Narrow Results

Collaborative representation classification (CRC) is an important sparse method, which is easy to carry out and uses a linear combination of training samples to represent a test sample. CRC method utilizes the offset between representation result of each class and the test sample to implement classification. However, the offset usually cannot well express the difference between every class and the test sample. In this paper, we propose a novel representation method for image recognition to address the above problem. This method not only fuses sparse representation and CRC method to improve the accuracy of image recognition, but also has novel fusion mechanism to classify images. The implementations of the proposed method have the following steps. First of all, it produces collaborative representation of the test sample. That is, a linear combination of all the training samples is first determined to represent the test sample. Then, it gets the sparse representation classification (SRC) of the test sample. Finally, the proposed method respectively uses CRC and SRC representations to obtain two kinds of scores of the test sample and fuses them to recognize the image. The experiments of face recognition show that the combination of CRC and SRC has satisfactory performance for image classification.

The production cross sections for the synthesis of superheavy nuclei with charge number 118 are studied with the di-nuclear system model with dynamical potential surface (DNS-DyPES model). The dynamical potential energy surface (PES) and the fusion probabilities for ⁴⁸Ca bombarding Cf nuclei reactions are studied. By multiplying the capture cross section, fusion probability and survival probability, the evaporation residue(ER) cross sections for superheavy nuclei with Z = 118 are obtained. And the excitation functions for the reactions with a mixture target of Cf isotopes are also shown.

The fusion mechanism and the production cross sections for the synthesis of superheavy nuclei are studied with the di-nuclear system model with a dynamical potential energy surface (DNS-DyPES model). The potential energy surface is calculated and the fusion probability as a function of angular momentum is also investigated. It is found the fusion probability decreases with increasing the angular momentum. By multiplying the capture cross section, fusion probability and survival probability, the production cross sections for some superheavy nuclei are obtained. It is found the theoretical results are in good agreement with the experimental results.