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Identifying and detecting the unknown abnormal sparse signal has become an important issue for distributed networks. In this paper, we proposed a new detection scheme based on convex optimization for wireless sensor networks. Under the Neyman-Pearson testing framework, the detection scheme first estimates the unknown signal by employing the convex optimization at the fusion center. Then the sensor...
In this paper, a new approach of blind estimation of subcarrier number based on multiple signal classification (MUSIC) algorithm is proposed for MB-OFDM ultra-wide band (UWB) communications system. The proposed eigenvalue-construct method only using signal autocorrelation of orthogonal frequency-division multiplexing (OFDM) symbols estimates the number of subcarriers. The computer simulations show...
Recently, the sparse overcomplete signal representations have been introduced to solve the direction-of-arrival (DOA) estimation problem by sensor array. However, it still has high computational complexity, and as the dictionary, i.e. a collection of possible direction response vectors, is required to be ldquoovercompleterdquo, it has to cover all the possible DOAs both of the interesting signals...
Due to the weak energy and nonstationarity, incipient fault characteristic signals are usually submerged by vibration signals of rotary machine and noise. Based on the multi-resolution feature and time-frequency localization feature of Wavelet Transform, a method to extract fault characteristic signals by decomposing them into corresponding time-frequency segmentations is presented. The noise is attenuated,...
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