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Study of Bio-Simulation on Binary-Tree Multiprocessor

二叉树多处理器生物仿真研究

基本信息

批准号：
63580028
负责人：
TAKAHASHI Yoshizo
金额：
$ 1.15万
依托单位：
The University of Tokushima
依托单位国家：
日本
项目类别：
Grant-in-Aid for General Scientific Research (C)
财政年份：
1988
资助国家：
日本
起止时间：
1988 至 1990
项目状态：
已结题

项目摘要

(1) We have improved the parallel speech recognition system developed in 1989 by adding DSP (digital signal processor) to carry out computations for correlation and DP matching. With this improvement and, by removing redundant computations, We obtained more than 20 times increase in recognition speed. As it is necessary to increase the number of filter banks to attain higher recognition rate, the required computation time will be suppressed with this improvement.(2) We have implemented a hand-printed Kanji character recognition system based on biosimulation on our binary-tree multiprocessor Coral 68K and evaluated its performance. In this system a number of processors extract many different strokes from an input Kanji character and, by communicating each other, find the character that has the disposition of the strokes as described in their individual dictionary. In our experiment more than 90% of hand-written Knaji characters composed of less than five strokes were recognized successfully. This method will be applicable to the image recognition system.(3) The wire-routing problem is to connect all terminals in pair which are distributed on a plane with the wires which never intersect each other. When there are many terminals the computation time to find the paths of the wires becomes prohibitively large. As the wirerouting is a strongly sequential problem, the parallel processing of it has been considered very difficult. Therefore we have applied the bio-simulation to this problem and developed a new parallel processing scheme which we call parallel processing with competing processors. This algorithm is implemented on Coral 68K and a satisfactory performance was obtained.

(1)我们改进了1989年开发的并行语音识别系统，增加了DSP（数字信号处理器）来执行相关和DP匹配的计算。通过这种改进，并通过去除冗余计算，我们获得了超过20倍的识别速度的提高。由于需要增加滤波器组的数量以获得更高的识别率，因此所需的计算时间将被抑制。(2)我们已经实现了一个手写体汉字字符识别系统的生物模拟的基础上，我们的二叉树多处理器珊瑚68K，并评估其性能。在这个系统中，许多处理器从输入的汉字字符中提取许多不同的笔划，并通过相互通信，找到具有如在它们各自的字典中所描述的笔划配置的字符。在我们的实验中，超过90%的手写Knaji字符组成的少于五个笔画被成功地识别。该方法适用于图像识别系统。(3)布线问题是用互不相交的导线将平面上成对分布的所有端子连接起来。当有许多终端时，找到导线路径的计算时间变得非常大。由于布线问题是一个强序列问题，其并行处理一直被认为是非常困难的。因此，我们应用生物模拟这个问题，并开发了一个新的并行处理方案，我们称之为并行处理与竞争处理器。该算法在Coral 68K上实现，取得了令人满意的性能。