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For Internet of Things (IoT) edge devices, it is very attractive to have the local sensemaking capability instead of sending all the data back to the cloud for information processing. For image pattern recognition, neuro-inspired machine learning algorithms have demonstrated enormous powerfulness. To effectively implement learning algorithms on-chip for IoT edge devices, on-chip synaptic memory architectures...
Deep belief network (DBN) has been successfully applied in variety areas such as image recognition and natural language processing. In this paper, we investigate the signal demodulation problems in different types of communication channels. Then, a novel deep belief networks (DBN)-based demodulator is proposed. Since the DBN-based method is just like a black box that can automatically learn how to...
Based on the "pharmacology" method, this paper puts forward that safety consciousness concentration is the key factor to judge the effect of safety education and training in response to the lack of effective supervision in the enterprise safety training. Besides, the paper provides a theoretical basis for enterprise to formulate the training programs scientifically and rationally by establishing...
This paper proposed a new algorithm of multi-category SVM incremental learning by analyzing the distribution characteristics of the intrusion detection data. Samples used in learning were selected by measuring the distance between samples and their class-centers, and they are just those samples which will most possibly be the SVs in incremental learning. By several binary-class hyper-planes, the zones...
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