基于FPGA数学技术的ai -模糊VCN自动化算法

Tingfang Zhang, Qiusun Ye
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引用次数: 3

摘要

现场可编程门阵列(FPGA)是20世纪末出现的一种新型材料可编程逻辑单元,具有存储容量大、时间延迟短、可改进性和灵活性等特点。在神经模糊网络系统(NFSN)理论的基础上,提出了一种基于可变承载数的动态数字测量算法(DNMA)的FPGA实现方法。该算法采用了VCR (Variable Carrying Rules)路径复用技术,即中间数据的成形和存储过程。经过对测试的深入研究和分析,该算法是切实可行的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Novel FPGA Mathematical Technology Based AI-Fuzzy VCN Algorithm of Automation
Field Programmable Gate Array (FPGA) was a new material Programmable Logic Units in end of the 20th century, FPGA was with some properties such that, large memory of capacities, short delays of time, improvement able & flexibilities etc. On the basis theory of Neural Fuzzy System of Networks (NFSN), this paper gives a FPGA method of DNMA (Dynamic Numbers Measuring Algorithm) with VCN (Variable Carrying Numbers). The algorithm takes a reusing technique of VCR (Variable Carrying Rules) path, a process of middle-data to be shaped & placed in RAM. In the deep research & analysis of testing, this algorithm is practicable.
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