数据信号处理技术能够将电子设备所采集到的原始数据进行滤波处理，将无效数据进行剔除，将有效数据信息进行信号转化。Matlab是一款商业数学软件，用于数据分析、无线通信、深度学习、图像处理与计算机视觉等领域。用Matlab进行数据信号处理可以更加快速有效。DSP的历史可以追溯到1936年PCM(Pulse Code Modulation)技术的发明和Dudley发明声音编码器(Voice Coder)时期。1942年，当因数学难度而闻名的Wiener预测理论用于天气预报时，人们就感到必须将连续时间函数改进为离散时间函数。从理论上，Levinson虽然给出了由连续时间域向离散时间域转换的可能性，但因当时计算机技术尚不完善，Levinson的算法未能得到实际的应用。20世纪50年代，计算机技术开始普及。60年代，Z变换成为描述线性离散时间系统的基本工具，并指导了数字滤波器的设计。20世纪70年代，VLSP芯片两大成功的范例才使得数字信号处理引起了社会的广泛关注: 首先是以Levinson算法为中心的声音的线性预测编码(Linear Predictive Coding，LPC)，1978年美国德州仪器公司(TI)将该算法作为滤波器开发出LSI芯片; 第二是贝尔实验室开发的，用于在长途电话中消除回声现象的回声消除器(EchoCanceller)。回声消除器的核心是一种应用LSM算法后的自适应滤波器，滤波器解决了长话系统中，虽然信号统计量是未知的，但可由数据推出滤波系数。今天，自适应滤波器还用作通信线路均衡器，电视图像重影(Ghost)的消除器，以及抑制有源噪声等方面。DSP的另一大支柱理论是快速傅里叶变换(Fast Fourier Transform，FFT)。起初由Cooley和Tukey发表，FFT实际上可以追溯到Gauss时代，Cooley和Tukey也表示，在1942年他们也发现过，但在手摇计算时代，计算量为数十万数量级是一件不可想象的事情。也正是由于计算机技术的应用，FFT不但没被作为一个纯数学上的发现而埋没，反而在MIT林肯实验室中更成熟，并广泛被应用在信号流程图解释、bit位变换分析、定位计算和NlegN的计算量研究上。
Data signal processing technology can filter the original data collected by electronic equipment, remove invalid data, and transform effective data information into signal. Matlab is a commercial mathematics software used in data analysis, wireless communication, deep learning, image processing and computer vision. Using Matlab for data signal processing can be more rapid and effective.
The history of DSP can be traced back to the invention of Pulse Code Modulation (PCM) in 1936 and Dudley's invention of the Voice Coder. When Wiener's theory of prediction, known for its mathematical difficulty, was applied to weather forecasting in 1942, it was felt that the continual-time function had to be improved into a discrete-time function. Theoretically, although Levinson gave the possibility of converting from continuous time domain to discrete time domain, because of the imperfect computer technology at that time, Levinson's algorithm could not get practical application. In the 1950s, computer technology became widespread. In the 1960s, the Z-transform became a fundamental tool for describing linear discrete-time systems and guided the design of digital filters. In the 1970s, two successful examples of VLSP chips brought digital signal processing to the attention of the society: The first is Linear Predictive Coding (LPC) based on Levinson's algorithm. In 1978, Texas Instruments (TI) developed LSI chip by using this algorithm as a filter. The second is the EchoCanceller, developed by bell LABS, which cancels echoes in long distance
calls. The core of echo canceller is an adaptive filter based on LSM algorithm. This filter solves the problem in long speech system where the signal statistics are unknown, but the optimal filter coefficients can be derived from the data. Today, adaptive filters are also used as equalizer for communication lines, Ghost eliminator for television images, and active noise suppression. Another pillar of DSP theory is Fast Fourier Transform (FFT). Originally published by Cooley and Tukey, FFT actually dates back to Gauss's time. Cooley and Tukey also stated that they had discovered it in 1942, but in the era of hand computing, computations of the order of hundreds of thousands would have been unthinkable. Because of the application of computer technology, FFT was not buried as a pure mathematical discovery, but became more mature in MIT Lincoln Laboratory, and eventually widely used in signal flow chart interpretation, bit transformation analysis, positioning calculation and NlegN computation research.