Redundant Data Elimination in Independent Component Analysis
MetadataShow full item record
Independent component analysis involves a lot of data in statistical calculations. This paper studies the model by examining which part of the data is essential and which part is redundant for defining the mixing system and proposes an idea called redundant data elimination. Statistical properties change in the direction of uniform distribution as redundant data are eliminated, yet the model still holds and the solution still exists. A theoretical explanation is given of the geometrical transformation of independent sources. The above reasoning is verified by separation experiment. It is shown that this idea can also improve model match for unsymmetrical sources.
Showing items related by title, author, creator and subject.
High performance communication redundancy in a digital substation based on IEC 62439-3 with a station bus configurationKumar, S.; Das, N.; Islam, Syed (2015)High speed communication is critical in a digital substation from protection, control and automation perspectives. Although International Electro-Technical Commission (IEC) 61850 standard has proven to be a reliable guide ...
Bettermann, Stephan (2013)Real-time Internet services are becoming more popular every day, and Voice over Internet Protocol (VOIP) is arguably the most popular of these, despite the quality and reliability problems that are so characteristic of ...
Using models of the ocean's mean dynamic topography to identify errors in coastal geodetic levellingFilmer, Michael (2014)Identifying errors (blunders and systematic errors) in coastal geodetic levelling networks has often been problematic. This is because (1) mean sea level (MSL) at tide gauges cannot be directly compared to height differences ...