The “bee-identification problem” was formally defined by Tandon, Tan and Varshney [IEEE Trans. Commun., vol. 67, 2019], and the error exponent was studied. This work extends the results for the “absentee bees” scenario, where a fraction of the bees are absent in the beehive image used for identification. For this setting, we present an exact characterization of the bee-identification error exponent, and show that independent barcode decoding is optimal, i.e., joint decoding of the bee barcodes does not result in a better error exponent relative to independent decoding of each noisy barcode. This is in contrast to the result without absentee bees, where joint barcode decoding results in a significantly higher error exponent than independent barcode decoding. We also define and characterize the ‘capacity’ for the bee-identification problem with absentee bees, and prove a strong converse for the same.

中文翻译：

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有缺勤蜜蜂的蜜蜂识别误差指数

“蜜蜂识别问题”由 Tandon、Tan 和 Varshney [IEEE Trans. 社区，卷。67, 2019]，并研究了误差指数。这项工作扩展了“缺席蜜蜂”场景的结果，其中用于识别的蜂巢图像中缺少一小部分蜜蜂。对于此设置，我们提供了蜜蜂识别错误指数的精确特征，并表明独立条码解码是最佳的，即蜜蜂条码的联合解码不会导致相对于每个嘈杂条码的独立解码更好的错误指数. 这与没有缺席蜜蜂的结果形成对比，其中联合条码解码导致比独立条码解码明显更高的错误指数。