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Extreme learning machine (ELM) is an efficient training algorithm originally proposed for single-hidden layer feedforward networks (SLFNs), of which the input weights are randomly chosen and need not to be fine-tuned. In this paper, we present a new stack architecture for ELM, to further improve the learning accuracy of ELM while maintaining its advantage of training speed. By exploiting the hidden...
The existing image compression methods (e.g., JPEG2000, etc.) are vulnerable to bit-loss, and this is usually tackled by channel coding that follows. However, source coding and channel coding have conflicting requirement. In this paper, we address the problem with an alternative paradigm, and a novel compressive sensing (CS) based compression scheme is therefore proposed. Discrete wavelet transform...
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