Filtered gradient algorithms applied to a subband adaptive filter structure

Apolinario, J.A.; Alves, R.G.; Diniz, Paulo S. R.; Swamy, M.N.S.

doi:10.1109/icassp.2001.940647

Cited by 8 publications

(5 citation statements)

References 6 publications

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“…According to the results in [10], it is noticed that the results of FGA and OGA algorithms are similar to those obtained by the normalised version of OGA (NOGA) algorithm. The convergence rate of the NOGA algorithm is shown that it is better than that of both FGA and OGA.…”

Section: A Mixed-tone Normalised Orthogonal Gradient Adaptive (Mt-nogsupporting

confidence: 50%

“…The orthogonal gradient adaptive (OGA) algorithm is formulated from the FGA algorithm [10] by introducing an orthogonal constraint between the present and previous direction vectors [17]. This OGA algorithm employs the optimised forgetting-factor on a sample-by-sample basis, so that the direction vector is orthogonal to the previous direction vector.…”

Section: A Mixed-tone Normalised Orthogonal Gradient Adaptive (Mt-nogmentioning

confidence: 99%

“…When the forgetting-factor is optimised sample by sample whereas a fixed forgetting-factor is used for FGA algorithm [10]. A normalised version of the OGA (NOGA) algorithm that has been introduced with the mixed-tone cost function and fixed step-size presented in [11].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Adaptive Step-Size Orthogonal Gradient-Based Per-Tone Equalisation in Discrete Multitone Systems

Sitjongsataporn¹

2012

Advances in Discrete Time Systems

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Section: A Mixed-tone Normalised Orthogonal Gradient Adaptive (Mt-nogsupporting

confidence: 50%

Section: A Mixed-tone Normalised Orthogonal Gradient Adaptive (Mt-nogmentioning

confidence: 99%

See 1 more Smart Citation

Adaptive Step-Size Orthogonal Gradient-Based Per-Tone Equalisation in Discrete Multitone Systems

Sitjongsataporn¹

2012

Advances in Discrete Time Systems

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“…In order to improve the convergence properties, the adaptive orthogonal gradient-based algorithm has been presented, which can provide with the development of simple and robust adaptive filtering across the wide range of input environments [29], [30]. Motivation for using the orthogonal gradient-based algorithm is concerned with the development of simple and robust adaptive filtering by the normalised orthogonal gradient adaptive (NOGA) algorithm.…”

Section: Introductionmentioning

confidence: 99%

Diffusion Hammerstein Spline Adaptive Filtering Based on Orthogonal Gradient Adaptive Algorithm

Sitjongsataporn

2022

IEEE Access

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In this paper, we propose a class of nonlinear diffusion filtering based on Hammerstein function with the spline adaptive filter (HSAF) implemented by normalised version of orthogonal gradient adaptive (NOGA) algorithm over the distributed network. Diffusion adaptation algorithm approximates a variable vector with the help of a network of agents using a joint optimisation on the sum of cost function. A HSAF comprises of memoryless function during learning by interpolating polynomials with respect to the linear filter. We derive a diffusion adaptation framework on HSAF motivated from NOGA algorithm; called DHSAF-NOGA. There are two types of adaptive diffusion strategies with the combine-then-adapt (CTA) algorithm and the adapt-then-combine (ATC) algorithm that are considered and implemented by DHSAF-NOGA algorithm. The network stability and performance over mean square error networks is derived. Experiment results depict that proposed CTA-DHSAF-NOGA and ATC-DHSAF-NOGA algorithms can learn robustly underlying the nonlinear Hammerstein model compared with a non-cooperative solution and existing techniques.

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“…This leads to an idea of mixed-subcarrier cost function presented in [3]. In order to improve the convergence properties, the orthogonal gradient adaptive (OGA) algorithm has been presented by using the orthogonal projection in conjunction with the filtered gradient adaptive algorithm [4].…”

Section: Introductionmentioning

confidence: 99%

Variable step-size orthogonal gradient-based algorithm with gradient weighted average method

Sitjongsataporn

Nurarak

2013

2013 13th International Symposium on Communications and Information Technologies (ISCIT)

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In this paper, a variable step-size normalised orthogonal gradient adaptive algorithm based on the gradient weighted average approach and mixed-subcarrier criterion is proposed for orthogonal frequency division multiplexing systems. In order to enhance convergence rate and a low misadjustment error, a gradient-based weighted avearage algorithm is introduced for a smooth gradient vector by means of weighted-averaging with mixed-subcarrier criterion. A convergence analysis of proposed algorithm is presented. Simulation results show that the proposed algorithm can improve the convergence rate compared with the existing algorithm.

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Filtered gradient algorithms applied to a subband adaptive filter structure

Cited by 8 publications

References 6 publications

Adaptive Step-Size Orthogonal Gradient-Based Per-Tone Equalisation in Discrete Multitone Systems

Adaptive Step-Size Orthogonal Gradient-Based Per-Tone Equalisation in Discrete Multitone Systems

Diffusion Hammerstein Spline Adaptive Filtering Based on Orthogonal Gradient Adaptive Algorithm

Variable step-size orthogonal gradient-based algorithm with gradient weighted average method

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