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说明：  轴承滚动体故障诊断代码，内含频率计算，大家一起学习(Rolling Element Bearing Fault Diagnosis code, containing the frequency calculation, everyone learning together)

本书既包含了数字信号处理的经典内容，也包含了部分前言内容。理论与应用相结合，特别注重应用matlab来解决理论与算法的实现问题，对于数字信号处理的学习者很实用。  (The book contains both the digital signal processing classic content, but also contains some foreword content. The combination of theory and application, with particular emphasis on applications to solve matlab realization theory and algorithms for digital signal processing learners very practical.)

一个可以实现矩形阵列信号处理的程序，大家试一试吧(A rectangular array signal processing can achieve the program, we try it)

有限元法(finite element method)求波导中的TE模(FEM (finite element method) waveguide for the TE mode)

计算采用MATLAB并画出匹配波波形器的压缩输出(Calculated and drawn to match the compressed output waveform)

反应扩散问题长期在研究领域中c++去实现, 现在我们用MATLAB也可以(Reaction-diffusion problem in the area of research in long-term c++ to achieve, and now we can use MATLAB)

通过运用数学软件matlab绘制不同颜色形状的花坛曲面(By using mathematical software matlab draw a different colors and shapes of flowerpot surface )

说明：  压缩感知（Compressed sensing），也被称为压缩采样(Compressive sampling)，稀疏采样(Sparse sampling)，压缩传感 [1] 。它作为一个新的采样理论，它通过开发信号的稀疏特性，在远小于Nyquist 采样率的条件下，用随机采样获取信号的离散样本，然后通过非线性重建算法完美的重建信号 [1] 。压缩感知理论一经提出，就引起学术界和工业界的广泛关注。(Compressed sensing (Compressed sensing), also known as compression sampling (Compressive from), Sparse sampling (Sparse from), Compressed sensing [1].As a new sampling theory, it develops the sparse characteristics of signals, obtains the discrete samples of signals with random sampling under the condition that the sampling rate is much lower than Nyquist sampling, and then perfectly reconstructs the signals through the nonlinear reconstruction algorithm [1].Once the theory of compressed sensing was put forward, it attracted extensive attention from academia and industry.)

峰值检测，用于图像处理中的峰值检测！程序能够自动找到峰值的位置！(Peak detection, image processing for peak detection! Program can automatically find the location of the peak!)

Transmission of a signal and to check probability of Detection.