pac-man condition
Gradient Descent Learns Linear Dynamical Systems
A linear dynamical system (A,B,C,D) is equivalent to the system (TAT {-1}, TB, CT {-1}, D) for any invertible matrix T in terms of the behavior of the outputs. A little thought shows therefore that in its unrestricted parameterization the objective function cannot have a unique optimum. A common way of removing this redundancy is to impose a canonical form.
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