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Volumn 6, Issue 3, 2007, Pages 269-281

Sorting of neural spikes: When wavelet based methods outperform principal component analysis

Author keywords

Clustering; Neural spikes; Spike sorting; Wavelet analysis

Indexed keywords

ALGORITHM; CLUSTER ANALYSIS; COMPUTER SIMULATION; CONCEPTUAL FRAMEWORK; CONFERENCE PAPER; DATA BASE; ELECTROPHYSIOLOGY; HISTOGRAM; HUMAN; IMAGE PROCESSING; INTERMETHOD COMPARISON; KNOWLEDGE BASE; MATHEMATICAL COMPUTING; PRINCIPAL COMPONENT ANALYSIS; QUALITY CONTROL; SEPARATION TECHNIQUE; SPIKE WAVE;

EID: 34547650665     PISSN: 15677818     EISSN: None     Source Type: Journal    
DOI: 10.1007/s11047-006-9014-8     Document Type: Conference Paper
Times cited : (52)

References (12)
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  • 6
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    • A method for spike sorting and detection based on wavelet packets and Shannon's mutual information
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    • Hulata, E.1    Segev, R.2    Ben-Jacob, E.3
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    • Spike sorting based on discrete wavelet transform coefficients
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  • 9
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    • A review of methods for spike sorting: The detection and classification of neural action potentials
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  • 10
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    • Unsupervised spike detection and sorting with wavelets and superparamagnetic clustering
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  • 11
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    • Robust, automatic spike sorting using mixtures of multivariate t-distributions
    • Shoham S, Fellows MR, Normann RA (2003) Robust, automatic spike sorting using mixtures of multivariate t-distributions. Journal of Neuroscience Methods 127: 111-122
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.