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20192021
most citedIndependent Gaussian Distributions Minimize the Kullback-Leibler (KL) Divergence from Independent Gaussian Distributions

8 citations · 14 across the 7 of their papers we have counts for

collaborators

11 papers

cs.IT20212 cited

Feedback Capacity of Parallel ACGN Channels and Kalman Filter: Power Allocation with Feedback

Song Fang, Quanyan Zhu

In this paper, we relate the feedback capacity of parallel additive colored Gaussian noise (ACGN) channels to a variant of the Kalman filter. By doing so, we obtain lower bounds on…

eess.SY20211 cited

Relativistic Rocket Control (Relativistic Space-Travel Flight Control): Feedback Control of Relativistic Dynamics Propelled by Ejecting Mass

Song Fang, Quanyan Zhu

In this short note, we investigate the feedback control of relativistic dynamics propelled by mass ejection, modeling, e.g., the relativistic rocket control or the relativistic (sp…

math.ST2021

The Spectral-Domain Wasserstein Distance for Elliptical Processes and the Spectral-Domain Gelbrich Bound

Song Fang, Quanyan Zhu

In this short note, we introduce the spectral-domain Wasserstein distance for elliptical stochastic processes in terms of their power spectra. We also introduce the…

math.ST2020

Independent Elliptical Distributions Minimize Their Wasserstein Distance from Independent Elliptical Distributions with the Same Density Generator

Song Fang, Quanyan Zhu

This short note is on a property of the Wasserstein distance which indicates that independent elliptical distributions minimize their Wasserstein di…

cs.IT20208 cited

Independent Gaussian Distributions Minimize the Kullback-Leibler (KL) Divergence from Independent Gaussian Distributions

Song Fang, Quanyan Zhu

This short note is on a property of the Kullback-Leibler (KL) divergence which indicates that independent Gaussian distributions minimize the KL divergence from given independent G…

eess.SY2020

Fundamental Limits of Controlled Stochastic Dynamical Systems: An Information-Theoretic Approach

Song Fang, Quanyan Zhu

In this paper, we examine the fundamental performance limitations in the control of stochastic dynamical systems; more specifically, we derive generic bounds that h…