메뉴 건너뛰기




Volumn 60, Issue 4, 1999, Pages 4637-4644

Mechanism of stochastic resonance enhancement in neuronal models driven by [formula presented] noise

Author keywords

[No Author keywords available]

Indexed keywords

ANIMAL; BIOPHYSICS; METABOLISM; NERVE CELL; PHYSIOLOGY; STATISTICAL MODEL; STATISTICS; THEORETICAL MODEL;

EID: 0033215676     PISSN: 1063651X     EISSN: None     Source Type: Journal    
DOI: 10.1103/PhysRevE.60.4637     Document Type: Article
Times cited : (66)

References (51)
  • 45
    • 85036182041 scopus 로고    scopus 로고
    • this study, we used Gaussian (Formula presented) noise (Formula presented) with zero mean and upper and lower limits on the frequency range. The (Formula presented) noise was generated by the spectrum-based method described in Ref. 13
    • In this study, we used Gaussian (Formula presented) noise (Formula presented) with zero mean and upper and lower limits on the frequency range. The (Formula presented) noise was generated by the spectrum-based method described in Ref. 13.
  • 46
    • 85036296734 scopus 로고    scopus 로고
    • We used the fourth-order Runge-Kutta method for digital simulation (time step of 0.002 s; total time, 32.768 s). The impulse trains were convolved by a symmetric Hanning window (width = 6 s) to estimate (Formula presented), where the brackets (Formula presented) denote the ensemble average. The signal (Formula presented) was formed by convolving Gaussian white noise with the same window function
    • We used the fourth-order Runge-Kutta method for digital simulation (time step of 0.002 s; total time, 32.768 s). The impulse trains were convolved by a symmetric Hanning window (width = 6 s) to estimate (Formula presented), where the brackets (Formula presented) denote the ensemble average. The signal (Formula presented) was formed by convolving Gaussian white noise with the same window function.


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.