AI 中文总结
本文基于文献[1]的逻辑基础，证明了霍普菲尔德神经网络可将更多超立方体顶点编程为稳定态，为其“编程问题”提供了新视角。
AI 中文摘要
利用文献[1]提出的、将超立方体期望顶点作为稳定态来综合霍普菲尔德神经网络的逻辑基础，本文证明了无论神经元数量为偶数还是奇数，都可将更多超立方体顶点编程为稳定态，为霍普菲尔德神经网络的“编程问题”提供了新视角。
英文摘要
Using the logical basis of synthesizing Hopfield Neural Network with desired corners of hypercube as stable states (proposed in [1]), it is proved that more corners of hypercube can be programmed as stable states (whether the number of neurons is even or odd). The research paper presents a new perspective to the so called "Programming Problem" of Hopfield Neural Network.
