and complexity) based on tensor decompositions and modelling. In this paper, following the framework of the rls-TF, we propose a regularized version of this algorithm, where the regularization terms are incorporated within the cost functions. Furthermore, the optimal regularization parameters are derived, aiming at attenuating the effects of the system noise. Simulation results support the performance features of the proposed algorithm, especially in terms of its robustness in noisy environments.

关键词： Adaptive filters rls algorithm regularization system identification tensor decomposition

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Fiber-optic MZI activity monitoring based on rls algorithm 18

Fiber-optic MZI activity monitoring based on RLS algorithm

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18th International Conference on Optical Communications and Networks (ICOCN)

作者： Wang, Jiayu Xu, Wei Dong, Bo Yu, Changyuan Han, Shuying Natl Univ Singapore Suzhou Res Inst Suzhou 215123 Peoples R China Chinese Acad Sci Xian Inst Opt & Precis Mech Xian Peoples R China Anlight Optoelect Technol Inc Suzhou 215123 Peoples R China Hong Kong Polytech Univ Dept Elect & Informat Engn Kowloon Hong Kong Peoples R China Soochow Univ Sch Elect & Informat Engn Suzhou 215006 Peoples R China

A non-invasive activity monitoring using Mach-Zehnder interferometer (MZI) is presented and recursive least square (rls) algorithm is performed to classify presence and absence activity states with accuracy higher tha... 详细信息

ISBN: (纸本)9781728127644

关键词： Activity monitoring MZI rls algorithm

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