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Image super-resolution aims to recover a fine-resolution image from one or more low-resolution image(s). In this paper, we propose a novel image super-resolution approach based on the recent development of coupled deep auto-encoder. In the training step, the vector of the local low resolution (LR) and high resolution image (HR) patches and the corresponding edge information are extracted to be the...
In this paper, a new method is proposed to identify solid oxide fuel cell using extreme learning machine–Hammerstein model (ELM–Hammerstein). The ELM–Hammerstein model consists of a static ELM neural network followed by a linear dynamic subsystem. First, the structure of ELM–Hammerstein model is determined by Lipschitz quotient criterion from input–output data. Then, a generalized ELM algorithm is...
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