Probability a posteriori. [I.]

Maximum a posteriori probability tree models

The context-tree weighting method (Willems, Shtarkov, and Tjalkens [1995]) can be used to compress sequences generated by tree sources. Its redundancy behavior is optimal in the sense that Rissanen’s lower bound [1984] is achieved. Here we study some questions related to the context-tree weighting method. First we stress again that the a priori distribution over all tree models that is mainly c...

A (simplified) Bluetooth Maximum a Posteriori Probability (map) Receiver

In our software-defined radio project we aim at combining two standards: Bluetooth and HiperLAN/2. The HiperLAN/2 receiver requires the most computation power in comparison with Bluetooth. We choose to use this computational power also for Bluetooth and look for more advanced demodulation algorithms such as a Maximum A posteriori Probability (MAP) receiver. This paper discusses a simplified MAP...

Ocean acoustic inversion with estimation of a posteriori probability distributions

Inversion methods are applied in ocean acoustics to infer parameters which characterize the environment. The objective of this paper is to provide such estimates, and means of evaluating the inherent uncertainty of the parameter estimates. In a Bayesian approach, the result of inversion is the a posteriori probability density for the estimated parameters, from which all information such as mean...

Idempotent Probability Measures, I

The set of all idempotent probability measures (Maslov measures) on a compact Hausdorff space endowed with the weak* topology determines is functorial on the category Comp of compact Hausdorff spaces. We prove that the obtained functor is normal in the sense of E. Shchepin. Also, this functor is the functorial part of a monad on Comp. We prove that the idempotent probability measure monad conta...

Measure-Theoretic Probability I