In this paper, we describe a novel algorithm, called Coherent In-dependent Components Analysis, and referred to as Coherent ICA for short. The algorithm, rooted in information-theoretic learn-ing, exploits the combined use of the Infomax and Imax princi-ples. Experimental results, based on the auditory coding of natural sounds, are presented that demonstrate the ability of coherent ICA to extract the envelope of amplitude-modulated sounds in a man-ner similar to the behaviour of neurons in the cochlear nucleus and inferior colliculus. 1
The high levels goals of this thesis are to: understand the neural representation of sound, produce ...
An extension of the infomax algorithm of Bell and Sejnowski (1995) is presented that is able blindly...
An extension of the infomax algorithm of Bell and Sejnowski (1995) is presented that is able blindly...
Unsupervised learning algorithms paying attention only to second-order statistics ignore the phase s...
Independent Component Analysis (ICA) is a signal-processing method to extract independent sources gi...
terry~salk.edu Because of the distance between the skull and brain and their differ-ent resistivitie...
Because of the distance between the skull and brain and their dier-ent resistivities, electroencepha...
Abstract. Based on general findings from the field of neuroscience and their algorithmic implementat...
Abstract — We apply a blind source separation approach to the identification of statistically indepe...
<p>A) An explanation of the ICA model. Each epoch of binaural sound (left hand side of the equation)...
Meinicke P, Hermann T, Bekel H, Müller HM, Weiss S, Ritter H. Identification of Discriminative Featu...
Distinguishing between the sounds in our environment is quite trivial for humans. We can easily dist...
Previously, modulations in power of neuronal oscillations have been functionally linked to sensory, ...
AbstractPreviously, modulations in power of neuronal oscillations have been functionally linked to s...
Independent component analysis (ICA) is a technique which extracts statistically independent compone...
The high levels goals of this thesis are to: understand the neural representation of sound, produce ...
An extension of the infomax algorithm of Bell and Sejnowski (1995) is presented that is able blindly...
An extension of the infomax algorithm of Bell and Sejnowski (1995) is presented that is able blindly...
Unsupervised learning algorithms paying attention only to second-order statistics ignore the phase s...
Independent Component Analysis (ICA) is a signal-processing method to extract independent sources gi...
terry~salk.edu Because of the distance between the skull and brain and their differ-ent resistivitie...
Because of the distance between the skull and brain and their dier-ent resistivities, electroencepha...
Abstract. Based on general findings from the field of neuroscience and their algorithmic implementat...
Abstract — We apply a blind source separation approach to the identification of statistically indepe...
<p>A) An explanation of the ICA model. Each epoch of binaural sound (left hand side of the equation)...
Meinicke P, Hermann T, Bekel H, Müller HM, Weiss S, Ritter H. Identification of Discriminative Featu...
Distinguishing between the sounds in our environment is quite trivial for humans. We can easily dist...
Previously, modulations in power of neuronal oscillations have been functionally linked to sensory, ...
AbstractPreviously, modulations in power of neuronal oscillations have been functionally linked to s...
Independent component analysis (ICA) is a technique which extracts statistically independent compone...
The high levels goals of this thesis are to: understand the neural representation of sound, produce ...
An extension of the infomax algorithm of Bell and Sejnowski (1995) is presented that is able blindly...
An extension of the infomax algorithm of Bell and Sejnowski (1995) is presented that is able blindly...