尖端神经膜系统具有适应性突触时间延迟
Yongshun Shen1, Xuefu Liu1, Zhen Yang1
1College of Business, Shandong Normal University, Jinan 250014, P. R. China.
International journal of neural systems
|May 6, 2024
概括
尖端神经P系统 (SNP系统) 通过结合星球细胞,增强了自适应性突触时间延迟 (ADSNP系统). 这个模型更好地模拟了生物神经网络,并证明了图灵对计算的普遍性.
科学领域:
- 计算神经科学是一种计算神经科学.
- 理论计算机科学理论计算机科学
- 生物启发的计算是生物启发的
背景情况:
- 尖端神经P系统 (SNP系统) 是以并行性和时间编码而闻名的计算模型.
- 最初的SNP系统没有考虑突触传输延迟,限制了它们的生物现实性.
- 适应性调节突触延迟对于神经系统中准确的时间编码至关重要.
研究的目的:
- 提出和研究具有适应性突触时间延迟 (ADSNP系统) 的尖端神经膜系统.
- 通过结合天体细胞介导的适应性突触延迟来增强计算模型.
- 证明ADSNP系统的图灵通用性和实际可行性.
主要方法:
- 将能够产生腺三酸盐 (ATP) 的星球细胞引入SNP系统框架.
- 天体细胞将接收到的尖峰转化为ATP,调节突触时间延迟.
- 数学证明数字生成和接受模式中的图灵普遍性.
主要成果:
- ADSNP系统的图灵通用性已经被正式证明.
- 构建了一个具有93个神经元和星球细胞的小型通用ADSNP系统.
- ADSNP系统在六种现有变体上表现出优势.
- 成功实施了一种用于检测信用卡欺诈的实际应用.
结论:
- 通过包括自适应性突触延迟,ADSNP系统提供了一个更具生物学可信性的神经信息处理模型.
- 改进后的模型提高了神经P系统的适应性和时间控制.
- ADSNP系统可用于现实世界的应用,例如欺诈检测.
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