This thesis describes the implementation of an ELINT algorithm for the detection and classification of Low Probability of Intercept (LPI) signals. The algorithm was coded in the C programming language and executed on a Field Programmable Gate Array based reconfigurable computer; the SRC-6 manufactured by SRC Computers, Inc. Specifically, this thesis focuses on the preprocessing stage of an LPI signal processing algorithm. This stage receives a detected signal that has been run through a Quadrature Mirror Filter Bank and outputs the preprocessed signal for classification by a neural network. A major value of this study comes from comparing the performance of the reconfigurable computer to that of supercomputers and embedded systems that are currently used to solve the signal processing needs of the United States Navy.