For the analysis of multiunit extracellular neural signals as multiple spike trains, neural spike sorting is essential. Existing algorithms for the spike sorting have been unsatisfactory when the signal-to-noise ratio (SNR) is low, especially for implementation of fully-automated systems. We present a novel method that shows satisfactory performance even under low SNR, and compare its performan...

An extension of the infomax algorithm of Bell and Sejnowski (1995) is presented that is able blindly to separate mixed signals with sub- and supergaussian source distributions. This was achieved by using a simple type of learning rule first derived by Girolami (1997) by choosing negentropy as a projection pursuit index. Parameterized probability distributions that have sub- and supergaussian re...

An extension of the infomax algorithm of Bell and Sejnowski (1995) is presented that is able to blindly separate mixed signals with suband super-Gaussian source distributions. This was achieved by using a simple type of learning rule rst derived by Girolami (1997) by choosing negentropy as a projection pursuit index. Parameterized probability distributions that have suband super-Gaussian regime...

The current theory for Independent Component Analysis (ICA) tries to model the observations as unknown linear combination or mixture of N independent components or sources S1(t), . . . , SN(t) whose distribution is also usually unknown. In the ICA problem one tries to recover all the N independent and non-Gaussian components from the only knowledge of the observations. In this paper, we address...

We present a method to separate and deconvolve sources which have been recorded in real environments. The use of noncausal FIR filters allows us to deal with nonminimum mixing systems. The learning rules can be derived from different viewpoints such as information maximization, maximum likelihood and negentropy which result in similar rules for the weight update. We transform the learning rule ...

This paper aims at obtaining universal laws and absolute lower bounds of feedback systems using information theory. The feedback system setup is that with causal plants and causal controllers. Three laws (entropy rate never decreases, generalized Bode integral, and absolute lower bound in variance minimization) are obtained, which are in entropy domain, frequency domain, and time domain, respec...

В статье рассматриваются проблемы изучения основных подходов к определению сущности информации, для чего анализируются основные работы выдающихся мыслителей, таких как Н. Винер, К. Шеннон и Г. Бейтсон, которые внесли значительный вклад в область теории информации. Проводится связь между информацией такими понятиями, энтропия, сложность негэнтропия. Рассмотрение этого материала предполагает выяв...

Brian Computer Interface (BCI) is a direct communication pathway between the brain and an external device. BCIs are often aimed at assisting, augmenting or repairing human cognitive or sensory-motor functions. EEG separation into target and non-target ones based on presence of P300 signal is of difficult task mainly due to their natural low signal to noise ratio. In this paper a new algorithm i...