In this paper, we derive two modified RLS algorithms to tackle this problem. In the first algorithm, namely, the true weight decay RLS (TWDRLS) algorithm, we ...
Two regularizers for recursive least squared algorithms in feedforward ...
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Simulation results show that both algorithms improve the generalization capability of the trained network. Index Terms—Generalizability of feedforward ...
Recursive least squares (RLS)-based algorithms are a class of fast online training algorithms for feedforward multilayered neural networks (FMNNs).
In this paper, we derive two modified RLS algorithms to tackle this problem. In the first algorithm, namely, the true weight decay RLS (TWDRLS) algorithm, we ...
(2001): Two regularizers for recursive least squared algorithms in feedforward multilayered neural networks. - IEEE Trans. Neural Netw., Vol. 12, No. 6, pp ...
In this paper, we propose a numerically robust recursive least square type algorithm using prewhitening. The proposed algorithm improves the performance of RLS.
Dec 6, 2001 · Two regularizers for recursive least squared algorithms in feedforward multilayered neural networks · Author Picture Chi-Sing Leung,; Author ...
Leung, C.S., Tsoi, A.C.: Two-regularizers for Recursive Least Squared Algorithms in Feedforward Multilayered Neural Networks. IEEE Trans. Neural Networks 12, ...
... neural networks. Two regularizers for recursive least squared algorithms in feedforward multilayered neural networks. 2001, IEEE Transactions on Neural Networks ...
We present a recursive total least squares (RTLS) algorithm for multilayer feedforward neural networks. So far, recursive least squares (RLS) has been ...