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9789812565914

Stochastic Systems in Merging Phase Space

by ;
  • ISBN13:

    9789812565914

  • ISBN10:

    9812565914

  • Format: Hardcover
  • Copyright: 2005-12-21
  • Publisher: World Scientific Pub Co Inc
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Table of Contents

Preface v
Markov and Semi-Markov Processes
1(34)
Preliminaries
1(1)
Markov Processes
2(17)
Markov Chains
2(4)
Continuous-Time Markov Processes
6(4)
Diffusion Processes
10(1)
Processes with Independent Increments
11(3)
Processes with Locally Independent Increments
14(1)
Martingale Characterization of Markov Processes
15(4)
Semi-Markov Processes
19(6)
Markov Renewal Processes
19(2)
Markov Renewal Equation and Theorem
21(2)
Auxiliary Processes
23(1)
Compensating Operators
24(1)
Martingale Characterization of Markov Renewal Processes
25(1)
Semimartingales
25(3)
Counting Markov Renewal Processes
28(3)
Reducible-Invertible Operators
31(4)
Stochastic Systems with Switching
35(32)
Introduction
35(1)
Stochastic Integral Functionals
36(4)
Increment Processes
40(3)
Stochastic Evolutionary Systems
43(3)
Markov Additive Processes
46(1)
Stochastic Additive Functionals
47(3)
Random Evolutions
50(9)
Continuous Random Evolutions
50(4)
Jump Random Evolutions
54(2)
Semi-Markov Random Evolutions
56(3)
Extended Compensating Operators
59(2)
Markov Additive Semimartingales
61(6)
Impulsive Processes
61(2)
Continuous Predictable Characteristics
63(4)
Stochastic Systems in the Series Scheme
67(36)
Introduction
67(1)
Random Evolutions in the Series Scheme
68(6)
Continuous Random Evolutions
68(4)
Jump Random Evolutions
72(2)
Average Approximation
74(7)
Stochastic Additive Functionals
74(5)
Increment Processes
79(2)
Diffusion Approximation
81(9)
Stochastic Integral Functionals
81(3)
Stochastic Additive Functionals
84(4)
Stochastic Evolutionary Systems
88(1)
Increment Processes
89(1)
Diffusion Approximation with Equilibrium
90(13)
Locally Independent Increment Processes
90(3)
Stochastic Additive Functionals with Equilibrium
93(4)
Stochastic Evolutionary Systems with Semi-Markov Switching
97(6)
Stochastic Systems with Split and Merging
103(36)
Introduction
103(1)
Phase Merging Scheme
104(12)
Ergodic Merging
104(6)
Merging with Absorption
110(2)
Ergodic Double Merging
112(4)
Average with Merging
116(6)
Ergodic Average
117(2)
Average with Absorption
119(1)
Ergodic Average with Double Merging
120(1)
Double Average with Absorption
121(1)
Diffusion Approximation with Split and Merging
122(12)
Ergodic Split and Merging
123(3)
Split and Merging with Absorption
126(2)
Ergodic Split and Double Merging
128(2)
Double Split and Merging
130(2)
Double Split and Double Merging
132(2)
Integral Functionals in Split Phase Space
134(5)
Ergodic Split
134(3)
Double Split and Merging
137(1)
Triple Split and Merging
138(1)
Phase Merging Principles
139(54)
Introduction
139(1)
Perturbation of Reducible-Invertible Operators
140(10)
Preliminaries
140(1)
Solution of Singular Perturbation Problems
141(9)
Average Merging Principle
150(10)
Stochastic Evolutionary Systems
151(1)
Stochastic Additive Functionals
152(2)
Increment Processes
154(2)
Continuous Random Evolutions
156(1)
Jump Random Evolutions
157(2)
Random Evolutions with Markov Switching
159(1)
Diffusion Approximation Principle
160(13)
Stochastic Integral Functionals
161(4)
Continuous Random Evolutions
165(4)
Jump Random Evolutions
169(3)
Random Evolutions with Markov Switching
172(1)
Diffusion Approximation with Equilibrium
173(9)
Locally Independent Increment Processes
174(1)
Stochastic Additive Functionals
175(1)
Stochastic Evolutionary Systems with Semi-Markov Switching
176(6)
Merging and Averaging in Split State Space
182(6)
Preliminaries
182(2)
Semi-Markov Processes in Split State Space
184(2)
Average Stochastic Systems
186(2)
Diffusion Approximation with Split and Merging
188(5)
Ergodic Split and Merging
188(1)
Split and Double Merging
189(1)
Double Split and Merging
190(1)
Double Split and Double Merging
191(2)
Weak Convergence
193(26)
Introduction
193(1)
Preliminaries
193(3)
Pattern Limit Theorems
196(13)
Stochastic Systems with Markov Switching
196(5)
Stochastic Systems with Semi-Markov Switching
201(4)
Embedded Markov Renewal Processes
205(4)
Relative Compactness
209(7)
Stochastic Systems with Markov Switching
209(3)
Stochastic Systems with Semi-Markov Switching
212(1)
Compact Containment Condition
213(3)
Verification of Convergence
216(3)
Poisson Approximation
219(24)
Introduction
219(1)
Stochastic Systems in Poisson Approximation Scheme
220(11)
Impulsive Processes with Markov Switching
220(5)
Impulsive Processes in an Asymptotic Split Phase Space
225(3)
Stochastic Additive Functionals with Semi-Markov Switching
228(3)
Semimartingale Characterization
231(12)
Impulsive Processes as Semimartingales
232(5)
Stochastic Additive Functionals
237(6)
Applications I
243(26)
Absorption Times
243(6)
Stationary Phase Merging
249(4)
Superposition of Two Renewal Processes
253(5)
Semi-Markov Random Walks
258(11)
Introduction
258(1)
The algorithms of approximation for SMRW
259(3)
Compensating Operators
262(3)
The singular perturbation problem
265(2)
Stationary Phase Merging Scheme
267(2)
Applications II
269(18)
Birth and Death Processes and Repairable Systems
269(7)
Introduction
269(1)
Diffusion Approximation
270(2)
Proofs of the Theorems
272(4)
Levy Approximation of Impulsive Processes
276(11)
Introduction
276(2)
Levy Approximation Scheme
278(4)
Proof of Theorems
282(5)
Problems to Solve
287(14)
Appendix A Weak Convergence of Probability Measures
301(4)
A.1 Weak Convergence
301(2)
A.2 Relative Compactness
303(2)
Appendix B Some Limit Theorems for Stochastic Processes
305(6)
B.1 Two Limit Theorems for Semimartingales
305(3)
B.2 A Limit Theorem for Composed Processes
308(3)
Appendix C Some Auxiliary Results
311(4)
C.1 Backward Recurrence Time Negligibility
311(1)
C.2 Positiveness of Diffusion Coefficients
312(3)
Bibliography 315(10)
Notation 325(4)
Index 329

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