An analog-digital merged neural circuit using pulse width modulation technique
This paper presents a neural circuit using PWM technique based on an analog-digital merged circuit architecture. Some new PWM circuit techniques are proposed. A bipolar-weighted summation circuit is described which attains 8-bit precision in SPICE simulation at 5V supply voltage by compensating parasitic capacitance effects. A high performance differential-type latch comparator which can discriminate 1 mV difference at 100 MHz in SPICE simulation is also described. Next, we present a prototype chip fabricated using a 0.6 mu m CMOS process. The measurement results demonstrate that the overall precision in the weighted summation and the sigmoidal transformation is 5 bits. A neural network has been constructed using the prototype chips, and the experimental results for realizing the XOR function have successfully verified the basic neural operation.
pwm neural networks lsi implementation pulse-width modulation