65,048 research outputs found
Reduction of Second-Order Network Systems with Structure Preservation
This paper proposes a general framework for structure-preserving model
reduction of a secondorder network system based on graph clustering. In this
approach, vertex dynamics are captured by the transfer functions from inputs to
individual states, and the dissimilarities of vertices are quantified by the
H2-norms of the transfer function discrepancies. A greedy hierarchical
clustering algorithm is proposed to place those vertices with similar dynamics
into same clusters. Then, the reduced-order model is generated by the
Petrov-Galerkin method, where the projection is formed by the characteristic
matrix of the resulting network clustering. It is shown that the simplified
system preserves an interconnection structure, i.e., it can be again
interpreted as a second-order system evolving over a reduced graph.
Furthermore, this paper generalizes the definition of network controllability
Gramian to second-order network systems. Based on it, we develop an efficient
method to compute H2-norms and derive the approximation error between the
full-order and reduced-order models. Finally, the approach is illustrated by
the example of a small-world network
Reconstructing Native Language Typology from Foreign Language Usage
Linguists and psychologists have long been studying cross-linguistic
transfer, the influence of native language properties on linguistic performance
in a foreign language. In this work we provide empirical evidence for this
process in the form of a strong correlation between language similarities
derived from structural features in English as Second Language (ESL) texts and
equivalent similarities obtained from the typological features of the native
languages. We leverage this finding to recover native language typological
similarity structure directly from ESL text, and perform prediction of
typological features in an unsupervised fashion with respect to the target
languages. Our method achieves 72.2% accuracy on the typology prediction task,
a result that is highly competitive with equivalent methods that rely on
typological resources.Comment: CoNLL 201
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A survey of behavioral-level partitioning systems
Many approaches have been developed to partition a system's behavioral description before a structural implementation is synthesized. We highlight the foundations and motivations for behavioral partitioning. We survey behavioral partitioning approaches, discussing abstraction levels, goals, major steps, and key assumptions in each
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