Differentially Private Filtering for Stationary Stochastic Collective Signals
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This chapter builds on the two-stage architecture for differentially private filtering, and presents mechanisms with better performance than the zero-forcing equalization mechanism, for the situation where we have some knowledge about the statistics of the privacy-sensitive input signals, which moreover are assumed to be stationary. The mechanisms described use as second stage in the architecture a Wiener filter, and the performance of the overall mechanism is then optimized, following the general methodology outlined in Chap. 3.
- Boyd S et al (1994) Linear matrix inequalities in system and control theory. Studies in applied mathematics. SIAM, PhiladelphiaGoogle Scholar