1. Introduction. - 1. 1 Classification Prediction and Identification: an Informal Description. - 1. 2 Part I: Known Sources. - 1. 3 Part II: Applications. - 1. 4 Part III: Unknown Sources. - 1. 5 Part IV: Connections. - I Known Sources. - 2. Premonn Classification and Prediction. - 3. Generalizations of the Basic Premonn. - 4. Mathematical Analysis. - 5. System Identification by the Predictive Modular Approach. - II Applications. - 6. Implementation Issues. - 7. Classification of Visually Evoked Responses. - 8. Prediction of Short Term Electric Loads. - 9. Parameter Estimation for and Activated Sludge Process. - III Unknown Sources. - 10. Source Identification Algorithms. - 11. Convergence of Parallel Data Allocation. - 12. Convergence of Serial Data Allocation. - IV Connections. - 13. Bibliographic Remarks. - 14. Epilogue. - Appendices. - A Mathematical Concepts. - A. 1 Notation. - A. 2 Probability Theory. - A. 3 Sequences of Bernoulli Trials. - A. 4 Markov Chains. - References. Language: English