Abstract—Inductive concept generation in image processing on neural networks that perform the algebra of Fourier-dual model-determining operations is considered. A model of initial (i.e., when there are no earlier concepts) concept generation is proposed. The biological inspiration of the model is established. The phenomenon of cognitive saturation is proposed, which is expressed by stopping the growth of the performance evaluation of the formation of an inductive hypothesis with an increasing number of examples. The mechanism of this phenomenon is analyzed and the relationship with the information capacity of patterns of the internal representations of perceived images, due to the inherent characteristics of the cognitive agent, is given. The simulation results are given based on the example of the Darii syllogism inversion when the weights of links are recorded in plane and in volume.

中文翻译：

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基于傅里叶对偶运算代数的图像处理概念的初始生成

摘要-考虑了执行傅立叶对偶模型确定运算的代数的神经网络图像处理中的归纳概念生成。提出了初始（即，当没有较早的概念时）概念生成的模型。建立了模型的生物学灵感。提出了认知饱和现象，这种现象可以通过增加实例的数量来停止对归纳假设形成的性能评估的增长来表达。分析了这种现象的机理，并给出了由于认知主体的固有特征而与感知图像的内部表示的图案的信息容量之间的关系。