Location:Training / Testing and Measurement / Random signal analysis / Random Signal Analysis 33

This course is a basic course for electronic information undergraduate majors that organically integrates random signal analysis, signal detection and estimation. Emphasizing the intuitive understanding of concepts, carefully designing some easy-to-understand examples to illustrate concepts; emphasizing the cultivation of practical abilities, introducing statistical analysis methods based on MA TLAB, including probability distributions, estimation of numerical features, etc., and giving a large number of MATLAB The implementation program also adds an introduction to the basic theory of Monte Carlo simulation in the textbook, and how to use the Monte Carlo method to simulate and analyze the performance of the system.
Divided into 9 chapters, the content includes the basis of random variables, basic concepts of random processes, linear transformation of random processes, nonlinear transformation of random processes, narrow-band random processes, Markov processes and Poisson processes, estimation theory, detection theory and noise Detection of medium signals. Each chapter is accompanied by exercises, computer assignments, and experiments.
It is suitable for undergraduate electronic information majors in ordinary colleges and universities.