Abstract:
Provided is a method of optimizing parameter intervals of manufacturing processes based on prediction intervals. The method includes: collecting process data by applying an experiment design method to a target process; training a second-order polynomial regression model based on the collected process data; estimating importance values of each input variable with respect to each output variable using the second-order polynomial regression model; defining an objective function for process optimization based on the second-order polynomial regression model; optimizing each parameter value by applying an optimization algorithm to the defined objective function; and optimizing each parameter interval including the optimized parameter value in an input space using the prediction interval of the second-order polynomial regression model.
Abstract:
A direct conversion receiver includes: a high linearity mixer device including a sampler unit charge-sampling an input current according to a sampling frequency, and a buffer unit receiving an output signal from the sampler unit while having a low input impedance, amplifying the received signal, and outputting a current signal; and a filter device decimating an output signal from the mixer device and FIR-filtering the decimated signal.