In this paper, the selection of H = weighting functions for general practical applications is investigated. It is shown that an H = weighting function for a single-input}single-output (SISO) plant can be obtained by considering a series of connections of elementary low-order plants. For a constrained control e!ort, an explicit weighting function expression is derived for the "rst time. A novel ...

In order to achieve relevant scholarly information from the biomedical databases, researchers generally use technical terms as queries such as proteins, genes, diseases, and other biomedical descriptors. However, the technical terms have limits as query terms because there are so many indirect and conceptual expressions denoting them in scientific literatures. Combinatorial weighting schemes ar...

the goal in information retrieval is to enable users to automatically and accurately retrieve data relevant to their queries. One possible approach to this problem is to use the vector space model, which models documents and queries as vectors in the term space. The components of the vectors are determined by the term weighting scheme. This paper compared between a selected set from the availab...

Instance weighting has been widely applied to phrase-based machine translation domain adaptation. However, it is challenging to be applied to Neural Machine Translation (NMT) directly, because NMT is not a linear model. In this paper, two instance weighting technologies, i.e., sentence weighting and domain weighting with a dynamic weight learning strategy, are proposed for NMT domain adaptation...

Finding shortest paths in mixed graphs is NP-hard even when the weighting is conservative. We give an FPT algorithm for this problem, where the parameter k is the number of “negative trees”. We may always assume that the undirected edges have negative weights, and in a conservative weighting they form some trees – these trees are called the negative trees. Our algorithm extends to mixed graphs ...

One of the core components in information retrieval(IR) is the document-term-weighting scheme. In this paper,we will propose a novel learning-based term-weighting approach to improve the retrieval performance of vector space model in homogeneous collections. We first introduce a simple learning system to weighting the index terms of documents. Then, we deduce a formal computational approach acc...

Regressions can be weighted by propensity scores in order to reduce bias. However, weighting is likely to increase random error in the estimates, and to bias the estimated standard errors downward, even when selection mechanisms are well understood. Moreover, in some cases, weighting will increase the bias in estimated causal parameters. If investigators have a good causal model, it seems bette...

PURPOSE Children must develop optimal perceptual weighting strategies for processing speech in their first language. Hearing loss can interfere with that development, especially if cochlear implants are required. The three goals of this study were to measure, for children with and without hearing loss: (a) cue weighting for a manner distinction, (b) sensitivity to those cues, and (c) real-world...

It is usually true that some structures like title can express the main content of texts, and these structures may have an influence on the effectiveness of text categorization. However, the most common feature weighting algorithms, called term frequency-inverse document frequency (TF-IDF) doesn’t think about the structural information of texts. To solve this problem, a new feature weighting al...

This paper presents an extended version of Partial Parallel Interference Cancellation (PPIC) called Variance reduced Partial Parallel Interference Cancellation (VRPPIC) for multicarrier code division multiple access uplink systems. The combination of PPIC receiver and new bit estimator is called VRPPIC detector. This realization is derived for the main PPIC operation and soft decision (SD) from...