信号处理 -凯发k8网页登录

对信号处理系统进行分析、设计和仿真

mathworks^® 产品为音频、深度学习和信号处理应用提供工作流。您可以结合基于语言的编程和 simulink^® 模块图来预处理、可视化和分析时间序列，开发和调试算法，设计和应用滤波器，以及对系统进行建模和测试。使用 matlab^® coder™ 和 gpu coder™ 将您的凯发官网入口首页的解决方案部署到硬件上。

适用产品：信号处理

signal processing toolbox

执行信号处理和分析

dsp system toolbox

design and simulate streaming signal processing systems

audio toolbox

design and analyze speech, acoustic, and audio processing systems

wavelet toolbox

perform time-frequency and wavelet analysis of signals and images

主题

滤波

数字滤波实践介绍 (signal processing toolbox)
设计、分析和应用数字滤波器，以消除信号中不需要的内容，而不会使数据失真。
multirate filtering in matlab and simulink (dsp system toolbox)
perform multirate filtering using rate conversion objects and blocks.
(dsp system toolbox)
process signals using frame-based processing and compare the performance using simulink profiler.

测量

检测信号的爆发和重大变化 (signal processing toolbox)
使用累积和与变化点检测确定信号的重大变化或爆发。
测量信号相似性 (signal processing toolbox)
比较具有不同采样率或频率成分的信号，测量延迟，并确定测量值中是否有信号。
measure and manage impulse responses (audio toolbox)
capture and analyze impulse response (ir) measurements by using the impulse response measurer.

可视化

使用信号分析器 (signal processing toolbox)
在时域、频域和时频域中可视化、测量、分析和比较信号。
using wavelet time-frequency analyzer app (wavelet toolbox)
learn how to use wavelet time-frequency analyzer app.
signal visualization and measurements in matlab (dsp system toolbox)
visualize and measure signals in the time and frequency domain in matlab® using a time scope and spectrum analyzer.

频谱、时频和多分辨率分析

time-frequency gallery (signal processing toolbox)
examine the features and limitations of the time-frequency analysis functions provided by signal processing toolbox™.
(wavelet toolbox)
perform and interpret time-frequency analysis of signals using the continuous wavelet transform.
estimate the power spectrum in simulink (dsp system toolbox)
compute the power spectrum using the spectrum analyzer and the spectrum estimator blocks.

机器学习和深度学习

(wavelet toolbox)
learn how to develop an alert system for predictive maintenance using wavelet scattering and deep learning.
deep learning for audio applications (audio toolbox)
learn common tools and workflows to apply deep learning to audio applications.
(dsp system toolbox)
use the wavelet scattering block and a pretrained deep learning network to classify audio signals.

建模和仿真

sample- and frame-based concepts (dsp system toolbox)
explore basic signal concepts in the context of a simulink model. learn more about sample-based processing and frame-based processing.
digital up and down conversion for family radio service in matlab (dsp system toolbox)
family radio service (frs) is an improved walkie talkie fm radio system authorized in the united states since 1996.

代码生成和算法加速

(wavelet toolbox)
create and deploy a simulink model for signal classification using wavelet-based features.
(audio toolbox)
generate code to spot keywords using a bidirectional long short-term memory (bilstm) network and mel frequency cepstral coefficient (mfcc) feature extraction.
(signal processing toolbox)
generate a mex function and a standalone executable to perform waveform segmentation on a raspberry pi^®.

精选示例

频域分析实践介绍

使用仿真数据和真实数据执行和解释基本频域信号分析。