Automated extraction of dolphin whistles—A sequential Monte Carlo probability hypothesis density approach
نویسندگان
چکیده
منابع مشابه
Automated tracking of dolphin whistles using Gaussian mixture probability hypothesis density filters.
This work considers automated multi target tracking of odontocete whistle contours. An adaptation of the Gaussian mixture probability hypothesis density (GM-PHD) filter is described and applied to the acoustic recordings from six odontocete species. From the raw data, spectral peaks are first identified and then the GM-PHD filter is used to simultaneously track the whistles' frequency contours....
متن کاملOn Using Truncated Sequential Probability Ratio Test Boundaries for Monte Carlo Implementation of Hypothesis Tests.
When designing programs or software for the implementation of Monte Carlo (MC) hypothesis tests, we can save computation time by using sequential stopping boundaries. Such boundaries imply stopping resampling after relatively few replications if the early replications indicate a very large or very small p-value. We study a truncated sequential probability ratio test (SPRT) boundary and provide ...
متن کاملTowards Automated Sequential Monte Carlo for Probabilistic Graphical Models
We revisit the idea of using sequential Monte Carlo (SMC) for inference in general probabilistic graphical models. By constructing a sequence of auxiliary target distributions (also known as a sequential decomposition) based on the graph structure we can run a standard SMC sampler on the graph. In this paper we study the impact of the sequential decomposition on the accuracy of the SMC method b...
متن کاملSequential Monte Carlo Samplers
In this paper, we propose a methodology to sample sequentially from a sequence of probability distributions known up to a normalizing constant and defined on a common space. These probability distributions are approximated by a cloud of weighted random samples which are propagated over time using Sequential Monte Carlo methods. This methodology allows us to derive simple algorithms to make para...
متن کاملSequential Monte Carlo Bandits
In this paper we propose a flexible and efficient framework for handling multi-armed bandits, combining sequential Monte Carlo algorithms with hierarchical Bayesian modeling techniques. The framework naturally encompasses restless bandits, contextual bandits, and other bandit variants under a single inferential model. Despite the model’s generality, we propose efficient Monte Carlo algorithms t...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: The Journal of the Acoustical Society of America
سال: 2020
ISSN: 0001-4966
DOI: 10.1121/10.0002257