Coordination of Self-Organization and External Intelligence

在自组织系统中，大量具有可修改状态的信息处理元件协同工作。这样一个完整的系统可以揭示复杂和复杂的信息处理。本研究计划利用此能力，在联合数据压缩和虚拟电影生成。通过本研究获得了以下方法和结果。(1)采用多下降成本竞争的方法，得到一种新的学习自组织算法。该算法同时生成权向量特征图和组向量特征图。(2)数字静止图像的数据压缩是通过多重下降成本竞争来实现的。这创建了一组可变形颜色区域图案和一组网格图案。(3)根据外部智能的规范对分组模式进行变形，从而生成虚拟数字电影。(4)进一步加入深度信息，生成虚拟三维动画，这些新方法和结果对改善人机界面具有一定的借鉴意义。

In self-organizing systems, a massively large number of information processing elements with modifiable states work together in coordination. Such a total system can reveal complex and sophisticated information processing. This research project utilized this ability in joint data compression and virtual movie generation. The following methods and results were obtained by this study.(1) Multiple descent cost competition is applied to obtain a new learning and self-organization algorithm. This algorithm generates a weight vector feature map and a group vector feature map simultaneously.(2) Digital still image is data-compressed by the multiple descent cost competition. This created a set of deformable color region patterns and a group mesh pattern.(3) The grouping pattern was deformed according to the specification of external intelligence so that virtual digital movie can be generated.(4) Depth information was further added so that virtual 3D movie can be generated.The above new methods and results can be understood to improve computer human interface.