Advances in Independent Component Analysis and Learning Machines

In honour of Professor Erkki Oja, one of the pioneers of Independent Component Analysis (ICA), this book reviews key advances in the theory and application of ICA, as well as its influence on signal processing, pattern recognition, machine learning, and data mining.Examples of topics which have developed from the advances of ICA, which are covered in the book are:A unifying probabilistic model for PCA and ICAOptimization methods for matrix decompositions Insights into the Fast ICA algorithm Unsupervised deep learning Machine vision and image retrieval A review of developments in the theory and applications of independent component analysis, and its influence in important areas such as statistical signal processing, pattern recognition and deep learning.A diverse set of application fields, ranging from machine vision to science policy data.Contributions from leading researchers in the field.Advances in Independent Component Analysis and Learning Machines is written by Bingham, Ella; Kaski, Samuel; Laaksonen, Jorma; Lampinen, Jouko and published by Academic Press.ISBNs for Advances in Independent Component Analysis and Learning Machines are 9780128028063, 9780128028070, 0128028076 and the print ISBNs are 9780128028063, 0128028068.