Research on the Application of Machine Learning Big Data Mining Algorithms in Digital Signal Processing

Traditional digital signal processing technology based on DSP and FPGA is more suitable for real-time signal processing, and is limited by data scale and frequency resolution, making it unsuitable for offline data processing, analysis and mining under large-scale data Application. At present, the industrial big data analysis platform can use Spark as a calculation engine for real-time signal processing and offline signal processing acceleration, but the analysis platform lacks mathematical calculation solutions such as digital signal processing suitable for distributed parallel calculation engines. This article is based on time the parity decomposition is selected, and the fast Fourier transform is realized by MATLAB software. Based on an example of the application of the compiled FFT source program, this article analyses the frequency spectrum of discrete-time and continuous-time signals of limited length.