Probabilistic model building methods can render difficult problems feasible by identifying and exploiting dependencies. They build a probabilistic model from the statistical prope...
We propose a Markov process model for spike-frequency adapting neural ensembles which synthesizes existing mean-adaptation approaches, population density methods, and inhomogeneou...
Eilif Mueller, Lars Buesing, Johannes Schemmel, Ka...
—For a long time, signal processing applications, and most particularly detection and parameter estimation methods, have relied on the limiting behaviour of test statistics and e...
Variants of Huffman codes where words are taken as the source symbols are currently the most attractive choices to compress natural language text databases. In particular, Tagged...
This paper describes the construction of second generation bandelet orthogonal bases. The decomposition on a bandelet basis is computed using a wavelet filter bank followed by ada...