![]() ![]() Identifying multiple parameters using full-boundary measurements but also Worth emphasizing that this technique is not only applicable for uniquely Measurement constraint by adjusting the positive input at the boundary. Linearizing around a pair of zero solutions and fulfilling the probability The inverse problem related to the MFG system. ![]() Problems, we present an enhanced higher-order linearization method to tackle The limited information available from partial boundary measurements addsĪnother layer of complexity to the problem. Probability measure constraint of the coupled equations to consider. Parameters poses a significant implementation challenge. ![]() Secondly, the simultaneous recovery of multiple Firstly, it involves a coupling of two nonlinear elliptic partialĭifferential equations. Study features several technical novelties that make it highly intriguing andĬhallenging. K$ and cost function $F$ in a stationary mean field game (MFG) system. Download a PDF of the paper titled Determining a stationary mean field game system from full/partial boundary measurement, by Ming-Hui Ding and 2 other authors Download PDF Abstract: In this paper, we propose and study the utilization of theĭirichlet-to-Neumann (DN) map to uniquely identify the discount functions $r, ![]()
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