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Identifying the structure in cuttlefish visual signals

机译:识别墨鱼视觉信号中的结构

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The common cuttlefish (Sepia officinalis) communicates and camouflages itself by changing its skin colour and texture. Hanlon and Messenger (1988 Phil. Trans. R. Soc. Lond. B 320, 437-487) classified these visual displays, recognizing 13 distinct body patterns. Although this conclusion is based on extensive observations, a quantitative method for analysing complex patterning has obvious advantages. We formally define a body pattern in terms of the probabilities that various skin features are expressed, and use Bayesian statistical methods to estimate the number of distinct body patterns and their visual characteristics. For the dataset of cuttlefish coloration patterns recorded in our laboratory, this statistical method identifies 12-14 different patterns, a number consistent with the 13 found by Hanlon and Messenger. If used for signalling these would give a channel capacity of 3.4 bits per pattern. Bayesian generative models might be useful for objectively describing the structure in other complex biological signalling systems. [References: 25]
机译:普通乌贼(Sepia officinalis)会通过改变其肤色和质地来进行交流和伪装。 Hanlon和Messenger(1988 Phil。Trans。R. Soc。Lond。B 320,437-487)对这些视觉显示进行了分类,识别出13种不同的身体模式。尽管此结论基于广泛的观察,但是用于分析复杂图案的定量方法具有明显的优势。我们根据表达各种皮肤特征的概率来正式定义一种身体形态,并使用贝叶斯统计方法来估计不同的身体形态及其视觉特征的数量。对于我们实验室记录的墨鱼着色模式数据集,这种统计方法可识别12-14种不同的模式,这一数字与Hanlon和Messenger所发现的13种一致。如果用于信令,则每个模式将提供3.4位的信道容量。贝叶斯生成模型可能有助于客观描述其他复杂生物信号系统中的结构。 [参考:25]

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