The IM Algorithm: A Variational Approach to Information Maximization.

作者：David Barber, Felix Agakov · 发表于：UCL Discovery (University College London) · 年份：2003 · 被引用次数：290 · 研究领域：Blind Source Separation Techniques、Algorithms and Data Compression、Fractal and DNA sequence analysis

The maximisation of information transmission over noisy channels is a common, albeit generally computationally difficult problem. We approach the difficulty of computing the mutual information for noisy channels by using a variational approximation. The resulting IM algorithm is analagous to the EM algorithm, yet maximises mutual information, as opposed to likelihood. We apply the method to several practical examples, including linear compression, population encoding and CDMA.