Abstract: The growing demand for ultra-high-speed data transmission in short-reach optical interconnects exacerbates inter-symbol interference (ISI) and device-induced nonlinearities, presenting ...
In this work, we introduce a new method ability radial basic function-partial least square (RBF-PLS) with high accuracy and precision in QSPR studies. Three quantitative structure-propertty ...
Dr. James McCaffrey presents a complete end-to-end demonstration of the kernel ridge regression technique to predict a single numeric value. The demo uses the kernel matrix inverse (Cholesky ...
Dr. James McCaffrey presents a complete end-to-end demonstration of the kernel ridge regression technique to predict a single numeric value. The demo uses stochastic gradient descent, one of two ...
ABSTRACT: Based on theorems, the Atomic AString Functions theory, evolving since the 1970s, is introduced into Quantum Mechanics to represent a wave function via the shifts and stretches of smooth ...
Introduction: Intelligent vehicles and autonomous driving have been the focus of research in the field of transport, but current autonomous driving models have significant errors in lateral tracking ...
Radial Basis Function Neural Networks (RBFNNs) are a type of neural network that combines elements of clustering and function approximation, making them powerful for both regression and classification ...
First at all, thanks a lot for putting this nice tool available for everyone. It is really nice! I have a question regarding which RBF basis to choose in case I am interested in obtaining smooth ...
It has been proven that robot-assisted rehabilitation training can effectively promote the recovery of upper-limb motor function in post-stroke patients. Increasing patients’ active participation by ...
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