DFT的matlab源代码戈策尔算法 Goertzel算法是数字信号处理（DSP）中的一项技术，为有效评估离散傅里叶变换（DFT）的各个项提供了一种方法。 Goertzel算法： 我创建了一个具有多个频率f0，f1和f2的正弦波。 我加了一些白噪声。 之后，我将goertzel功能应用于嘈杂的Signal。 另外，我计算了每个频率的检测概率，并绘制了平均概率与检测到的所有频率的关系图。 通过本塞迪克El Mehdi 14/03/2019

本书是九五电子部重点教材、电子信息类高等学校规划教材之一。本书全面、系统、深入地讨论了现代数字信号处理的理论、设计和应用。全书由自成体系而又有联系的八章组成，分别论及统计信号处理基础，维纳和卡尔曼滤波器，自适应滤波器，现代功率谱估计，同态信号处理，高阶谱估计，小波分析，以及人工神经网络信号处理。

数字信号处理DSP八个实验

2．巴特列特（Bartlett）窗（又称三角形窗） 其幅度函数为 三、各种窗函数

期末考试复习题，一到七章，涉及到要考的内容，有选择，填空，简答，设计题，很全的哦

测试信号处理技术，DSP MATLAB处理信号的基础知识，北航仪器科学与光电工程学院课件。

A.V.奥本海姆 R.W.谢弗 中文 图片版

上海交通大学本科DSP课件，配套李力利第二版数字信号处理教材，另含李力利第二版数字信号处理教材课后答案

数字信号处理 DSP 时域离散随机信号处理 丁玉美 电子书

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