## Cognitive Networks: Applications and DeploymentsJaime Lloret Mauri, Kayhan Zrar Ghafoor, Danda B. Rawat, Javier Manuel Aguiar Perez A cognitive network makes use of the information gathered from the network in order to sense the environment, plan actions according to the input, and make appropriate decisions using a reasoning engine. The ability of cognitive networks to learn from the past and use that knowledge to improve future decisions makes them a key area of interest for anyone whose work involves wireless networks and communications. |

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### Contents

Some Preliminary Notions and Facts from Probability Theory | 7 |

Comparison of Random Variables Preferences of Individuals | 63 |

COMPARISON OF R V S AND LIMIT THEOREMS | 79 |

NONLINEAR CRITERIA | 111 |

OPTIMAL PAYMENT FROM THE STANDPOINT OF THE INSURED 125 | 125 |

An individual Risk Model for a Short Period | 137 |

CHAPTERS Conditional Expectations | 191 |

A GENERAL APPROACH TO CONDITIONAL EXPECTATIONS | 215 |

Global Characteristics of the Surplus Process Ruin Models | 363 |

CHAPTERS Survival Distributions | 413 |

Life Insurance Models | 461 |

Annuity Models | 499 |

Premiums and Reserves | 531 |

Reinsurance and Coinsurance | 565 |

Tables | 607 |

Answers to Exercises | 619 |

A Collective Risk Model for a Short Period | 225 |

CHAPTERS Random Processes I Counting and Compound Processes | 269 |

Random Processes II Brownian Motion and Martingales | 329 |