Research Fabrication of Integrated Neural Computing Circuits

作为集成神经元网络研究的第一步，制作了一个ad转换器。通过构建集成神经网络的ad转换器，可以研究除突触的可塑性外，用于一般集成神经网络构建的各种基本问题。所设计的电路是一个由4个神经元和12个突触组成的4位系统。一个神经元包括2个CMOS晶体管，一个突触包括一对CMOS和一个nMOS。突触权重的值由门的几何形状（L/W）决定。电路有外部控制线，当工艺产生意外偏差时，可以修改特性。考虑到工艺中可能出现的各种困难，图案尺寸按4微米的规则进行设计。合成神经元的阈值特征符合预期的s型曲线。突触的输出与输入成正比，有一个小的偏移。通过改变通道掺杂的条件，可以消除这种偏移。Hopfield提出的具有对称突触的ad -转换器由于解被局部最小值所困，导致运行结果错误。发现了一种具有非对称突触的新型ad转换器。一种新的模数转换器正在制造中。

An AD-converter was fabricated as the first step of research for integrated neuron networks. By constructing an AD-converter of integrated neural network one can study various fundamental problems underlying for the fabrication of general integrated neural networks except for the plasticity of the synapses. The designed circuit was a 4-bit system composed of 4 neurons and 12 synapses. A neuron includes 2 paris of CMOS transistors, and a synapse includes a pair of CMOS and a nMOS. The value of a synapse weight is determined by the geometry of the gate, L/W. The circuit has outside control lines to modify the characteristics in case the processes create some unexpected deviation. The pattern size was designed by 4 micron rule considering the various possible difficulties in the processes. The fabricated neuron showed a threshold characteristics with a sigmoidal curve as expected. The output of the synapse was proportional to the input with a small off-set. The off-set would be removed by changing the condition of the channel doping. The AD-converter with symmetric synapses proposed by Hopfield was found to operate with wrong results as the solution was trapped by a local minimum. A new AD-converter with desymmetrized synapses was found to operate always correctly. Fabrication of a new AD-converter is under way.