Adjoint least mean square control for solar photovoltaic array grid‐connected energy generating system

In this paper, we develop a modified adaptive combination strategy for the distributed estimation problem over diffusion networks. We still consider the online adaptive combiners estimation problem from the perspective of minimum variance unbiased estimation. In contrast with the classic adaptive combination strategy which exploits orthogonal projection technology, we formulate a non-constrained mean-square deviation (MSD) cost function by introducing Lagrange multipliers. Based on the Karush–Kuhn–Tucker (KKT) conditions, we derive the fixed-point iteration scheme of adaptive combiners. Illustrative simulations validate the improved transient and steady-state performance of the diffusion least-mean-square LMS algorithm incorporated with the proposed adaptive combination strategy.

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Adaptive decision feedback equaliser based on sparse incremental least mean square/fourth approach

Pramana ◽

10.1007/s12043-021-02156-3 ◽

2021 ◽

Vol 95 (3) ◽

Author(s):

Anjana Kumari ◽

Yash Keju Barapatre ◽

Swetaleena Sahoo ◽

Sarita Nanda

Keyword(s):

Decision Feedback ◽

Mean Square ◽

Least Mean Square

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Design and Analysis of the Fractional-Order Complex Least Mean Square (FoCLMS) Algorithm

Circuits Systems and Signal Processing ◽

10.1007/s00034-021-01715-8 ◽

2021 ◽

Author(s):

Jawwad Ahmad ◽

Muhammad Zubair ◽

Syed Sajjad Hussain Rizvi ◽

Muhammad Shafique Shaikh

Keyword(s):

Fractional Order ◽

Order Complex ◽

Mean Square ◽

Least Mean Square

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Adaptive Modified Versoria Zero Attraction Least Mean Square Algorithms

IEEE Transactions on Circuits & Systems II Express Briefs ◽

10.1109/tcsii.2020.2999886 ◽

2020 ◽

Vol 67 (12) ◽

pp. 3602-3606 ◽

Cited By ~ 2

Author(s):

Sankha Subhra Bhattacharjee ◽

Dwaipayan Ray ◽

Nithin V. George

Keyword(s):

Mean Square ◽

Least Mean Square

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A Novel Neuron in Kernel Domain

ISRN Signal Processing ◽

10.1155/2013/748914 ◽

2013 ◽

Vol 2013 ◽

pp. 1-11 ◽

Cited By ~ 1

Author(s):

Zahra Khandan ◽

Hadi Sadoghi Yazdi

Keyword(s):

Neural Network ◽

Online Learning ◽

Mean Square ◽

Least Mean Square ◽

Backpropagation Neural Network ◽

Adaptive Parameters ◽

Kernel Parameter ◽

Online Learning Algorithms ◽

Adaptive Kernel ◽

Kernel Least Mean Square

Kernel-based neural network (KNN) is proposed as a neuron that is applicable in online learning with adaptive parameters. This neuron with adaptive kernel parameter can classify data accurately instead of using a multilayer error backpropagation neural network. The proposed method, whose heart is kernel least-mean-square, can reduce memory requirement with sparsification technique, and the kernel can adaptively spread. Our experiments will reveal that this method is much faster and more accurate than previous online learning algorithms.

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