For the sustainable supply of mineral resources, blind deposits are becoming the emphasis of exploration after long-period exploitation of exposed deposits.The collection and analysis of gravity or magnetic data repre...For the sustainable supply of mineral resources, blind deposits are becoming the emphasis of exploration after long-period exploitation of exposed deposits.The collection and analysis of gravity or magnetic data represents one of the cheapest forms of large-scale geophysical exploration.With the identification of potential fields,we can get the map of worms or skeletonizations showing the three-dimension structure of shallow crust,and find the展开更多
For the sustainable supply of mineral resources, blind deposits are becoming the emphasis of exploration after long-period exploitation of exposed deposits.The collection and analysis of gravity or magnetic data repre...For the sustainable supply of mineral resources, blind deposits are becoming the emphasis of exploration after long-period exploitation of exposed deposits.The collection and analysis of gravity or magnetic data represents one of the cheapest ways of large-scale geophysical exploration.With the identification of potential mineral fields,we can get the map of worms or skeletonizations showing展开更多
To make the modulation classification system more suitable for signals in a wide range of signal to noise rate （SNR）, a feature extraction method based on signal wavelet packet transform modulus maxima matrix （WPT...To make the modulation classification system more suitable for signals in a wide range of signal to noise rate （SNR）, a feature extraction method based on signal wavelet packet transform modulus maxima matrix （WPTMMM） and a novel support vector machine fuzzy network （SVMFN） classifier is presented. The WPTMMM feature extraction method has less computational complexity, more stability, and has the preferable advantage of robust with the time parallel moving and white noise. Further, the SVMFN uses a new definition of fuzzy density that incorporates accuracy and uncertainty of the classifiers to improve recognition reliability to classify nine digital modulation types （i.e. 2ASK, 2FSK, 2PSK, 4ASK, 4FSK, 4PSK, 16QAM, MSK, and OQPSK）. Computer simulation shows that the proposed scheme has the advantages of high accuracy and reliability （success rates are over 98% when SNR is not lower than 0dB）, and it adapts to engineering applications.展开更多
文摘For the sustainable supply of mineral resources, blind deposits are becoming the emphasis of exploration after long-period exploitation of exposed deposits.The collection and analysis of gravity or magnetic data represents one of the cheapest forms of large-scale geophysical exploration.With the identification of potential fields,we can get the map of worms or skeletonizations showing the three-dimension structure of shallow crust,and find the
文摘For the sustainable supply of mineral resources, blind deposits are becoming the emphasis of exploration after long-period exploitation of exposed deposits.The collection and analysis of gravity or magnetic data represents one of the cheapest ways of large-scale geophysical exploration.With the identification of potential mineral fields,we can get the map of worms or skeletonizations showing
文摘To make the modulation classification system more suitable for signals in a wide range of signal to noise rate （SNR）, a feature extraction method based on signal wavelet packet transform modulus maxima matrix （WPTMMM） and a novel support vector machine fuzzy network （SVMFN） classifier is presented. The WPTMMM feature extraction method has less computational complexity, more stability, and has the preferable advantage of robust with the time parallel moving and white noise. Further, the SVMFN uses a new definition of fuzzy density that incorporates accuracy and uncertainty of the classifiers to improve recognition reliability to classify nine digital modulation types （i.e. 2ASK, 2FSK, 2PSK, 4ASK, 4FSK, 4PSK, 16QAM, MSK, and OQPSK）. Computer simulation shows that the proposed scheme has the advantages of high accuracy and reliability （success rates are over 98% when SNR is not lower than 0dB）, and it adapts to engineering applications.
