前辅文
 Part 1. Matrices and Linear Dynamical Systems
  Chapter 1. Autonomous Linear Differential and Difference Equations
   1.1. Existence of Solutions
   1.2. The Real Jordan Form
   1.3. Solution Formulas
   1.4. Lyapunov Exponents
   1.5. The Discrete-Time Case: Linear Difference Equations
   1.6. Exercises
   1.7. Orientation, Notes and References
  Chapter 2. Linear Dynamical Systems in Rd
   2.1. Continuous-Time Dynamical Systems or Flows
   2.2. Conjugacy of Linear Flows
   2.3. Linear Dynamical Systems in Discrete Time
   2.4. Exercises
   2.5. Orientation, Notes and References
  Chapter 3. Chain Transitivity for Dynamical Systems
   3.1. Limit Sets and Chain Transitivity
   3.2. The Chain Recurrent Set
   3.3. The Discrete-Time Case
   3.4. Exercises
   3.5. Orientation, Notes and References
  Chapter 4. Linear Systems in Projective Space
   4.1. Linear Flows Induced in Projective Space
   4.2. Linear Difference Equations in Projective Space
   4.3. Exercises
   4.4. Orientation, Notes and References
  Chapter 5. Linear Systems on Grassmannians
   5.1. Some Notions and Results from Multilinear Algebra
   5.2. Linear Systems on Grassmannians and Volume Growth
   5.3. Exercises
   5.4. Orientation, Notes and References
 Part 2. Time-Varying Matrices and Linear Skew Product Systems
  Chapter 6. Lyapunov Exponents and Linear Skew Product Systems
   6.1. Existence of Solutions and Continuous Dependence
   6.2. Lyapunov Exponents
   6.3. Linear Skew Product Flows
   6.4. The Discrete-Time Case
   6.5. Exercises
   6.6. Orientation, Notes and References
  Chapter 7. Periodic Linear Differential and Difference Equations
   7.1. Floquet Theory for Linear Difference Equations
   7.2. Floquet Theory for Linear Differential Equations
   7.3. The Mathieu Equation
   7.4. Exercises
   7.5. Orientation, Notes and References
  Chapter 8. Morse Decompositions of Dynamical Systems
   8.1. Morse Decompositions
   8.2. Attractors
   8.3. Morse Decompositions, Attractors, and Chain Transitivity
   8.4. Exercises
   8.5. Orientation, Notes and References
  Chapter 9. Topological Linear Flows
   9.1. The Spectral Decomposition Theorem
   9.2. Selgrade’s Theorem
   9.3. The Morse Spectrum
   9.4. Lyapunov Exponents and the Morse Spectrum
   9.5. Application to Robust Linear Systems and Bilinear Control Systems
   9.6. Exercises
   9.7. Orientation, Notes and References
  Chapter 10. Tools from Ergodic Theory
   10.1. Invariant Measures
   10.2. Birkhoff’s Ergodic Theorem
   10.3. Kingman’s Subadditive Ergodic Theorem
   10.4. Exercises
   10.5. Orientation, Notes and References
  Chapter 11. Random Linear Dynamical Systems
   11.1. The Multiplicative Ergodic Theorem (MET)
   11.2. Some Background on Projections
   11.3. Singular Values, Exterior Powers, and the Goldsheid-Margulis Metric
   11.4. The Deterministic Multiplicative Ergodic Theorem
   11.5. The Furstenberg-Kesten Theorem and Proof of the MET in Discrete Time
   11.6. The Random Linear Oscillator
   11.7. Exercises
   11.8. Orientation, Notes and References
 Bibliography
 Index