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lora收发demo
说明： stm32使用ra02模块的例程,点对点通讯(Stm32 USES ra02 module routines to communicate point-to-point)
- 2020-11-10 18:51:10下载
- 积分：1
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AMC
说明： 自己编写的TPC Chase II译码算法，支持多种高阶调制，支持缩短码等(I have written the TPC Chase II decoding algorithm to support multiple high-order modulation, supported a short code, etc.)
- 2020-12-26 18:49:02下载
- 积分：1
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imgSlider
说明： 一款HTML5响应式全屏宽度幻灯片特效，该HTML5图片特效是一款可以根据屏幕的大小自动调整幻灯片的宽度(An HTML5 responsive full-screen width slide effect is free. The HTML5 image effect is a slide width that can be adjusted automatically according to the size of the screen.)
- 2019-05-10 09:18:54下载
- 积分：1
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图书借阅系统文档与程序实现
图书借阅系统文档与程序实现-Lending Library System files and Program Implementation
- 2023-04-15 15:10:04下载
- 积分：1
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ex_01a_simple_tx
example 01a simple tx example
- 2018-05-22 19:30:04下载
- 积分：1
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pantompkins code
ecg noise generator
- 2018-02-27 23:31:49下载
- 积分：1
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Modern-Communications-Jamming
该书是一本通信对抗专业的实用参考书。系统地介绍了现代抗干扰通信技术(主要是直接序列扩谱和跳频扩谱)和抗干扰通信的检测技术，讨论了每一种基本抗干扰信号类型的干扰技术，包括干扰直接序列扩谱信号、干扰快跳频扩谱信号、干扰慢跳频扩谱信号和干扰直接序列扩谱/跳频扩谱混合信号。该书的读者对象是电子战和通信对抗领域的工程师和科技工作者，也可供通信领域的科技工作者参考。(Content HighlightsAnti-Jam Communications and Electronic Countermeasures. Radio Frequency Propagation. Signaling for AJ Communications. Jamming Techniques. Anti-Jam Signal Detection. Jamming Direct Sequence Spread Spectrum Systems. Jamming Fast Frequency Hopping Systems. Jamming Slow Frequency Hopping Systems. Jamming Hybrid Spread Spectrum Systems.)
- 2017-02-27 19:59:50下载
- 积分：1
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report_58f1c27321474wkjx
模拟自由曲面面型，对光学设计人员很有帮助(Analog freeform surface)
- 2017-09-06 16:40:43下载
- 积分：1
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二进制搜索
说明： RFID防碰撞算法，二进制搜索树使用matlab仿真，(Simulation of binary search tree using MATLAB)
- 2019-06-21 12:34:55下载
- 积分：1
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聚类-k均值算法
K-means算法是基于划分的思想，因此算法易于理解且实现方法简单易行，但需要人工选择初始的聚类数目即算法是带参数的。类的数目确定往往非常复杂和具有不确定性，因此需要专业的知识和行业经验才能较好的确定。而且因为初始聚类中心的选择是随机的，因此会造成部分初始聚类中心相似或者处于数据边缘，造成算法的迭代次数明显增加，甚至会因为个别数据而造成聚类失败的现象。(K-means algorithm is based on the idea of partitioning, so the algorithm is easy to understand and the implementation method is simple and feasible, but it requires manual selection of the initial number of clusters, that is, the algorithm is with parameters. The number of classes is often very complex and uncertain, so professional knowledge and industry experience are needed to better determine. Moreover, because the selection of initial clustering centers is random, some initial clustering centers will be similar or at the edge of data, resulting in a significant increase in the number of iterations of the algorithm, and even the phenomenon of clustering failure due to individual data.)
- 2020-06-21 17:40:01下载
- 积分：1
