## Adaptation and Learning in Automatic SystemsAdaptation and Learning in Automatic Systems |

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### Contents

5 | |

17 | |

Chapter 3 Adaptation and Learning | 44 |

Chapter 4 Pattern Recognition | 76 |

Chapter 5 Identification | 119 |

Chapter 6 Filtering | 147 |

Chapter 7 Control | 176 |

Chapter 8 Reliability | 210 |

Chapter 9 Operations Research | 229 |

Chapter 10 Games and Automata | 248 |

Epilogue | 286 |

289 | |

Mathematics in Science and Engineering | 293 |

### Common terms and phrases

adaptation and learning adaptive approach adaptive filter Akad algorithms of adaptation algorithms of learning algorithms of optimization algorithms of training application aſn assume automatic control automaton best algorithms block diagram Braverman characteristics cInj coefficients components computers considered constraints continuous algorithms control systems convergence convex function corresponding criterion of optimality defined described determine discrete systems estimate finite automata functional J(c gradient identification IEEE Trans input signal iterative methods Kibern linear loss function Math mathematical expectation matrix minimization mixed strategies Moscow noise nonlinear obtain operation optimal control optimal value optimal vector optimization problems parameters pattern class pattern recognition perceptron performance index plant priori information probabilistic probability density function problem of optimality rate of convergence realization reliability Remote Contr Russian search algorithm self-learning shown in Fig solution solving statistical stochastic approximation strategies theory threshold element tion Tsypkin unknown uſn USSR vector cº Volterra series