Neural implementation of cascaded INA for Yokto level signal processing

Instrumentation amplifier (INA) is a circuit which is used to amplify small signal in a noisy environment. It not only allow us to to amplify very small signals of sensor but also to add or subtract offset voltages and to electrically isolate (buffer) sensors from rest of the system. The analysis is based largely on ideal amplifiers. Here, we present the amplification of Yokto level signal (10^-24) to the saturation level of op-amp with the help of cascaded structure of INA. This structure of cascaded INA with order five, amplifies the signal level upto 490 dB at normal condition of components. At the critical values of all the components, the gain will be approximately 630 dB. Further, we implement INA on Artificial Neural Network for extracting the best performance, utilizing the most from avalable resources. The goal is met at 65 epoches i.e, mse of 10^-3.