  Due to their simple construction, LFSRs are commonly used as building blocks
in various random number generators. Nonlinear feedforward logic is
incorporated in LFSRs to increase the linear complexity of the generated
sequence. In this work, we extend the idea of nonlinear feedforward logic to
LFSRs over arbitrary finite fields and analyze the statistical properties of
the generated sequences. Further, we propose a method of applying nonlinear
feedforward logic to word-based {\sigma}-LFSRs and show that the proposed
scheme generates vector sequences that are statistically more balanced than
those generated by an existing scheme.
