heracle5's Projects
人工智能学习路线图,整理近200个实战案例与项目,免费提供配套教材,零基础入门,就业实战!包括:Python,数学,机器学习,数据分析,深度学习,计算机视觉,自然语言处理,PyTorch tensorflow machine-learning,deep-learning data-analysis data-mining mathematics data-science artificial-intelligence python tensorflow tensorflow2 caffe keras pytorch algorithm numpy pandas matplotlib seaborn nlp cv等热门领域
對抗文字識別
🔍 iOS和Mac端使用Apple-News.
A list of awesome papers and cool resources on WiFi CSI sensing.
Bypass Paywalls web browser extension for Chrome and Firefox.
Carbon Language's main repository: documents, design, implementation, and related tools. (NOTE: Carbon Language is experimental; see README)
仅支持"内核集成"模式的WARP多功能脚本(支持ARM/X86):纯IPV4、纯IPV6、双栈IPV4+IPV6 各种VPS都可用。目前已测试通过oracle(甲骨文云),gpc(谷歌云),buyvm,racknerd,virmach,vultr,aws(亚马逊云),azure(微软云),bandwagonhost(搬瓦工)……欢迎大家补充反馈!
Channel estimations based on RLS, LMS and ML methods.
Clash for Windows & Mac 自用稳定分流规则、参考配置
backup of clash core
A rule-based tunnel in Go.
☁️ Cloudflare workers + Github 实现的动态博客系统,使用边缘计算,无需服务器
本仓库的内容包括**境内部分高校的各类课程复习资料、笔记、优秀作业代码。本仓库为非营利、永久免费的开源项目。
A Matlab code for the "Maximum Likelihood Sequence Detection" for any CPM modulation (GMSK-RECT-RC....) using the Viterbi Algorithm.
Examples and guides for using the Gemini API.
java核心技术各个版本源码
coursera吴恩达机器学习课程作业自写Python版本+Matlab原版
:books: 技术面试必备基础知识、Leetcode、计算机操作系统、计算机网络、系统设计
计算机视觉入门
A tensorflow implementation of "Deep Convolutional Generative Adversarial Networks"
编程开发相关书籍整理分享,持续更新...
Tools to work with android .dex and java .class files
《自然辩证法研究》中文期刊LaTeX模板
Information Protection & OSINT resources | 一个关于数字隐私搜集、保护、清理集一体的方案,外加开源信息收集(OSINT)对抗
The repo includes the project of the course digital system experiment[fpga part]
Eye diagrams are used for visual analysis of the severity of inter symbol interference (ISI), accuracy of sampling timing extraction and noise immunity. In this report, eye diagrams are used to analyze the robustness of binary phase shift keying (BPSK) and 4-PAM (pulse amplitude modulation) digital communication systems. In task 1, a random bit sequence is generated and those bits are mapped to BPSK symbols. Impulse train of BPSK symbols was convoluted with a pulse shaping filter. Three pulses were used as the impulse response of the pulse shaping filter. They were sinc pulse, raised-cosine pulse with α = 0:5 and raised-cosine pulse with α = 1 where α is the roll-off factor. The impulse responses are shown in below Eye diagrams for those three transmit sequences were generated and the systems were compared as follows. After the task 1, additive white Gaussian noise (AWGN) is added to the transmit signals with specified bit energy to noise ratio. Finally, in task 3, 4-PAM system is used.. Then the eye diagrams are generated for the received signals with the presence of AWGN. Same pulse shaping filters as in task 1 are used.