## Random Processes |

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### Contents

FOUNDATIONS OF PROBABILITY | 1-1 |

RANDOM PROCESSES | 2-2 |

FURTHER EXAMPLES OF PROBABILITY AND RANDOM PROCESSES | K-1 |

7 other sections not shown

### Common terms and phrases

antenna application approximation assume average called characteristic function complex numbers computed consider constant continuous correlation function corresponding decision problem decision rule decision theory defined definition denoted density function detection discrete distribution function elements equation example exists expected value follows formula frequency Gaussian process given Hilbert space independent infinite integral interval likelihood ratio limit linear combination linear filter Markov Process mathematical mathematician matrix mean square error minimize multivariate noise figure noise temperature non-negative notation observation obtained operator optimum filter output parameter prediction probability density probability distribution probability measure properties quadratic mean random process random variables real line real number real random receiver input result sample sequence shown signal solution specified spectral density spectrum stationary statistics stochastic process subset subspace theorem tion uncorrelated vector space voltage white Gaussian noise Wiener xs(t zero