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Low-rank representation (LRR) via rank minimization is a high efficiency method for capturing low-dimensional structure embedded in high-dimensional data. However, minimizing the rank of a matrix is NP-hard. In this paper, robust truncated nuclear norm low-rank representation regularized by L2,1-norm method (RTLRR) is proposed. The truncated nuclear norm is introduced to replace the nuclear norm to...
In order to compensate the nonlinear distortion of the traveling wave tube amplifiers (TWTAs), a new analog predistortion linearizer based on vector synthesis technique is presented. This linearizer consists of quadrature hybrids, adjustable analog attenuator based on PIN diodes and nonlinear circuit based on Schottky diodes. The analog predistortion linearizer can realize the expansion of amplitude...
Wireless video transmission systems have been widely adopted to facilitate the ubiquitous access of the multimedia services on the Internet. However, wireless links are not stable and the channel quality might vary with time. Efficient modulation scheme plays an important role to improve the quality of service (QoS) of video transmission. However, the previous efforts mainly focused on the rectangular...
Unknown word recognition is a very important problem in natural language processing. It has a great influence on the performance of dictionary construction and word segmentation. This paper introduces two methods to improve the effect of Chinese unknown word recognition by using Conditional Random Fields: the rough label of the characters and the N-best listing. The CRF with the two methods proposed...
We present a ME (Maximum Entropy) model for Semantic Chunk Annotation in a Chinese Question and Answer (Q&A) system. The model was derived from a corpus of real world questions, which are collected from some discussion groups on the Internet. The questions are supposed to be answered by other people, so the questions are very complex. The semantic chunks were introduced. Feature for the model...
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