Advances in Independent Component Analysis and Learning Machines eBook
$100.00
By: Bingham, Ella; Kaski, Samuel; Laaksonen, Jorma; Lampinen, Jouko
Publisher: Academic Press
Print ISBN: 9780128028063, 0128028068
eText ISBN: 9780128028063, 9780128028070, 0128028076
Pages: 328
Delivery: Can be download immediately after purchasing. For new customer, we need process for verification from 30 mins to 12 hours.
Version: PDF/EPUB. If you need EPUB and MOBI Version, please send contact us.
Compatible Devices: Can be read on any devices
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 ICA
- Optimization methods for matrix decompositions
- Insights into the FastICA 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. The Digital and eTextbook ISBNs for Advances in Independent Component Analysis and Learning Machines are 9780128028063, 9780128028070, 0128028076 and the print ISBNs are 9780128028063, 0128028068. Save up to 80% versus print by going digital with VitalSource.
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