Spike detection approaches for noisy neuronal data: Assessment and comparison

H Azami; S Sanei

doi:10.1016/j.neucom.2013.12.006

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Spike detection approaches for noisy neuronal data: Assessment and comparison

Journal article

Peer reviewed

Spike detection approaches for noisy neuronal data: Assessment and comparison

H Azami and S Sanei

NEUROCOMPUTING, Vol.133, pp.491-506

10/06/2014

DOI: https://doi.org/10.1016/j.neucom.2013.12.006

Abstract

Science & Technology

Technology

Computer Science

Artificial Intelligence

Computer Science

COMPUTER SCIENCE

ARTIFICIAL INTELLIGENCE

Spike detection

Fractal dimension

Smoothed nonlinear energy operator

Standard deviation

Empirical mode decomposition

Singular spectrum analysis

WAVELET

SIGNALS

FILTER

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Title: Spike detection approaches for noisy neuronal data: Assessment and comparison
Creators: H Azami
S Sanei
Publication Details: NEUROCOMPUTING, Vol.133, pp.491-506
Publisher: ELSEVIER SCIENCE BV
Date published: 10/06/2014
Date submitted: 17/05/2017
Identifiers: 99514391002346
Academic Unit: University of Surrey
Language: English
Resource Type: Journal article

Spike detection approaches for noisy neuronal data: Assessment and comparison

Abstract

Files and links (1)

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