3 research outputs found

    MACROTEX : a LATEX code generator in MACSYMA

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    Estimation of settling velocities

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    International audienceThis paper deals with settling velocities estimation, which is of major importance as settling velocities estimation is a prerequisite for properly dimensioning settling ranks. Several measurement procedures are presented and analyzed here. A general framework for identification which includes modelisation of the settlers and identification techniques is developed here-in. In this paper, we demonstrate that for a parametric set of settling density functions ?(dv) = S(i)(N)= (l)?(i)?(i)(dv) the mathematical relation between the measures M(t(i))(i) = l,N and the unknown quantities (0(i))(i) = (l,N) take the following linear form M(t(i)) = S(k)(N) = (l)0(k)?RØx(t(i),v)?(k)(dv). This relation makes it possible to have access to statistical errors in settling velocity estimates (0(i)) in assuming that a statistical model of measurement errors (M(t(i))) exists. The consequences of the choice of sampling times (t(i))(i) = (l,N) on the quality of the estimation are also investigated.This paper deals with settling velocities estimation, which is of major importance as settling velocities estimation is a prerequisite for properly dimensioning settling tanks. Several measurement procedures are presented and analyzed here. A general framework for identification which includes modelization of the settlers and identification techniques is developed here-in. In this paper, we demonstrate that for a parametric set of settling density functions ?(dv) = ?i = 1N?i?i(dv) the mathematical relation between the measures M(ti)i = 1,N and the unknown quantities (?i)i = 1,N take the following linear form M(ti) = ?k = 1N?k?Rfx(ti, v)?k(dv). This relation makes it possible to have access to statistical errors in settling velocity estimates (?i) in assuming that a statistical model of measurement errors (M(ti)) exists. The consequences of the choice of sampling times (ti)i = 1,N on the quality of the estimation are also investigated

    An Expert System for Control and Signal Processing With Automatic FORTRAN Program Generation.

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    A prototype expert system for the treatment of stochastic control and nonlinear signal processing problems is described with several illustrative examples. The system is written In MACSYMA, LISP and PROLOG. It accepts user input in natural language or symbolic form; it carries out the basic analysis of the user's problem in symbolic form (e.g., computing the Bellman dynamic programming equations for stochastic control problems or the Zakai equation and the estimation Lie algebra or likelihood ratio for nonlinear filtering problems); and it produces output in the form of automatically generated FORTRAN code for the flannel numerical reduction of the problem. The system also has a module using PROLOG which can check the well-posedness (existence and uniqueness) of certain classes of linear and nonlinear partial differential equations specified in symbolic form by computing a natural Sobolev space for the solutions and verifying classical existence and uniqueness criteria for the given equation using MACSYMA for the computations and PROLOG for the logical analysis. Sample sessions with three of the modules of the system are presented to illustrate its operation. The status of the system and plans for its further development are described
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