weighted least mean squaresA new error function based on weighted least-mean-square analysis is suggested for use in a back-propagation algorithm in neural networks. The standard back-propagation algorithm has been revised to minimize the sum of the weighted residual error squared. This method has...
The proposed neural network model is multilayer perceptron type with one hidden layer and one output layer Based on the mathematical explanations and the Adaptive filter theory we have proposed least mean square (LMS) algorithm for short term wind speed forecasting. We can make changes in the ...
[判断题](1分)Intermsofalgorithm,ADALINEneuralnetworkadoptsW-Hlearningrule,alsoknownastheleastmeansquare(LMS)algorithm.Itisdevelopedfromtheperceptronalgorithm,anditsconvergencespeedandaccuracyhavebeengreatlyimproved.()A.对B.,本题来源于在线网课《人工神经网
The Least Mean Square (LMS) error algorithm is an example of supervised training, in which the learning rule is provided with a set of examples of desired network behavior: {p1, t1}, {p2, t2}, …, {pi, ti}. Here, pi is an input to the network, and ti is the corresponding target...
monte-carlo-simulation equalizer equalization recursive-least-squares adaptive-equalizers adaptive-equalization least-mean-squares Updated Apr 19, 2021 MATLAB intelligent-control-lab / AGen Star 15 Code Issues Pull requests Adaptable generative prediction using recursive least square algorithm prediction...
The kernel least mean square (KLMS) algorithm is the simplest algorithm in kernel adaptive filters. However, the network growth of KLMS is still an issue for preventing its online applications, especially when the length of training data is large. The Nyström method is an efficient method for...
16.ON APPROXIMATE HEDGING A CONTINGENT CLAIM IN THE MINIMUM VARIANCE CRITERION最小方差准则下一个未定权益的近似对冲(英文) 17.DOA Passive Location Algorithm on Least Mean Square Error Criterion一种基于最小均方误差准则的唯方位定位方法 18.New Proof of Criterion for Uniformly Minimum Variance Unbiased Es...
A Neural Network Assisted FuLMS Algorithm forActive Noise Control System In active noise control (ANC) systems, the Filtered-u Least Mean Square (FuLMS) algorithm has better control performance and faster rate of convergence tha... L Jiang,H Liu,L Shi,... - International Conference on Commun...
4.2 Recursive least square-based system identification This method is a tool to estimate unknown parameters of a system in a dynamic manner. This method is the extended type of least mean square algorithm. At the beginning of this algorithm, let us assume, (50)[∑t=1Nφ(t)φT(t)]=R...
To determine the updating rules for the hidden layers, a similar back propagation method used in the SBP algorithm is developed. This permits the application of the learning procedure to all the neural network layers. Several experiments was carried out indicate significant reduction in the total ...