On the Observability and Controllability of Leaky-ReLU Networks
Liangjie Sun, Wai-Ki Ching, Shun-ichi Azuma, Tatsuya Akutsu
Abstract
This paper studies minimum-node observability and controllability of Leaky rectified linear unit (Leaky-ReLU) networks under degree constraints. The objective is to characterize how many state nodes must be measured or directly actuated to determine the initial state from a finite output sequence or to steer the network between arbitrary states within a finite horizon. For observability, a graph-theoretic analysis yields a class-wide upper bound on the minimum number of observation nodes. We construct a family of networks attaining this bound, thereby determining the exact worst-case minimum number of observation nodes. We also construct networks that are observable from a single node over a finite horizon, establishing the exact best-case value of one. By establishing an observability--controllability duality under the corresponding degree constraints, we obtain analogous exact best- and worst-case results for the minimum number of control nodes. A comparison with ReLU networks shows how replacing the zero negative slope with a nonzero slope changes the observation-node requirement. More generally, the observability arguments require only injectivity of the activation function, whereas the controllability results extend to bijective activation functions.
Create a lesson
Related papers
Leader-Follower Formation Control with Prescribed Convergence Rates under Bearing Persistence of Excitation
Tarek Bouazza, Zhiqi Tang, Soulaimane Berkane et al.
On asymptotic stability of the time-varying Kalman filter for unstabilizable linear systems: an optimization perspective
James B. Rawlings, Titus Quah, Matthias A. Müller
Designing Grid-Aware Dynamic Specifications for Large Data Center Loads
Ashutossh Gupta, Vassilis Kekatos
Time-Optimal Operation of a Load-Hoisting Gantry Crane
Eric Mountain, Tarunraj Singh
Learning to Solve Two-Stage Stochastic Unit Commitment Problems with Quality Guarantees
Andrea Fusco, Andrea Lodi, Lavanya Marla
Towards Interaction Regulation from Human Feedback via Free Energy Minimization
Maria Paula Diaz Monfort, Cinzia Tomaselli, Michael Richardson et al.