The Probability Density Function (PDF) Introduction So far, you learned about discrete random variables and how to calculate or visualize their distribution functions. In this lesson, you'll learn ...

About Bayesian Inference for Vision: Calculation of the Posterior and the variance of the Posterior while manipulation the data and interpreting the results. Then visualizing the probability density ...

Nonparametric methods provide a flexible framework for estimating the probability density function of random variables without imposing a strict parametric model. By relying directly on observed ...

The dominant mode rejection (DMR) adaptive beamformer (ABF) is a reduced rank subspace algorithm, which replaces the covariance matrix in the Minimum Variance Distortionless Response (MVDR) beamformer ...

Incremental sampling can be applied in scientific imaging techniques whenever the measurements are taken incrementally, i.e., one pixel position is measured at a time. It can be used to reduce the ...

We propose a new bias-corrected spline-kernel estimator and a smooth simultaneous confidence band (SCB) as a global inference tool for the conditional variance function in a nonparametric regression ...