Andrzej Cichocki, Ph.D., Dr.Sc.
- Our goal is to develop novel technologies for analysis of massive data and processing in a real time brain signals
Advanced Brain Signal Processing
Senior Team Leader
Visiting Professor, Graduate School of Life Science and Systems Engineering, Kyushu Institute of Technology
Computational neuroscience, Dynamic tensor analysis, Brain/human computer interactions
The Andrzej Cichocki lab for Advanced Brain Signal Processing is focused on developing novel and state of the art methods to extract, detect, recognize, find functional connectivity, and classify brain signals and to gain the insights building intelligent feature extraction systems. Central research interest: * Multi-modal multi-sensory multidimensional brain data analysis , especially EEG/MEG, fMRI data (Human Perception: sound, vision, odors, taste, tactile), * Bio-inspired signal processing - Blind Sources Separation: (Sparse Component Analysis-SCA, Independent Component Analysis-ICA, Morphological Component Analysis -MCA, Nonnegative Matrix Factorization-NMF, Nonnegative Tensor Factorization-NTF, Time-Frequency Morohological Component Analyzer-TFCA), * Brain Computer Interface (BCI) / Human Computer Interaction (HCI). Development and investigation of models, architectures (structures) and associated learning algorithms of artificial neural systems. We develop novel reconstruction algorithms and implementations for bio-medical imaging applications that can greatly enhance our ability to monitor neuroimage structures and processes. The imaging systems of our interests include existing modalities such as EEG, fMRI, and NIRS as well as emerging technologies.
Architecture of the Amari-Hopfield discrete-time model of recurrent neural network with regularization used for a class of optimization problem and robust ICA.
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1
Vialatte FB, Maurice M, Dauwels J, and Cichocki A: "Steady-state visually evoked potentials: focus on essential paradigms and future perspectives.", Prog Neurobiol, 90(4), 418-38 (2010)
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2
Caiafa C, and Cichocki A: "Generalizing the Column-row Matrix Decomposition to Multi-way Arrays.", Linear Algebra and its Applications, 433(3), 557-573 (2010)
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3
Cichocki A, and Amari S: "Families of Alpha-Beta-and Gamma-Divergences: Flexible and Robust Measures of Similarities.", Entropy, 12, 1532-1568 (2010)
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4
Cichocki A, and Phan AH: "Fast Local Algorithms for Large Scale Nonnegative Matrix and Tensor Factorizations.", IEICE Trans. Fundamentals, (Invited paper) (2009)
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5
Cichocki A, Zdunek R, Phan AH, and Amari S: "Nonnegative Matrix and Tensor Factorization: In Aplications to Exploratory Multway Data Analysis", Monograph (477 pages) Joohn Wiley (2009)
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6
Cichocki A, Washizawa Y, Rutkowski T, Bakardjian H, Phan AH, Choi S, Lee H, Zhao Q, Zhang L, and Li Y: "Noninvasive BCIs: Multiway signal-processing array decompositions", IEEE Computer, 41(10), 34-42 (2008)
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7
Li Y, Amari S, Cichocki A, Ho DWC, and Xie S: "Underdetermined Blind Source Separation Based on Sparse Representatio", IEEE Transactions On Signal Processing, 54(2), 423-437 (2006)
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8
Cichocki A, Shishkin SL, Musha T, Leonowicz Z, Asada T, and Kurachi T: "EEG filtering based on blind source separation (BSS) for early detection of Alzheimer's disease.", Clin Neurophysiol, 116(3), 729-37 (2005)
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9
Li Y, Cichocki A, and Amari S: "Analysis of sparse representation and blind source separation.", Neural Comput, 16(6), 1193-234 (2004)
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10
Cichocki A, and Amari S: "Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications. (550 pages)", monograph Wiley (2003)
- May. 3, 2010 Gene database created for the hypothalamus, which regulates instinct and emotional action Tomomi Shimogori, Ph.D., Molecular Mechanisms of Thalamus Development
