Algorithms description

The algorithmic description of MPC dynamics given earlier outlined its essential elements and properties and provided a basis for implementations of the dynamics. However, a more formal specification of the evolution is required in order to make a link between the mesoscopic description and macroscopic laws that govern the system on long distance and time scales. This link will also provide us with expressions for the transport coefficients that enter the... 

Multi-objective Library Design Algorithm Description... 

Hoogen R., Rozanov, V., and Burrows J. (1999) Ozone profiles from GOME satellite data Algorithm description and first validation, J. Geophys. Res., 104, pp. 8263-8280. 

The vectorization of computer simulation algorithms for new generations of supercomputers is described by Heyes and Fincham in Vol. 63 of this series. Algorithm descriptions are avaUable in the Quarterly Review of the... 

Protein flexibility as the second major challenge is discussed in two separate chapters. The first is dedicated primarily to the algorithmic description of the methods available for handling protein flexibility, based on a new classification of the different approaches. The second chapter focuses on their application in high-throughput docking and virtual screening. As these chapters illustrate, a multitude of different approaches are already available for at least partial consideration of protein... 

MEDA improves the interpretation of both the data set and the model fitted without actually pursuing a simple structure. The result is that MEDA has better properties than rotation methods it is more accurate and its performance is not deteriorated when the number of PCs is overestimated. Also, the output of MEDA does not depend on the normalization of the loadings, like rotated models do, an it is not limited to subspaces with two or three components at most. A comparison of MEDA with rotation methods is out of the scope of this chapter. Please refer to (11) for it and also for a more algorithmic description of MEDA. 

The Algorithm An algorithmic description of the method is easily devised once a geometric understanding of the method has been established. It is assumed that a feed point Cf and stoiehiometrie eoeffieient matrix A have been specified. The method is broken down into three main phases as follows ... 

Design entry in a high-level synthesis system is an algorithmic description written in a common programming language (like PASCAL or FORTRAN), or by a special purpose hardware description language (HIX), such as ISPS, DSL or VHDL. 

For the generation of constant values in the algorithmic description, constanlh nodes are defined. These nodes deliver the (specified) constant value to their output port when the nodes are executed, and can be regarded as unary operators. A sequence edge is connected to deliver the enabling token see figure 8. 

A primary task in high-level architecture synthesis is the extraction of the data flow from a given algorithm description. The term data flow is defined here as the combination of operations and dependencies between them that define the algorithm. In contrast, control flow is then defined as a (partial) ordering of computations meeting the restrictions of their dependencies. The control flow is usually specified by introducing loops and function hierarchy. 

It is impossible to show properly the order existing in a vegetational community only with a floristic description s (e.g. phytosodologic table). Rather, if the shorter algorithmic description of a system coincides with the description of the entire system, the system has to be classified as chaotic, dependent from the initial condition (Pignatti et al. 1998). 

This article is structured as follows we first introduce the problem of unconstrained minimization and an abstract algorithmic description for its solution strategy. Then we give a short review of the classical approaches and briefly discuss their properties, in particular their shortcomings. The third part introduces the subspace search method. We discuss the underlying mathematics and devise an algorithmic representation. Finally, we report on the numerical performance of the outlined algorithms and comment on the solution of systems of nonlinear equations. 

Figure 11.2 Design Flow from Algorithmic Description To Gates Using...

The input to BC is a high-level algorithmic description (behavioral), while the output is an optimized RTL description which is then optimized to gates using DC as shown in Figure 11.2. 

Computer-aided synthesis of digital circuits from an algorithmic description is a difficult problem. We have proposed in this research an approach to ASIC synthesis that addresses some of the difficulties in effectively integrating a synthesized design with other components in the system. However, many difficult problems have not yet been solved. We summarize in Section 12.1.1 the... 

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