729 standard in detail, analyzes the important technologies in theory: linear prediction, vector quantization, codebook search and post-filter.

study of vector quantization fast codeword search algorithms;

提出了一种矢量量化快速码字搜索算法。

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prediction model based on least squares support vector machine with harmony search and its application

和声搜索最小二乘支持向量机预测模型及其应用

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secondly, aiming at the easily falling into local optimum problem, we introduce one or two perturbation vector into the search way of the improved algorithm. this can maintain the diversity of the population and prevent the algorithm falling into a focal optimum.

其次，针对算法容易陷入局部最优的问题，我们在改进算法的搜索方式中引入一个或两个扰动向量，这样来保持种群的多样性，防止算法陷入局部最优。

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an improved dtw speech recognition method based on vector quantization and search table is proposed. compared with classic dtw, it largely reduces time and space complexity and more suitable for software and hardware implementation.

提出一种基于矢量量化和查找表的改进DTW语音识别方法，大幅度降低了传统DTW算法的时空复杂度，非常适合于软硬件实现。

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therefore, the key elements of this thesis are divided into two parts: adaptive segmentation of internet music feature recognition/ extraction and classification method based on support vector machine intelligence search technology for internet music analysis.

所以，本论文研究的重点内容主要分为两大部分：基于自适应分词的互联网音乐特征识别／提取和基于支持向量机分类方法的互联网音乐智能检索技术分析。

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and secondly, we can find out a nearest codeword to the input vector using up-down search mechanism in the blocks near the initial best-matching block.

然后在该码书块附近上下扩展搜索相邻码书块中距输入矢量最近的码字。

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a new dtw speech recognition method based on vector quantization and search table

一种基于矢量量化和查找表的改进DTW语音识别方法

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to improve recall and precision ratios of this system, vector match search rather than traditional boolean search, term weighing according to the importance of terms and output sorting are used.

该系统采用了与传统的布尔逻辑检索截然不同的矢量匹配检索，加上标引词按重要性被赋予权值，再排序输出，从而使检索的查全率有了提高。

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through the above optimized macroblock mode mapping algorithm and motion vector refinement search algorithm, we achieve a significant reduction of computation complexity under the requirement of ensuring video quality.

通过采用上述优化的宏块编码模式映射算法和运动矢量精细化搜索算法，能够在保证图像质量的前提下，显著降低所需的计算量。

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in practical application, considering video watermarking system has high demand on real-time and low-bit rate, this paper proposed a fragile watermarking algorithm based on diamond search. fragile watermark was embedded in motion vector search of p frame inter prediction.

考虑到实际应用中视频水印系统的实时性需要和低码率需要，提出一种基于菱形搜索原理的脆弱水印算法，将脆弱水印嵌入P帧帧间预测的运动矢量中。

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According to this feature, we propose a bit vector search algorithm which maps multiple channels into an integer variable. This variable is the so-called bit vector. Each channel corresponds to a bit in the variable.

根据这个特点，本文提出一种位向量搜索算法，该算法将多个通道映射为一个整型变量.这个变量即二进制位向量，每个通道对应变量中的一个位。

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three optimization methods, namely, hooke-jeeves modular vector search method, powell conjugate direction search method, and random direction search method, have been chosen and improved. and three programs are given.

本文选用及改进了Hooke-Jeeves的模矢搜索法、Powell的共轭方向法及随机方向搜索法，相应编制了3个优化设计程序。

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after detailed discussion on the rationale and procedure of the mle approach, an efficient numerical wind vector search algorithm is presented in this paper, according to the general distribution of objective function.

该文对最大似然估计的风场反演方法的基本原理和具体过程进行探讨，根据其目标函数的一般分布特征，提出一种较为高效的数值风矢量搜索算法。

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a minimal matching error direction prediction-based fast half-pixel motion vector search algorithm is pro-posed in this paper in order to reduce computation load of half-pixel search.

为了减小半像素搜索的计算量，本文提出了一个基于最小匹配误差方向预测的快速半像素运动估计算法。

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fast and adaptive motion vector search

一种快速的自适应运动矢量搜索算法

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with the rapid development of internet of things technology, a huge business value network is formed.

随着物联网技术迅猛发展，物联网日益形成一个巨大的商业价值网。

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the development of the gateway is very important to build internet of things' architecture.

在构建物联网体系结构，网关是非常重要。

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another trend is the growth of what is known as the internet of things.

另一个趋势就是所谓的物联网的发展。

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another term for the internet of things is

针对物联网的另一术语是

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the connected internet of things is rapidly becoming reality.

物联网正在迅速地成为现实。

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