To realize digital processing of complex signals with limited storage capacity, it is necessary to sample and quantize the signals. The specific steps are as follows:

signal sampling

The continuous analog signal is discretized according to a certain time interval, and the signal value in the discrete time is obtained by sampling. The sampling theorem shows that in order to avoid sampling distortion, the sampling frequency should be at least twice the highest frequency of the signal.

quantify

Mapping sampled signal values to a limited number of discrete values is called quantization. Quantization error will affect the quality of digital signal, so it is necessary to choose appropriate quantization accuracy according to application requirements.

Compression and coding

Because the sampled and quantized digital signal occupies a large space, it needs to be compressed and encoded to save storage space and transmission bandwidth. Commonly used compression algorithms include huffman encoding, LZW compression and JPEG compression.

Digital signal processing

For the digital signal obtained by sampling, quantization and compression coding, various digital signal processing algorithms such as digital filtering, spectrum analysis and digital modulation and demodulation can be carried out to realize the digital processing of complex signals.

In a word, the digital processing of complex signals with limited storage capacity needs signal sampling, quantization, compression coding and digital signal processing, and the methods and algorithms of each step need to be selected according to the application requirements.