The bias of Fisher information for large-n samples of dynamical curves is calculated, with clustering of degrees of freedom shown to reduce bias and improve reconstruction accuracy from the same data.
Least squares quantization in pcm,
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A general framework for multi-agent control that achieves decentralization without dynamical coupling and provides convergence guarantees for time-varying objectives, demonstrated on formation control, coverage, and safe navigation.
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Fisher Information and Dynamical Sampling I
The bias of Fisher information for large-n samples of dynamical curves is calculated, with clustering of degrees of freedom shown to reduce bias and improve reconstruction accuracy from the same data.
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Disentangled Control of Multi-Agent Systems
A general framework for multi-agent control that achieves decentralization without dynamical coupling and provides convergence guarantees for time-varying objectives, demonstrated on formation control, coverage, and safe navigation.