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In order to solve the problems of signal modulation recognition in non-cooperative communication, this paper proposes a modulation type recognition algorithm based on instantaneous difference by neural network. Firstly, the method uses the structural difference of modulation parameters in time domain of modulation signal, and displays the difference in the form of image, so as to transform the modulation recognition problem into image recognition problem; secondly, it uses the advantage of convolution neural network to automatically extract features, and it classify different modulation signals; finally, a hierarchical neural network structure is formed to identify the unknown modulation signals.

A novel 8T single-event-upset (SEU) hardened and high static noise margin (SNM) SRAM cell is proposed. By adding one transistor paralleled with each access transistor, the drive capability of pull-up PMOS is greater than that of the conventional cell and the read access transistors are weaker than that of the conventional cell. So the hold, read SNM and critical charge increase greatly. The simulation results show that the critical charge is almost three times larger than that of the conventional 6T cell by appropriately sizing the pull-up transistors. The hold and read SNM of the new cell increase by 72% and 141.7%, respectively, compared to the 6T design, but it has a 54% area overhead and read performance penalty. According to these features, this novel cell suits high reliability applications, such as aerospace and military.