A
Regular Folding Procedure
M.
Gušev, D.J. Evans
Abstract.
Folding transformations on processor arrays result in smaller processor arrays,
more efficient work for the processing elements, a decrease in I/O time,
pipelineable implementations and circular data flow are presented in [1]. In
this paper the folding transformation is defined via symmetric transformations
and interlocking translations implemented on the space time graphs. The regular
folding transformation according to a translated line of symmetry offers valid
and regular solutions. Two generalized procedures for regular folding are given
here keep the complexity of the data communications, the processor operations,
the regular data flow and avoid data collision. The matrix vector multiplication
algorithm is given as an example of the proposed procedures and the best folding
transformation is determined.
The
efficiency analysis shows that the implementation obtained utilizes the
processor array with double efficiency. Moreover, by using the same processor
array, problems with double the dimension can be solved. Also, the circular data
flow can be used for cascaded algorithms.
Generalized
Semi-Markov Process Model of Asynchronous Automatic Assembly System with
Simultaneous Resource Possession Property, the statement of the perturbation
analysis algorithm
M.
Valent, Z. Lovász
Abstract.
In this paper we will construct the base of generated semi-Markov process (GSMP)
model of asynchronous automatic assembly system (AAAS) with simultaneous
resource possession (SRP) property, and perturbation analysis (PA) algorithm
corresponding to the system.
On
Planar Affine Transform Determination
G.
Podhájecký, J. Glasa
Abstract.
An effective direct method for determination of planar affine transform
coefficients is described. It is based on construction of triangles defined by
barycentric centroids of corresponding parts of reference and transformed images
which are cut by straight lines determined by barycentric centroids. Numerical
experiments performed have confirmed a good performance of proposed method.
Fuzzy
Modeling with Genetic Algorithms
V.
Wuwongse, S. Veluppilai
Abstract.
Recent applications of fuzzy control have created an urgent demand for fuzzy
modelling techniques. Several methods for identification of fuzzy models from
numerical input-output samples have been proposed. Among them, Sugeno and
Yasukawa's method [6], which employs fuzzy c/means clustering, holds significant
promises. This paper improves the method of Sugeno and Yasukawa. Identified
fuzzy models are tuned at various stages by means of genetic algorithms, i.e.,
the numbers of input variables and rules are reduced and membership function
parameters are adjusted. The technique, when applied to a nonlinear system,
demonstrates its efficiency in a comparison with the original method of Sugeno
and Yasukawa.
On
the Average Number of Solutions for SAT Instances
H.
Drias, A. Bensalma
Abstract.
In this paper, we are interested in counting solutions for instances of
satisfiability and more precisely we try to extend the formula for the average
number of solutions of random instances proposed in [4] to a large class of
instances. In fact the formula given in this reference works for the specific
class of instances where all clauses are dependent. When we consider the
independence characteristic of clauses, we find a more general mathematical
expression. The computation of the average number of solutions with the actual
formula depends only on the structure of independence of the instance. The
latter is defined to be the set of subsets of independent clauses.
Searching
the structure of independence for an instance is shown to be NP-hard. An
algorithm in time O
(nk2)
is designed for finding an approximate structure of an instance, k
being the number of clauses and n the
number of variables of the instance. Even though an approximate structure of
independence is considered in the calculation of the average number of
solutions, our formula yields results with more accuracy.
Lifting
of L-Narrowing Derivations
P.
Bachmann
Abstract. If conditional rewrite/rules are restricted to the form PÞ f (x1, …, xn) ® t where P is a finite set of equations, f is any function symbol, x1, …, xn are variables, and t is any term when the premise P contains in general variables which do not occur in the list x1, …, xn. The rule with premise P can be applied if P is satisfiable. Therefore, we need methods to solve P and narrowing must be combined with rewriting. But, narrowing becomes a special case, called L-narrowing, closely related to lay-narrowing. Two lifting lemmas are shown which characterize the relationship of L/narrowing derivations if the goals are modified by substitutions. From these lifting lemmas, soundness and completeness results can be concluded.