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MBD technology is capable of integrating all the information of the design and process technology into the product 3D model. But in the MBD mode, the complex product has massive information, and its structure is extremely complicated. Generally, the existing methods for complex product information modeling have some limitations. By considering that, this paper proposed an F-B-S-F-I framework model...
In this paper, we introduce a learning based cognitive radio receiver to automatically demodulate several types of modulated signals without sophisticated digital signal pre-processing. Our embedded learning engine can automatically learn the signal features and then achieve signal demodulation through feature-based classification. The proposed demodulator consists of a neural network (NN) structure...
Automatic modulation recognition (AMR) and demodulation are two essential components in cognitive radio receivers. This paper proposes a novel method based on MSOM neural networks to automatically recognize the modulation type and demodulate the radio signal at the same time. This efficient method is directly applied to the normalized radio signal samples and has relatively low computation complexity...
Automatic modulation recognition (AMR) of communication signals is a critical and challenging task in cognitive radio systems. In this work, classifications of four digital modulation types, including BPSK, QPSK, GMSK and 2FSK, are investigated. From the received radio signal, a set of cyclic spectrum features are first calculated, and a principal component analysis (PCA) is applied to extract the...
This paper researches the optimization of inventory system with discrete time, single product and single period under uncertainty environment. The aim is to analyze the impact of the alterability of the initial storage, production batch, output and need on system optimal policy and optimum cost. According to random order, we put forwards the random comparison result of optimal inventory and optimum...
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