Results 11 to 20 of about 98,314 (264)
A review on extreme learning machine [PDF]
Multimedia Tools and Applications, 2021 AbstractExtreme learning machine (ELM) is a training algorithm for single hidden layer feedforward neural network (SLFN), which converges much faster than traditional methods and yields promising performance. In this paper, we hope to present a comprehensive review on ELM.
Jian Wang 0109 +3 more
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Massive MIMO as an Extreme Learning Machine [PDF]
IEEE Transactions on Vehicular Technology, 2021 This work shows that a massive multiple-input multiple-output (MIMO) system with low-resolution analog-to-digital converters (ADCs) forms a natural extreme learning machine (ELM). The receive antennas at the base station serve as the hidden nodes of the ELM, and the low-resolution ADCs act as the ELM activation function.
Dawei Gao +2 more
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A Novel Fault Diagnosis Method for Motor Bearing Based on DTCWT and AFSO-KELM
Shock and Vibration, 2021 Aiming at the defects of wavelet transform-based feature extraction and extreme learning machine-based classification, a novel fault diagnosis method for motor bearing, based on dual tree complex wavelet transform and artificial fish swarm optimization ...
Yan Lu, Peijiang Li
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FORECASTING OF CURRENCY CIRCULATION IN INDONESIA USING HYBRID EXTREME LEARNING MACHINE
Barekeng, 2022 Forecasting currency circulation, including inflow and outflow, is one of Bank Indonesia's strategies to maintain the Rupiah value's stability. The characteristic of inflow and outflow data is that they have seasonal variations.
Mujiati Dwi Kartikasari
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Augmented Quaternion Extreme Learning Machine
IEEE Access, 2019 As an efficient training strategy for single hidden layer neural networks, extreme learning machine, and its variants have been widely used due to its fast learning speed and superior generalization performance.
Huisheng Zhang, Hui Lv
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Sparse Extreme Learning Machine for Classification [PDF]
IEEE Transactions on Cybernetics, 2014 Extreme learning machine (ELM) was initially proposed for single-hidden-layer feedforward neural networks (SLFNs). In the hidden layer (feature mapping), nodes are randomly generated independently of training data. Furthermore, a unified ELM was proposed, providing a single framework to simplify and unify different learning methods, such as SLFNs ...
Zuo Bai +4 more
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Advances in Mechanical Engineering, 2014 This paper presented a novel procedure based on the ensemble empirical mode decomposition and extreme learning machine. Firstly, EEMD was utilized to decompose the vibration signals into a number of IMFs adaptively and the permutation entropy of each IMF
Jianzhong Zhou +5 more
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MATEC Web of Conferences, 2016 By means of the model of extreme learning machine based upon DE optimization, this article particularly centers on the optimization thinking of such a model as well as its application effect in the field of listed company’s financial position ...
Fu Yu, Mu Jiong, Duan Xu Liang
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An online deep extreme learning machine based on forgetting mechanism
Dianzi Jishu Yingyong, 2018 The development of deep learning promotes the development of deep online learning, and online learning tends to have strong effectiveness. Based on the principle of online extreme learning machine and the principle of autoencoder of deep extreme learning
Liu Buzhong
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Binary/ternary extreme learning machines [PDF]
Neurocomputing, 2015 In this paper, a new hidden layer construction method for Extreme Learning Machines (ELMs) is investigated, aimed at generating a diverse set of weights. The paper proposes two new ELM variants: Binary ELM, with a weight initialization scheme based on { 0 , 1 } -weights; and Ternary ELM, with a weight initialization scheme based on { - 1 , 0 , 1 ...
van Heeswijk, Mark, Miche, Yoan
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