卡尔曼滤波的单目标跟踪代码Python版,视频中逐帧处理。
2022-11-18 23:52:13 8.17MB Python实现卡尔曼滤波的单目
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作业#16:D3.js 请通过以下链接访问已部署的网站: :
2022-11-17 10:43:59 9KB JavaScript
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密码学难题集合,便于密码学习者一目对困难问题一目了然,是密码学习的好帮手。
2022-11-15 09:18:11 416KB 密码学
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使用matlab实现三次样条函数的main函数,注意这里并未添加数据处理部分
2022-11-14 11:24:24 887B matlab 三次样条
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PCAP01_SPI_main源码.zip
2022-11-11 15:08:35 8KB
0.97以脱壳的MAIN
2022-11-06 17:49:09 468KB 0.97MAIN
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以整数线性规划方法解决火电机组机组组合问题。包括爬坡、启停约束等。以最小化运行成本为目标。
2022-11-05 01:20:14 2KB matlab例程 matlab
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基于emd的滚动轴承故障诊断驱动计数端的内圈故障,故障明显,基于EMD的包络解调有效风扇计数端的内圈故障,故障效果不好,基于EMD的包络解调不是很有效基础计数端的内圈故障,故障效果不好,基于EMD的包络解调无效,只能看到转频,故障频率不明显
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This article provides an overview of recent developments in mainmemory database systems. With growing memory sizes and memory prices dropping by a factor of 10 every 5 years, data having a “primary home” in memory is now a reality. Main-memory databases eschew many of the traditional architectural pillars of relational database systems that optimized for disk-resident data. The result of these memory-optimized designs are systems that feature several innovative approaches to fundamental issues (e.g., concurrency control, query processing) that achieve orders of magnitude performance improvements over traditional designs. Our survey covers five main issues and architectural choices that need to be made when building a high performance main-memory optimized database: data organization and storage, indexing, concurrency control, durability and recovery techniques, and query processing and compilation. We focus our survey on four commercial and research systems: H-Store/VoltDB, Hekaton, HyPer, and SAP HANA. These systems are diverse in their design choices and form a representative sample of the state of the art in main-memory database systems. We also cover other commercial and academic systems, along with current and future research trends.
2022-11-04 17:58:33 3.03MB c++ memory
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