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A drawback of the naive implementation of Monte Carlo localization occurs in a scenario where a robot sits at one spot and repeatedly senses the environment without moving. [4] Suppose that the particles all converge towards an erroneous state, or if an occult hand picks up the robot and moves it to a new location after particles have already ...
Monte Carlo simulation: Drawing a large number of pseudo-random uniform variables from the interval [0,1] at one time, or once at many different times, and assigning values less than or equal to 0.50 as heads and greater than 0.50 as tails, is a Monte Carlo simulation of the behavior of repeatedly tossing a coin.
In variational Bayesian methods, the evidence lower bound (often abbreviated ELBO, also sometimes called the variational lower bound [1] or negative variational free energy) is a useful lower bound on the log-likelihood of some observed data.
Data mining is the process of extracting and finding patterns in massive data sets involving methods at the intersection of machine learning, statistics, ...
Toggle Monte Carlo localization subsection. 1.1 Comments by Garamond Lethe. 1.1.1 First Impressions. 1.1.2 Lead. 1.1.3 History and Context. 1.1.4 State representation.
If a further piece of data, =, subsequently comes in, the probability distribution for x can be updated further, to give a new best guess (,,). If one reinvestigates the information gain for using p ( x ∣ y 1 , I ) {\displaystyle p(x\mid y_{1},I)} rather than p ( x ∣ I ) {\displaystyle p(x\mid I)} , it turns out that it may be either ...
The ensemble Kalman filter (EnKF) is a Monte Carlo implementation of the Bayesian update problem: given a probability density function (PDF) of the state of the modeled system (the prior, called often the forecast in geosciences) and the data likelihood, Bayes' theorem is used to obtain the PDF after the data likelihood has been taken into account (the posterior, often called the analysis).
An estimation, under Monte Carlo integration, of an integral defined as = / is = / where are uniformly obtained from all the phase space (PS) and N is the number of sampling points (or function evaluations).