{"text_format":"2","workbook":"xls","n_sheets":1,"sheets":["report2"],"not_rendered":{"charts":0,"images":0,"macros":0,"external_links":1,"defined_names":1,"comments":0,"pivot_tables":0},"unopened":[],"bounds":{"document_bytes":16777216,"sheet_cells":100000,"run_cost":"one","rows_first":2000,"rows_last":500,"rows_between":2000,"halvings":0,"cell_chars":16384,"cell_head_chars":4096},"cells_cut":0,"cells_raw":0,"read":"whole","date_system":"1900","formulas":"cached_only"}

{"sheet":"report2","index":0,"n_rows":27,"n_cols":5,"rows_kept":27,"cut":false,"hidden":false,"merged":[[0,2,0,3],[0,4,0,5],[1,2,1,3],[1,4,1,5],[2,2,2,3],[2,4,2,5],[3,2,3,3],[5,2,5,3],[9,2,9,3],[10,2,10,3],[11,2,11,3],[13,2,13,3],[15,2,15,3],[16,2,16,3],[20,2,20,3]],"flags":["formulas_cached_only"]}
[null,"1.","Record Nr.",null,"UNINA9910139467503321"]
[null,null,"Autore",null,"Harlamov Boris"]
[null,null,"Titolo",null,"Continuous semi-Markov processes [[electronic resource] /] / Boris Harlamov"]
[null,null,"Pubbl/distr/stampa",null,"London, : ISTE"]
[{"$nulls":4},"Hoboken, NJ, : Wiley, 2008"]
[null,null,"ISBN",null,"1-282-16484-8"]
[{"$nulls":4},"9786612164842"]
[{"$nulls":4},"0-470-61092-1"]
[{"$nulls":4},"0-470-39351-3"]
[null,null,"Descrizione fisica",null,"1 online resource (377 p.)"]
[null,null,"Collana",null,"ISTE ; ; v.8"]
[null,null,"Disciplina",null,"519.2/33"]
[{"$nulls":4},"519.233"]
[null,null,"Soggetti",null,"Markov processes"]
[{"$nulls":4},"Renewal theory"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Description based upon print version of record."]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"Continuous Semi-Markov Processes; Contents; Introduction; Chapter 1. Stepped Semi-Markov Processes; 1.1. Random sequence; 1.2. Markov chain; 1.3. Two-dimensional Markov chain; 1.4. Semi-Markov process; 1.5. Stationary distributions; Chapter 2. Sequences of First Exit Times and Regeneration Times; 2.1. Basic maps; 2.2. Markov times; 2.3. Deducing sequences; 2.4. Correct exit and continuity; 2.5. Time of regeneration; Chapter 3. General Semi-Markov Processes; 3.1. Definition of a semi-Markov process; 3.2. Transition function of a SM process; 3.3. Operators and SM walk"]
[{"$nulls":4},"3.4. Operators and SM process3.5. Criterion of Markov property for SM processes; 3.6. Intervals of constancy; Chapter 4. Construction of Semi-Markov Processes using Semi-Markov Transition Functions; 4.1. Realization of an in nite system of pairs; 4.2. Extension of a measure; 4.3. Construction of a measure; 4.4. Construction of a projective system of measures; 4.5. Semi-Markov processes; Chapter 5. Semi-Markov Processes of Diffusion Type; 5.1. One-dimensional semi-Markov processes of diffusion type; 5.1.1. Differential equation; 5.1.2. Construction SM process"]
[{"$nulls":4},"5.1.3. Some properties of the process5.2. Multi-dimensional processes of diffusion type; 5.2.1. Differential equations of elliptic type; 5.2.2. "]
[{"$nulls":4},"Neighborhood of arbitrary form; 5.2.3. Neighborhood of spherical form; 5.2.4. Characteristic operator; Chapter 6. Time Change and Semi-Markov Processes; 6.1. Time change and trajectories; 6.2. Intrinsic time and traces; 6.3. Canonical time change; 6.4. Coordination of function and time change; 6.5. Random time changes; 6.6. Additive functionals; 6.7. Distribution of a time run along the trace; 6.8. Random curvilinear integrals"]
[{"$nulls":4},"6.9. Characteristic operator and integral6.10. Stochastic integral; 6.10.1. Semi-martingale and martingale; 6.10.2. Stochastic integral; 6.10.3. Ito-Dynkin's formula; Chapter 7. Limit Theorems for Semi-Markov Processes; 7.1. Weak compactness and weak convergence; 7.2. Weak convergence of semi-Markov processes; Chapter 8. Representation of a Semi-Markov Process as a Transformed Markov Process; 8.1. Construction by operator; 8.2. Comparison of processes; 8.3. Construction by parameters of Lévy formula; 8.4. Stationary distribution; Chapter 9. Semi-Markov Model of Chromatography"]
[{"$nulls":4},"9.1. Chromatography9.2. Model of liquid column chromatography; 9.3. Some monotone Semi-Markov processes; 9.4. Transfer with diffusion; 9.5. Transfer with final absorption; Bibliography; Index"]
[null,null,null,"Sommario/riassunto","This title considers the special of random processes known as semi-Markov processes. These possess the Markov property with respect to any intrinsic Markov time such as the first exit time from an open set or a finite iteration of these times.The class of semi-Markov processes includes strong Markov processes, Lévy and Smith stepped semi-Markov processes, and some other subclasses. Extensive coverage is devoted to non-Markovian semi-Markov processes with continuous trajectories and, in particular, to semi-Markov diffusion processes. Readers looking to enrich their knowledge on Markov proce"]