Proceedings of ELM-2017

Häftad, Engelska, 2019

Del i serien Proceedings in Adaptation, Learning and Optimization

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Beskrivning

ELM learning theories show that effective learning algorithms can be derived based on randomly generated hidden neurons (biological neurons, artificial neurons, wavelets, Fourier series,etc) as long as they are nonlinear piecewise continuous, independent of training data and application environments.

Produktinformation

Utgivningsdatum:2019-12-10
Mått:155 x 235 x 19 mm
Vikt:528 g
Format:Häftad
Språk:Engelska
Serie:Proceedings in Adaptation, Learning and Optimization
Antal sidor:340
Förlag:Springer Nature Switzerland AG
ISBN:9783030131821

Utforska kategorier

Artificiell intelligens inom Data och IT
Programmeringsböcker inom Data och IT

Innehållsförteckning

Adaptive Control of Vehicle Yaw Rate with Active Steering System and Extreme Learning Machine.- Sparse representation feature for facial expression recognition.- Protecting User Privacy in Mobile Environment using ELM-UPP.- Application Study of Extreme Learning Machine in Image Edge Extraction.- A Normalized Mutual Information Estimator Compensating Variance Fluctuations.- Reconstructing Bifurcation Diagrams of Induction Motor Drives using an Extreme Learning Machine.- Ensemble based error minimization reduction forELM.- The Parameter Updating Method Based onKalman Filter for Online Sequential ExtremeLearning Machine.- Extreme Learning Machine BasedShip Detection Using Synthetic Aperture Radar.