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Digital signal processing technology

Technology for converting analog information into digital information
Digital signal processing technology is a technology that converts analog information (such as sound, video and pictures) into digital information. DSP usually refers to the chip or processor They may also be used to process this information and then output it as analog information.
Broadly speaking, digital signal processing technology refers to the application and implementation technology of digital signal processing theory. It is based on and composed of digital signal processing theory, hardware technology and software technology, and studies digital signal processing algorithms and their implementation methods.
Chinese name
Digital signal processing technology
Foreign name
Digital signal processing technology

Advantages and disadvantages

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Advantages of DSP:
can Program control : Easy to modify
Good stability:
Good repeatability:
Good anti-interference performance: large tolerance between 0/1 levels
realization adaptive algorithm
System characteristics with input signal Change
Low power consumption
system Fast development and low price
Disadvantages of DSP:
Analog signal processing Irreplaceability of
Most signals in nature are analog signals
Reasons why high-frequency signals cannot be digitally processed
(1) ADC is not fast enough
(2) Complex in real-time applications

Development of DSP

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The history of DSP can be traced back to the invention of PCM (Pulse Code Modulation) technology in 1936 and the invention of Voice Coder by Dudley. In 1942, when Wiener forecasting theory, which is famous for its mathematical difficulty, was applied to weather forecasting, people felt that it was necessary to improve the continuous time function into a discrete time function. In theory, Levinson gave the possibility of transforming from continuous time domain to discrete time domain, but because the computer technology was not perfect at that time, Levinson's algorithm could not be applied in practice.
In the 1950s, computer technology began to be popularized. In the 1960s, Z-transform became a basic tool for describing linear discrete-time systems and guided digital filter Design.
In the 1970s, the two successful examples of VLSP chip made digital signal processing cause widespread concern in society: the first is the Linear Predictive Coding (LPC) of sound centered on Levinson algorithm, which was developed by Texas Instruments (TI) as a filter in 1978; The second is developed by Bell Laboratories for Long distance call EchoCanceller for eliminating echo phenomenon. The core of echo canceller is a kind of echo canceller Adaptive filter This filter solves the problem that in the long-distance telephone system, although the signal statistics are unknown, the optimal filter coefficients can be derived from the data. The adaptive filter is also used as equalizer of communication lines, ghost eliminator of TV images, and active noise suppression.
Another pillar theory of DSP is fast Fourier transform (Fast Fourier Transform, FFT). Originally published by Cooley and Tukey, FFT can actually be traced back to the Gauss era. Cooley and Tukey also said that they also found it in 1942, but in the era of hand computing, it is unimaginable that the amount of computing is tens of thousands of orders of magnitude. It is precisely because of the application of computer technology that FFT has not been buried as a purely mathematical discovery, but has become more mature in the MIT Lincoln Laboratory, and has finally been widely used in signal flow chart interpretation, bit bit transformation analysis, positioning calculation, and research on computational complexity of NyegN.

Implementation of DSP

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(1) Software realization: the theory of using software to realize a certain aspect of signal processing on a general-purpose computer.
(2) Hardware implementation: general or special DSP chip And other ICs constitute the target system to meet the requirements of digital signal processing tasks.