Jin Xin, Zhou Dongming, Jiang Qian, Chu Xing, Yao Shaowen, Li Keqin, Zhou Wei
IEEE Trans Cybern. 2022 Jul;52(7):6354-6368. doi: 10.1109/TCYB.2020.3043233. Epub 2022 Jul 4.
The intersecting cortical model (ICM), initially designed for image processing, is a special case of the biologically inspired pulse-coupled neural-network (PCNN) models. Although the ICM has been widely used, few studies concern the internal activities and firing conditions of the neuron, which may lead to an invalid model in the application. Furthermore, the lack of theoretical analysis has led to inappropriate parameter settings and consequent limitations on ICM applications. To address this deficiency, we first study the continuous firing condition of ICM neurons to determine the restrictions that exist between network parameters and the input signal. Second, we investigate the neuron pulse period to understand the neural firing mechanism. Third, we derive the relationship between the continuous firing condition and the neural pulse period, and the relationship can prove the validity of the continuous firing condition and the neural pulse period as well. A solid understanding of the neural firing mechanism is helpful in setting appropriate parameters and in providing a theoretical basis for widespread applications to use the ICM model effectively. Extensive experiments of numerical tests with a common image reveal the rationality of our theoretical results.
交叉皮层模型(ICM)最初是为图像处理而设计的,是受生物启发的脉冲耦合神经网络(PCNN)模型的一个特例。尽管ICM已被广泛使用,但很少有研究关注神经元的内部活动和放电条件,这可能导致该模型在应用中无效。此外,缺乏理论分析导致参数设置不当,从而限制了ICM的应用。为了解决这一缺陷,我们首先研究ICM神经元的持续放电条件,以确定网络参数与输入信号之间存在的限制。其次,我们研究神经元脉冲周期以理解神经放电机制。第三,我们推导持续放电条件与神经脉冲周期之间的关系,并且该关系也能证明持续放电条件和神经脉冲周期的有效性。深入理解神经放电机制有助于设置合适的参数,并为有效使用ICM模型进行广泛应用提供理论基础。对一幅普通图像进行的大量数值测试实验揭示了我们理论结果的合理性。