ID 原文 译文
19605 利用加权统计(TF-IDF)算法实现了多关键词查询结果的排序。 The ranking of multi-keyword query results is realized by the Term Frequency–Inverse Document Frequency (TF-IDF) algorithm.
19606 在随机预言机模型下，证明该方案是适应性不可区分安全的，通过效率对比分析，表明该方案在区块链上实现了高效的密文检索。 Under the random oracle model, it is proved that the scheme is adaptive and indistinguishable. Through the comparative analysis of efficiency, it is shown that the scheme achieves efficient ciphertext retrieval on the blockchain.
19607 在有重尾的过程噪声和量测噪声的影响下，高斯混合势均衡多目标多伯努利滤波器(GM-CBMeMBer)的滤波性能会明显下降。 The filtering performance of Gaussian Mixture Cardinality Balanced Multi-target Multi-Bernoulli(GM-CBMeMBer) filter can be effected by the heavy-tailed process noise and measurement noise.
19608 针对上述问题，该文提出一种新的学生 t 混合势均衡多目标多伯努利滤波器(STM-CBMeMBer)。 To solve thisproblem, a new STudent’s t Mixture Cardinality Balanced Multi-target Multi-Bernoulli (STM-CBMeMBer)filter is proposed.
19609 该滤波器将过程噪声和量测噪声近似为学生 t 分布，并用学生 t 混合模型来近似多目标的先验强度。 The process noise and measurement noise approximately obey the Student’s t distribution in the filter, where the Student’s t mixture model is used to describe approximately the posterior intensity of the multi-target.
19610 从理论上推导出学生 t 混合形式的预测强度和后验强度，建立了势均衡多目标多伯努利滤波器的闭式递推框架。 The predictive intensity and posterior intensity of Student’s t mixture form are deduced theoretically, and the closed recursive framework of cardinality balanced multi-target multi-Bernoulli filter is established.
19611 仿真结果表明，在重尾的过程噪声和量测噪声存在的环境中，该滤波器能有效抑制其干扰，相比于传统方法，具有更高的跟踪精度。 The simulation results show that, in the presence of the heavy-tailed process noise and the measurement noise, the filter can effectively suppress its interference, its tracking accuracy is superior over the traditional methods.
19612 为了提高帧存储的压缩性能，该文提出一种基于方向插值预测变长编码(DIPVLC)的帧存有损压缩算法。 A lossy frame memory compression algorithm using Direction Interpolation Prediction VariableLength Coding (DIPVLC) is proposed to improve frame memory compression performance.
19613 首先根据自适应纹理方向插值获取参考像素，从而得到预测残差，然后优化率失真模型对预测残差进行量化，最后通过游程哥伦布算法对量化残差进行变长编码。 Firstly, the prediction residual is obtained by adaptive texture directional interpolation. Then, a new rate-distortion is optimized to quantize prediction residual. Finally, the run length Golomb method is used to entropy coding forquantized residual.
19614 实验结果显示，与内容感知自适应量化(CAAQ)的帧存压缩算法相比，该文算法不但PSNR下降更少，而且压缩率提高了10.05%，同时编码时间减少了10.62%。 Simulation results show that compared with parallel Content Aware Adaptive Quantization(CAAQ) oriented lossy frame memory recompression for HEVC, the proposed algorithm improves thecompression rate by 10.05% and reduces the encoding time by 10.62% with less PSNR reduction.