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Volumn 52, Issue 3, 2004, Pages 399-400

An artificial neural network to detect eeg seizures [9]

Author keywords

[No Author keywords available]

Indexed keywords

PENICILLIN G;

EID: 7244219929     PISSN: 00283886     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Letter
Times cited : (6)

References (10)
  • 4
    • 0028784350 scopus 로고
    • A Neural network confirms that physical exercise reverses EEG changes in depressed rats
    • Sarbadhikari SN: A Neural network confirms that physical exercise reverses EEG changes in depressed rats. Med Eng Physics 1995;17:579-82.
    • (1995) Med. Eng. Physics , vol.17 , pp. 579-582
    • Sarbadhikari, S.N.1
  • 6
    • 0003591521 scopus 로고    scopus 로고
    • Fundamentals of artificial neural networks
    • New Delhi: Printice-Hall of India Private Limited
    • Hassoun HM: Fundamentals of artificial neural networks. New Delhi: Printice-Hall of India Private Limited 1998.
    • (1998)
    • Hassoun, H.M.1
  • 7
    • 0031239741 scopus 로고    scopus 로고
    • Diagnostic acceptability of FFT-based ECG data compression
    • Kulkarni PK, Kumar V, Verma HK: Diagnostic acceptability of FFT-based ECG data compression. J Med Eng Technol 1997;21:185-9.
    • (1997) J. Med. Eng. Technol. , vol.21 , pp. 185-189
    • Kulkarni, P.K.1    Kumar, V.2    Verma, H.K.3
  • 8
    • 0029278224 scopus 로고
    • A dynamic Fourier series for the compression of ECG using FFT and adaptive coefficient estimate
    • Al-Nashash HAM: A dynamic Fourier series for the compression of ECG using FFT and adaptive coefficient estimate. Med Eng Physics 1995;17:197-203.
    • (1995) Med. Eng. Physics , vol.17 , pp. 197-203
    • Al-Nashash, H.A.M.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.