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Foliage echoes: A probe into the ecological acoustics of bat echolocation

机译:叶子回声:蝙蝠回声定位的生态声学探究

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The research reported here aims at understanding the biosonar system of bats based on the properties of its natural inputs (ecological acoustics). Echoes from foliages are studied as examples of ubiquitous, natural targets. The echo properties and their qualitative relationship to plant architecture are described. The echoes were found to be profoundly stochastic and in general neither Gaussian nor stationary. Consequently, features useful for discrimination of such target classes will be confined to estimated random process parameters. Several such statistical signal features which are sufficiently invariant to allow a classification of the used example plants were identified: the characteristic exponent and the dispersion of an α-stable model for the amplitude distribution, a crest factor defined as the ratio of maximum squared amplitude and signal energy, the dispersion of the first threshold passage distribution, the structure of the correlation matrix, and a nonstationarity in sound channel gain. Discrimination error probability could be reduced by combining features pairwise. The best combination was the crest factor and the correlation coefficient of a log-linear model of the time-variant sound channel gain; it yielded an estimated Bayes risk of 6.9% for data pooled from different views.
机译:此处报道的研究旨在基于蝙蝠的生物声纳系统的自然输入(生态声学)特性来对其进行理解。以树叶的回声为例,研究了无处不在的自然目标。描述了回波特性及其与植物结构的定性关系。发现这些回波是高度随机的,并且通常既不是高斯也不是平稳的。因此,可用于区分此类目标类别的功能将仅限于估计的随机过程参数。确定了几个这样的统计信号特征,这些特征足够不变以允许对所使用的示例植物进行分类:振幅分布的α稳定模型的特征指数和离散度,定义为最大平方振幅比的波峰因数和信号能量,第一阈值通道分布的离散度,相关矩阵的结构以及声通道增益的不平稳性。可以通过成对组合特征来降低识别错误的概率。最佳组合是时变声通道增益的对数线性模型的波峰因数和相关系数。对于从不同角度汇总的数据,估计贝叶斯风险为6.9%。

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