63,006 research outputs found
The Acquisition of Recursion: How Formalism Articulates the Child’s Path
We distinguish three kinds of recursion: Direct Recursion (which delivers a ‘conjunction’ reading), Indirect Recursion, and Generalized Transformations. The essential argument is that Direct Recursion captures the first stage of each recursive structure. Acquisition evidence will then be provided from both naturalistic data and experimentation that adjectives, possessives, verbal compounds, and sentence complements all point to con-junction as the first stage. Then it will be argued that Indirect Recursion captures the Strong Minimalist Thesis, which allows periodic Transfer and interpretation. Why is recursion delayed and not immediate? It is argued that an interpretation of Generalized Transformations in the spirit of Tree Adjoining Grammar offers a route to explanation. A labeling algorithm combines with Generalized Transformations to provide different labels for recursive structures projection. Recursion is then achieved by substitution of a recursive node for a simple node. One simple case is to substitute a Maximal Projection for a simple non-branching lexical node. A more complex case — essential to acquisition — is to substitute a category for a lexical string. Consequently, a computational ‘psychological reality’ can be attributed to explain why recursion requires an extra step for the addition of each recursive construction on the acquisition path
Compilation of extended recursion in call-by-value functional languages
This paper formalizes and proves correct a compilation scheme for
mutually-recursive definitions in call-by-value functional languages. This
scheme supports a wider range of recursive definitions than previous methods.
We formalize our technique as a translation scheme to a lambda-calculus
featuring in-place update of memory blocks, and prove the translation to be
correct.Comment: 62 pages, uses pi
Generalized Points-to Graphs: A New Abstraction of Memory in the Presence of Pointers
Flow- and context-sensitive points-to analysis is difficult to scale; for
top-down approaches, the problem centers on repeated analysis of the same
procedure; for bottom-up approaches, the abstractions used to represent
procedure summaries have not scaled while preserving precision.
We propose a novel abstraction called the Generalized Points-to Graph (GPG)
which views points-to relations as memory updates and generalizes them using
the counts of indirection levels leaving the unknown pointees implicit. This
allows us to construct GPGs as compact representations of bottom-up procedure
summaries in terms of memory updates and control flow between them. Their
compactness is ensured by the following optimizations: strength reduction
reduces the indirection levels, redundancy elimination removes redundant memory
updates and minimizes control flow (without over-approximating data dependence
between memory updates), and call inlining enhances the opportunities of these
optimizations. We devise novel operations and data flow analyses for these
optimizations.
Our quest for scalability of points-to analysis leads to the following
insight: The real killer of scalability in program analysis is not the amount
of data but the amount of control flow that it may be subjected to in search of
precision. The effectiveness of GPGs lies in the fact that they discard as much
control flow as possible without losing precision (i.e., by preserving data
dependence without over-approximation). This is the reason why the GPGs are
very small even for main procedures that contain the effect of the entire
program. This allows our implementation to scale to 158kLoC for C programs
Global and local Complexity in weakly chaotic dynamical systems
In a topological dynamical system the complexity of an orbit is a measure of
the amount of information (algorithmic information content) that is necessary
to describe the orbit. This indicator is invariant up to topological
conjugation. We consider this indicator of local complexity of the dynamics and
provide different examples of its behavior, showing how it can be useful to
characterize various kind of weakly chaotic dynamics. We also provide criteria
to find systems with non trivial orbit complexity (systems where the
description of the whole orbit requires an infinite amount of information). We
consider also a global indicator of the complexity of the system. This global
indicator generalizes the topological entropy, taking into account systems were
the number of essentially different orbits increases less than exponentially.
Then we prove that if the system is constructive (roughly speaking: if the map
can be defined up to any given accuracy using a finite amount of information)
the orbit complexity is everywhere less or equal than the generalized
topological entropy. Conversely there are compact non constructive examples
where the inequality is reversed, suggesting that this notion comes out
naturally in this kind of complexity questions.Comment: 23 page
Identification of nonlinear vibrating structures: Part I -- Formulation
A self-starting multistage, time-domain procedure is presented for the identification of nonlinear, multi-degree-of-freedom systems undergoing free oscillations or subjected to arbitrary direct force excitations and/or nonuniform support motions. Recursive least-squares parameter estimation methods combined with nonparametric identification techniques are used to represent, with sufficient accuracy, the identified system in a form that allows the convenient prediction of its transient response under excitations that differ from the test signals. The utility of this procedure is demonstrated in a companion paper
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