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| Japan | RIKEN | Brain Science Institute | Our Research Group | Amari Research Unit |
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 New
Monograph about NMF and Tensor Decompositions |
 A Book about
ICA
and BSS |
Email:
Address:
BSI RIKEN ABSP LabWako
351-0198
Fax: +81-48-467-9686
Laboratory Head
Dr. Andrzej Cichocki
The Cichocki Laboratory for
Advanced
Brain Signal Processing (ABSP) investigates and develops tools and
software for analysis, extraction, enhancement, de-noising detection,
localization, recognition and classification of brain signals and
patterns, especially measured by high density array EEG/MEG and ERP/EMG
systems.
| NEWS |
| One of our affective BCI project was nominated to the Annual BCI Research Award 2011 Our lab on CNN's Vital Signs, September'09 Our lab on France24's Health Technology, September'09 Our lab on CCTV9, August'09 Special Session at APSIPA ASC 2009 on "Advances in signal processing for data analysis and feature extraction" |
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| RIKEN BSI NEWS December 2006 [English] [Japanese] |
 RIKEN NEWS August 2005 [English] [Japanese] |
| ICALAB for Signal
Processing ver.
3.0 DOWNLOAD NMFLAB for Signal Processing ver 1.2 DOWNLOAD ICALAB for Image Processing ver. 2.0 DOWNLOAD NMFLAB for Image Processing ver. 1.2 DOWNLOAD NTFLAB for Signal Processing Beta version DOWNLOAD Guidebook of NMFLAB for signal processing [PDF] FAQ, Tips & Tricks for ICALAB |
| MLSP Benchmarks Competition |
We are interested in intelligent biomedical signal processing and nonlinear system theory approaches in computational neuroscience, with an emphasis on neural network models with underlying components (processing units) and biologically plausible learning algorithms.
In order to understand the higher order functioning of the brain, it is necessary to develop new methods of signal processing for brain data. On the other hand, the brain itself performs excellent information processing, by using diversified representations of information.
Our second goal is to elucidate brain signal processing through its modeling and engineering applications. We analyze models of biologically plausible neural networks with adaptive learning rules in order to understand brain information processing in the visual, auditory, olfactory and somatosensory systems. To this end, we implement engineering designs of brain-style pattern recognition, classification and cognitive systems.
Main Tasks and Applications
- Development of advanced methods for brain data analysis and processing.
- Development of generalized component analysis (ICA, SCA, NMF, SPCA) and blind source separation (BSS).
- Semi-blind extraction and analysis of ERP transient signals.
- Statistical analysis of multi-electrode signals- especially analysis of brain signals from EEG/MEG recording.
- Developments of neural network models and their engineering applications.
- Auditory signal processing and speech enhancement.
©1997-2009
Laboratory for Advanced Brain Signal Processing