Thumbnail
Access Restriction
Open

Author Szabó, Zoltán
Source CiteSeerX
Content type Text
File Format PDF
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Non-combinatorial Iterative Independent Process Analysis ♦ Independent Process Analysis ♦ Novel Decomposition Technique ♦ Independent Subspace Analysis ♦ Mixed Hidden Independent Autoregressive Process ♦ Iterative Scheme ♦ Ipa Task ♦ Separation Theorem ♦ Independent Component Analysis ♦ Identi Cation ♦ Computer Simulation ♦ Combinatorial Explosion ♦ Neural Network Implementation ♦ Reduction Method ♦ Neural Network Representation ♦ Certain Condition
Abstract It has been shown recently that the identi cation of mixed hidden independent autoregressive processes (Independent Process Analysis, IPA), under certain conditions, can be free from combinatorial explosion. The key is that IPA can be reduced (i) to Independent Subspace Analysis and then, via a novel decomposition technique called Separation Theorem, (ii) to Independent Component Analysis. Here, we introduce an iterative scheme and its neural network representation that takes advantage of the reduction method and can accomplish the IPA task. Computer simulation illustrates the working of the algorithm. Key words: independent process analysis, neural network implementation 1
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study