Development of Intelligent System Method Based on a Macroscopic Viewpoint of Brain Functions and Construction of its Hardware System

作为智能系统的一种新的方法论，我们提出了一种基于模式信息的主动学习方法(PBALM)，它不需要复杂的计算公式，具有非精确处理的性质。PBALM是在模糊概念的基础上形成的，力求像人类一样处理信息。典型的模糊规则。另一方面，PBALM特征是模棱两可的模式处理。当人类从复杂目标获取知识时，这模拟了人脑在模式状图像中处理信息的建模过程中的本质，而不是利用数字解释。PBALM具有多个称为入侵检测系统的处理单元，其任务是从被建模的系统中提取有用的信息。为了实现一个能够进行复杂的大规模建模的具有良好容错体系结构的PBALM系统，专用的入侵检测硬件是必不可少的。为了开发这样的智能硬件系统，我们利用市场上的评估板试探性地设计了一个入侵检测硬件单元，并对其有效性进行了验证，因为我们用评估板确认了专用入侵检测硬件的有效性，所以我们开发了一种新的入侵检测处理单元--HIDS。我们设计了一块印刷电路板，在电路板上安装了一个运行在100 MHz的入侵检测控制器。在性能测试结果中，尽管只有4块HIDS板卡并行化，但与基于软件的PBALM相比，HIDS在处理时间上的性能远远优于PBALM。通过使用我们在本项目中开发的HIDS单元，PBALM系统将应用于要求苛刻的实时条件下的建模和控制应用。

As a new methodology of intelligent system, we have proposed an pattern information based active learning method (PBALM), which has a non-exact processing nature without complex computational formulas. The PBALM is formed on the basis of fuzzy concepts, striving for human-like information processing. Typical fuzzy rules. On the other hand, the PBALM features are ambiguous pattern processings. This simulates human brain nature in the modeling of processing information in pattern-like images rather than utilizing numerical interpretations, when humans acquire knowledge from complex targets.The PBALM has plural processing units called IDS's, which are tasked with extracting useful information from a system subject to modeling. In order to realize an PBALM system which is capable of performing complex, large scale modeling with an excellent fault tolerant architecture, dedicated hardware for IDS is indispensable. For the purpose of developing such an intelligent hardware system, we tentatively designed an IDS hardware unit using an evaluation board available on the market, and verified how effective it would be.Because we confirmed the effectiveness of dedicated IDS hardware with the evaluation board, we developed a new IDS processing unit called 'HIDS'. We designed a printed circuit board on which an IDS controller which ran at 100MHz, were mounted. In performance test results, in spite of the parallelization of only four HIDS boards, the performance of HIDS was far superior in the processing time in comparison to that of the software-based PBALM. By using HIDS units that we developed in this project, the PBALM system would be applied to modeling and control applications under demanding realtime conditions.