Probability and Random Processes: Using MATLAB with Applications to Continuous and Discrete Time Systems |
Contents
Chapter | 1 |
Introduction to Probability | 16 |
Random Variables | 42 |
Copyright | |
13 other sections not shown
Common terms and phrases
amplitude assume autocorrelation function calculate chapter coefficients coin consider correlation covariance crosscorrelation crosscorrelation function cumulative probability distribution defined Definition denote Determine discrete random variable Edit Windows Help elements equal equation ergodic event Example expected value experimental outcome frequency fx(x Gaussian random independent input integral interval joint probability density linear prediction Markov chain matched filter MATLAB MATLAB program mean square member function method Note occurs output parameters periodogram plot Poisson power spectral density probability density function probability distribution function problem properties pulse Px(x Pxy(x Quiz random numbers random process random process X(t random sequence random vector Rxx(T sample space selected sense stationary random shown in Figure signal spectral estimate spectrum stationary random process Suppose Sxx f t₁ t₂ transition matrix variance waveform white noise wide sense stationary Wiener filter X₁ zero mean μχ σχ