X-Message-Number: 25983 From: Date: Tue, 5 Apr 2005 15:31:41 EDT Subject: Uploading technology (2.iV.0). Uploading technology (2.iV.0). In 2.ii.0 I have said that very nonlinear systems could be simulated at 3 levels: Boolean, differential an stochastic. The best prospect being something between differential and stochastic, namely the omega Taylor serie from van Kampen. A first project would cut the taylor expansion at the first order. There are similarly a number of intermediate state between boolean and differential. The first "post-boolean" model is the kinetic logic formalism, put forward by Thomas and D'Ari (1). In a boolean system, a variable is either On or Off, 0 or 1. In the kinetic logic, here are more states: 0, 1, 2, 3,... It is best for study purpose but falls short of what is requested in uploading. The next step is the Continuous logical network of Mestl et al. (2) The basic elements are molecular concentrations and interactions are modeled by linear differential equations: d(concentration of A)/dt = Cte1 - Cte2(concentration of a). Cte1 and Cte2 are functions of the concentration jumping from one constant value in a range to another. These values are precomputed and storred in a memory. The third intermediate formalism uses differential equations broken in chunks. There in a grammar telling how and when to use such or such fragment in this or that case (3). Why bother about that ? The next step in complexity is the full differential model and it is insufficient. So anything simpler seems without interest. In fact, some element may be computed one time and the result storred in a memory. In this case a very precise model will be used, if something is computed very often, the model must be simpler. May be after a long chain, there will be a precise computation on a sample of reactions so that a corrective term will be added. On FPGA, the full differential model is very costly, if here is a solution to reduce its computing request, it is welcome. That is why the grammar - differential solution is interesting. (1) Thomas, R., and D'Ari R., (1990). in : Biological Feedback. CRC Press, Boca Raton, Fla. (2) Mestl et al. (1996) Choas in high-dimensional neural and gene networks. Physica D. vol. 98: p. 33. (3) Fleischer, K., (1995). A Multiple-Mechanism Developmental Model for Defining Self-Organizing Geometric Structure. Ph.D. thesis, California Institute of Technology, Passadena, Calif. Yvan Bozzonetti. Content-Type: text/html; charset="US-ASCII" [ AUTOMATICALLY SKIPPING HTML ENCODING! ] Rate This Message: http://www.cryonet.org/cgi-bin/rate.cgi?msg=25983