Abstract:The sparse coding model for natural scene can explain some physiological properties of neurons in V1, but it is still unknown whether this coding model could be learned according to the biologically local synaptic plasticity rule.Due to the existence of the lateral inhibition phenomenon in the biological neural network, a neural network dynamic model was established based on this phenomenon and using the local synaptic plasticity.The simulation of the receptive field of V1 cells was carried out.At the same time, the reconstructed residuals were discussed by using the sparse reconstruction coefficients obtained by the model.The results show that the susceptibility field of V1 cells can be obtained by using the sparse coding, and the rationality of the kinetic model can be described by the input of natural images.
卢颍霞,王如彬. 关于稀疏编码在图像处理中的神经动力学分析[J]. 振动与冲击, 2018, 37(22): 17-21.
LU Yingxia,WANG Rubin. Nerve dynamics analysis on the sparse coding in image processing. JOURNAL OF VIBRATION AND SHOCK, 2018, 37(22): 17-21.
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