Aiming at the weak noise signals the existence of plant diseases and insect pest images, pathological activity regulation of identification of the plant, so that between the signal molecules exist in plants can regulate mutually, collaborative work. Therefore, identification of weak signal molecules in plants is significant to the study of plant life activities. Taking corn pest images as the research object, using the identification method of lifting wavelet transform, combined with image identification technology, calculated the original plant diseases and insect pest images by not detect the break point of signal. Simulation results show that, the analysis of lifting wavelet of plant disease image identification technology reliability is about 71.65%; the accuracy of edge detection is about 76.21%. The operation speed of this algorithm is fast, easy for hardware implementation, provides an effective method for plant disease images identification.
This paper proposed the electron density of time series by using the Siesta software to calculate the weak electrical signals of ginseng molecule, combining with the lifting scheme DWT to remove ginseng molecular spatial redundancy. For the acquisition and identification of weak electrical signals of ginseng molecule in physical environment , based on the analysis of collection and identification’s principles, the noise coefficient is removed to reconstruct the signal and retain the useful signal components through applying the multi-decomposition of DWT transform to divide weak electrical signals of ginseng molecule into wavelet coefficients of different scales. The experimental results show that the multi-resolution analysis of DWT transform is performed for the weak electrical signal of ginseng molecule with different rhythms and different frequency ranges, and the weak electrical signal size of ginseng molecule before and after compression, the percentage of high frequency coefficients set to zero, and the average energy percentage after compression are, respectively, increased to 77.73%, 46.88%, and 99.99%. This algorithm operates fast enough to ease hardware implementation, providing an effective method for lossless compression of the weak electrical signals of ginseng molecule.
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