水下潜艇的时频分析，重点是傅里叶变换和频率滤波。

时频分析的matlab实现，功能很强大

CS4495计算机视觉课程讲义，频域和傅里叶变换。

通过PLL实现AFC技术。

通过频率控制实现AFC

Introduction: radar electronic backscattering; radar signals; radar ambiguity function and matched filter; synthetic aperture radar imaging. Time-frequency transforms: linear transforms; bilinear transforms. Detection and extraction of signal noise: time-varying frequency filtering; SNR improvement in time-frequency domain; CFAR detection in joint time-frequency domain; signal extraction in joint time-frequency domain. Time-frequency analysis of radar range profiles: electromagnetic phenomenology embedded in backscattered data; time-frequency representation of range profiles; application of high-resolution time-frequency techniques to scattering data; extraction of dispersive scattering features from radar imagery using time-frequency processing. Time-frequency based image formation: radar imaging of moving targets; motion compensation; time-frequency based image formation; radar imaging of manoeuvring targets; radar imaging of multiple targets. Motion compensation in inverse synthetic aperture radar imaging using time-frequency techniques: motion compensation algorithms; time-frequency based motion compensation; motion compensation examples of simulated and measured data; presence of three-dimensional target motion. Synthetic aperture radar imaging of moving target: radar signatures of moving targets; effect of target motion on SAR imaging; detection and imaging of moving targets; SAR imaging of moving targets using time-frequency transforms. Time-frequency transform for analysis of micro-doppler phenomena: vibration induced micro-doppler; rotation induced micro-doppler; examples. Trends in time-frequency transforms for radar applications

适用于大学生

地震成像空频法/space-frequency/偏移成像脉冲响应

本方法旨在评估用于电气设备的部件。它的目的是确定部件承受中度至重度振动的能力，这些振动是由运输或现场操作产生的运动结果。这种类型的振动可能会干扰操作特性，特别是如果重复的压力导致疲劳。这是一项用于部件鉴定的破坏性试验。它通常适用于空腔型封装。

rolling-bear-fault-diagnosis-based-wavelet-time-frequency-map-and-CNN The wavelet time-frequency map is obtained from the original vibration signal, and then input into CNN to realize fault diagnosis, the test set has the highest diagnostic accuracy 在matlab和pytorch0.4下，通过matlab对原始振动信号求取小波时频图，然后输入进pytorchCNN实现故障诊断，测试集诊断精度最高达99.5%。代码出售的、出售的、出售的，需要的加qq2919218574.详细见我的博客： 小波时频数据为：链接: 提取码: xhqz