Analog electronic neural network circuits
Analog electronic neural network circuits
复制标题
模拟电子神经网络电路
DOI：
10.1109/101.29902
复制
发表时间：
1989
期刊：
影响因子：
--
通讯作者：
L. Jackel
中科院分区：
文献类型：
--
作者：
H. Graf;L. Jackel
有人认为，神经网络模型中所需的大互连性和精度为模拟计算提供了新的机会。模拟电路的各种各样的问题，如模式匹配，优化和学习已被提出，并已建成一些。到目前为止，大多数电路都是相对较小的探索性设计。电路实现几种不同的神经算法，即模板匹配，联想记忆，学习和二维电阻网络的视网膜的架构的启发进行了讨论。最成熟的电路是用于模板匹配的电路，执行这一功能的芯片现在正被应用于模式识别问题。模拟实现的例子进行了检查。<<ETX>>
It is argued that the large interconnectivity and the precision required in neural network models present novel opportunities for analog computing. Analog circuits for a wide variety of problems such as pattern matching, optimization, and learning have been proposed and a few have been built. Most of the circuits built so far are relatively small, exploratory designs. Circuits implementing several different neural algorithms, namely, template matching, associative memory, learning, and two-dimensional resistor networks inspired by the architecture of the retina are discussed. The most mature circuits are those for template matching, and chips performing this function are now being applied to pattern-recognition problems. Examples of analog implementation are examined.<<ETX>>