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US08463291B2 KL-divergence kernel regression for non-gaussian fingerprint based localization 有权
基于非高斯指纹定位的KL-散度核回归

KL-divergence kernel regression for non-gaussian fingerprint based localization
Abstract:
Embodiments are directed to mobile localization, and more specifically, but not exclusively, to tracking mobile devices. Embodiments include methods that consider probability kernels with distance-like metrics between distributions. Also described are probabilistic kernels that can be used for a regression of location, which can achieve up to about inn accuracy in an office environment.
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