An article on Expectation Maximization Theory, taken from the book “Biometric Authentication: A Machine Learning Approach”.
The article/book-chapter addresses a data-clustering algorithm, called the expectation-maximization (EM) algorithm, when complete or partial information of observed data is made available.
The book is written by M.W. Mak, S.Y. Kung, S.H. Lin. and the sample chapter is provided courtesy of Prentice Hall PTR. / Jan 3, 2005.
Multiple electrodes are now a standard tool in neuroscience research that make it possible to study the simultaneous activity of several neurons in a given brain region or across different regions. The data from multi-electrode studies present important analysis challenges that must be resolved for optimal use of these neurophysiological measurements to answer questions about how the brain works.
The authors review statistical methods for the analysis of multiple neural spike-train data and discuss future challenges for methodology research.
Emery N Brown, Robert E Kass & Partha P Mitra
Nature Neuroscience 7, 456 – 461 (2004)
Published online: 27 April 2004; | doi:10.1038/nn1228
A nice article trying to give the reader an intuition what computer scientists can contribute to the question how the brain works.
Pulsed neural networks are networks of spiking neurons, which represent an entirely new class of artificial neurons. The paper presents an overview of pulsed neural networks, including the structure, function and available training mechanisms for networks of spiking neurons.
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IEEE Spectrum Biomedical
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