Figure 1

An example perceptron circuit consisting of \(\pmb{N=4}\) programmable amplifiers for the coherent input vector \(\pmb{x = (x_{1}, x_{2}, x_{3}, x_{4})^{T}}\) , a static mixing element that sums their output, a quadrature filter to remove the imaginary quadrature and a final thresholding element to generate the estimated binary class label \(\pmb{\hat {y}}\) . The additional binary input T controls whether the system is in training mode, in which case the estimated class label \(\hat {y}\) is compared to the true class label Y which is provided as an additional input. When they differ, the programmable amplifiers receive a feedback signal to adjust their internal weights.