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Titlebook: Biomathematics and Related Computational Problems; Luigi M. Ricciardi Book 1988 Kluwer Academic Publishers 1988 Vibration.artificial intel

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期刊全稱Biomathematics and Related Computational Problems
影響因子2023Luigi M. Ricciardi
視頻videohttp://file.papertrans.cn/188/187904/187904.mp4
圖書封面Titlebook: Biomathematics and Related Computational Problems;  Luigi M. Ricciardi Book 1988 Kluwer Academic Publishers 1988 Vibration.artificial intel
影響因子Biomathematics emerged and rapidly grew as an independent discipline in the late sixties as scientists with various backgrounds in the mathematical, biological and physical sciences gathered together to form Departments and Institutes centered around this discipline that many at that time felt should fall between the cracks of legitimate science. For various reasons some of these new institutions vanished in the mid-seventies, particularly in the U. S. , the main reason for their demise being economic. Nevertheless, good biomathematical so that the range research has been ceaselessly carried on by numerous workers worldwide of this activity appears now as truly impressive: from useful and effective mathematical statements about problems that are firmly rooted in the ‘wet‘ reality of biology to deep theoretical investigations on outstanding basic questions. It is also interesting to take note that some ideas and theories set forth by ‘paleo-biomathematicians‘ almost a quarter of century ago are now becoming highly appreciated also by scientists engaged in quite different research fields. For instance, neural nets is the hot topic in computer science these days! Well aware of the gro
Pindex Book 1988
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A Birth-and-Death Model for Single Neuron’s ActivityFollowing Giorno .. (1987), a stochastic model for single neuron’s activity, constructed as the continuous limit of a birth-and-death process in the presence of a reversal hyperpolarization potential, is discussed with a view to obtain analytic and computational solutions to the firing time problem.
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Grundlagen des Konzernabschlusses,. In order to understand its information processing mechanism, it is necessary to study the properties of the dynamics of neural excitation patterns and of the dynamics of self-organization or learning. Mathematical methods are presented here for analyzing neurodynamics both in local and distributed
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https://doi.org/10.1007/978-3-322-94463-4ated in real nervous systems. A preparation that allows direct visualisation of space-time patterns generated by part of an invertebrate nervous system is described. An open question is how to classify and quantify these space-time patterns, to compare the behaviour of different models, and ultimate
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https://doi.org/10.1007/978-3-663-02635-8 models are focused mainly on the first passage time problem which is the theoretical equivalent of interspike distribution analysis. At the same time a statistical comparison of the models with experimental data is still an open question. Recently introduced diffusion model with restricted state sp
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