By Vasilis Z. Marmarelis (auth.), Vasilis Z. Marmarelis (eds.)
This quantity is the second one in a sequence of courses subsidized by means of the Biomedical Simulations source (BMSR) on the collage of Southern California that record on contemporary examine advancements within the quarter of physiological platforms modeling and anal ysis of physiological indications. As within the first quantity of this sequence, the paintings pronounced herein is anxious with the advance of complex methodologies and their novel program to difficulties of biomedical curiosity, with emphasis on nonlinear features of physiological functionality. The time period "advanced methodologies" is used to point that the scope of this paintings extends past the normal form of research utilized by such a lot investigators during this zone, that's limited basically within the linear area. because the im portance of nonlinearities in knowing the advanced mechanisms of physiological functionality is more and more famous, the necessity for powerful and functional methodolo gies that handle the problem of nonlinear dynamics in lifestyles sciences turns into progressively more urgent. The ebook of those volumes and the workshops, equipped via the BMSR at the similar topic, are key actions in our efforts to advertise and accentuate study during this quarter, foster interplay and collaboration between investigators, and disseminate contemporary effects through the biomedical community.
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Extra resources for Advanced Methods of Physiological System Modeling: Volume 2
25). , decreasing gain of the "equivalent linearized feedback"). The system response to pulses of increasing amplitude are shown in Fig. 25 and amplitudes A = 1,2 and 4. Note the progressive difference between on-set and off-set responses. In the case of the underdamped forward subsystem and sigmoid (negative) feedback the results are qualitatively similar to the previous case. The changes in the kernel waveform undergo a gradual transition from the linearized feedback system to the forward linear subsystem as the GWN input power level increases from very small to very large values.
EXACT 2ND-ORDER KERNEL OF QUADRATIC FEEDBACK SYSTEM (£=1) X-MIN= X-MAX= Fig. 51. 1432E+00 Exact second-order Wiener kernel of the system described in the caption of Fig. 48, as given by Eq. (50) for nominal values: e = 1, P = 1. 2ND-ORDER KERNEL OF X-MIN= X-MAX" Fig. 52. 0000 Z-MIN= -0. 001) with the overdamped forward of Fig. 5(P=1). 2ND-ORDER KERNEL OF CUBIC FEEDBACK SYSTEM FOR p=1 X-MINX-MAX= Fig. 53. 3596E-02 Z-MAX'" O. 2536E-03 Second-order Wiener kernel of system described in the caption of Fig.
0 100. TIME LAG Fig. 46. 25) with the band-pass forward of Fig. 45, for P = 1 (trace 1), 16 (trace 2),256 (trace 3) and 4096 (trace 4). 125 NORMALIZED FREQUENCY Fig. 47. 44 FFT magnitudes of the kernels shown in Fig. 46. We observe decreasing resonance frequency and gain as P increases, as well as broadening of the "tuning curve". 04) X-MIN= X-MAX- Fig. 48. 61BSE-02 Second-order Wiener kernel of negative quadratic feedback system with the underdamped forward shown in Fig. 04 and P = 1. OB) X-MINX-MAX" Fig.
Advanced Methods of Physiological System Modeling: Volume 2 by Vasilis Z. Marmarelis (auth.), Vasilis Z. Marmarelis (eds.)