从arXiv纸张标题生成类别 该项目采用并根据arXiv论文标题构建自动标签分类器。 系统输入：走向广泛学习：医疗保健实验 系统输出： stat.ML ， cs.LG 到上述论文。

Digital Signal Processing and Noise Reduction 4th Edition

processing粒子系统,创意好看，彩色，几何形状 代码 点击屏幕释放粒子系统会自动销毁

通过processing解读待绘图文件，使用串口通讯，arduino控制步进电机绘制图像

加工 我使用Processing 3 IDE收集的一些作品 执照 这些项目已获得MIT许可证的许可-有关详细信息，请参阅文件。

数据可视化：1900 年以来的地震 尝试处理 作为 Processing 的第一次用户，这只是深入了解 Processing 功能的好方法。 美国地质调查局有一个可追溯到 1900 年的精彩地震数据库，所以它们来了！

Understanding Digital Signal Processing, Third Edition, is quite simply the best resource for engineers and other technical professionals who want to master and apply today’s latest DSP techniques. Richard G. Lyons has updated and expanded his best-selling second edition to reflect the newest technologies, building on the exceptionally readable coverage that made it the favorite of DSP professionals worldwide. He has also added hands-on problems to every chapter, giving students even more of the practical experience they need to succeed. Comprehensive in scope and clear in approach, this book achieves the perfect balance between theory and practice, keeps math at a tolerable level, and makes DSP exceptionally accessible to beginners without ever oversimplifying it. Readers can thoroughly grasp the basics and quickly move on to more sophisticated techniques. This edition adds extensive new coverage of FIR and IIR filter analysis techniques, digital differentiators, integrators, and matched filters. Lyons has significantly updated and expanded his discussions of multirate processing techniques, which are crucial to modern wireless and satellite communications. He also presents nearly twice as many DSP Tricks as in the second edition—including techniques even seasoned DSP professionals may have overlooked. Coverage includes New homework problems that deepen your understanding and help you apply what you’ve learned Practical, day-to-day DSP implementations and problem-solving throughout Useful new guidance on generalized digital networks, including discrete differentiators, integrators, and matched filters Clear descriptions of statistical measures of signals, variance reduction by averaging, and real-world signal-to-noise ratio (SNR) computation A significantly expanded chapter on sample rate conversion (multirate systems) and associated filtering techniques New guidance on implementing fast convolution, IIR filter scaling, and more Enhanced coverage of analyzing digital filter behavior and performance for diverse communications and biomedical applications Discrete sequences/systems, periodic sampling, DFT, FFT, finite/infinite impulse response filters, quadrature (I/Q) processing, discrete Hilbert transforms, binary number formats, and much more

语音识别 spoken language processing

Computer-Based Exercises for Signal Processing Using MATLAB 5 配套源码

Iirj 用JAVA编写的IIR过滤器库。 高通，低通，带通和带阻分别为Butterworth，Bessel和Chebyshev I / II型。 它基于IIR1库[ ]，而该库又基于Vinnie Falco的DSPFilters [ ]。 用法 import uk.me.berndporr.iirj.*; 建设者 Butterworth butterworth = new Butterworth(); 初始化 带阻 butterworth.bandStop(order,Samplingfreq,Center freq,Width in frequ); 带通 butterworth.bandPass(order,Samplingfreq,Center freq,Width in frequ); 低通 butterworth.lowPass(order,Samplingfr