In this chapter we define random processes via the associated ensemble of signals, and be gin to explore their properties. In successive chapters we use random processes as models for random or uncertain signals that arise in communication, control and signal processing applications.
Random Processes • Sample values of a random process at time t 1, t 2, …, are a collection of random variables {X(t 1), X(t 2), …}. – Continuous-time random process: – Discrete-time random process: t t (set of real numbers) (set of integers) • Statistical description of random process X(t)
- [PDF]
RANDOM SIGNALS - DTU
Working in frequency domain is a powerful technique in signal processing. While the spectrum is directly related to the deterministic signals, the spectrum of a ran-dom signal is defined through its correlation function. This is a “natural” conse-quence of the “uncertainty”, which is characteristic to random signals.
随机信号分析 - 科学文库
《随机信号分析（英文版）（Random Signal Processing）》共分为六章，主要内容包括概率论知识回顾、随机过程及其特征描述、随机过程的线性变换、平稳窄带随机过程、平稳随机过程的非线性变换、非平稳随机过程的特征描述等。
随机信号分析（Random Signal Analysis 中英双语） - ChaoXing
The purpose of the course "random signal processing" is analyzing and utilizing the underlying structure in random signals. These types of signals are pervasive in communication, control and signal processing. The basic tools we utilize are probability models and statistical inference.
离散随机信号处理 - 百度百科
discrete random signal processing 利用数字运算，对离散随机信号进行各种滤波处理、离散变换和谱分析。 随机信号是一种非确定性的信号，如热 噪声信号发生器 输出的电信号，飞行器起飞时的结构振动，以及起伏海面的波动高度等。
Random Processes: Filtering, Estimation, and Detection
In this book, Lonnie Ludeman, an award-winning authority in digital signal processing, joins the fundamentals of random processes with the standard techniques of linear and nonlinear systems analysis and hypothesis testing to give signal estimation techniques, specify optimum estimation procedures, provide optimum decision rules for ...
9 - Random Signals and Processes - Cambridge University Press
2016年5月5日 · The primary goal of this chapter is to introduce the principles of random signals and processes for in-depth understanding of the processing methods. We will introduce the concept of probability and will discuss different standard distribution functions used for the analysis of random signals.
A random signal x[n] can be real-valued, complex-valued, etc. NB: signals can be continuous or discrete in time as well as amplitude Digital signal = discrete in time and amplitude
Random Signal Processing - MATLAB & Simulink Books
Random Signal Processing covers random signals and random processes along with estimation of probability density function, energy spectral density, and power spectral density. The properties of random processes and signal modeling are discussed with basic communication theory estimation and detection.