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Constant variance Gaussian processes and Kac-Rice◮ Generic Kac-Rice formula∫ {E {U u } = p t (u) E |ḟ (t)| 1 (0,∞) (ḟ (t)) ∣ }f (t) = u dtT◮ But f (t) and ḟ (t) are independent!
Constant variance Gaussian processes and Kac-Rice◮ Generic Kac-Rice formula∫ {E {U u } = p t (u) E |ḟ (t)| 1 (0,∞) (ḟ (t)) ∣ }f (t) = u dtT◮ But f (t) and ḟ (t) are independent!◮ Notation1 = σ 2 (t), λ(t) ∆ = E{[ḟ (t)] 2 }
Page 4 and 5: Our heroesMarc KacStephen O. Rice19
Page 6 and 7: Real roots of algebraic equations (
Page 10 and 11: Zeroes of complex polynomialsf (z)
Page 12 and 13: Zeroes of complex polynomialsf (z)
Page 14 and 15: Thinking more generally:1: f : R N
Page 16 and 17: Thinking more generally:1: f : R N
Page 18 and 19: The original (non-specific) Rice fo
Page 30 and 31: Constructing Gaussian Processes◮
Page 32 and 33: Constructing Gaussian Processes◮
Page 34 and 35: Existence of Gaussian processesTheo
Page 36 and 37: Existence of Gaussian processesTheo
Page 38 and 39: Example: The Brownian sheet on R NE
Page 40 and 41: Example: The Brownian sheet on R NE
Page 42 and 43: Constant variance Gaussian processe
Page 50 and 51: Gaussian Kac-Rice with no simplific
Page 52 and 53: Gaussian Kac-Rice with no simplific
Page 54 and 55: Some pertinent thoughts◮ Real roo
Page 56 and 57: Some pertinent thoughts◮ Real roo
Page 58 and 59: The Kac-Rice “Metatheorem”
Page 60 and 61: The Kac-Rice “Metatheorem”◮ T
Page 62 and 63: The Kac-Rice “Metatheorem”◮ T
Page 68 and 69: The Kac-Rice Conditions (the fine p
Page 70 and 71: Higher (factorial) moments◮ Facto
Page 72 and 73: The Gaussian case: What can/can’t
Page 80 and 81: The Gaussian-related casef (t) = (f
Page 82 and 83: The Gaussian-related casef (t) = (f
Page 84 and 85: The Gaussian Kinematic Formula (GKF
Page 86 and 87: The perturbed-Gaussian case◮ A ph
Page 88 and 89: Applications I: Exceedence probabil
Page 90 and 91: Applications I: Exceedence probabil
Page 92 and 93: Applications II: Local maxima on th
Page 94 and 95: Applications II: Local maxima on th
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Applications II: Local maxima on th
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Applications III: Local maxima on M
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Applications III: Local maxima on M
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Applications IV: Longuet-Higgins an
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Applications V: Higher moments and
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Applications VI: Poisson limits and
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Applications VI: Poisson limits and
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Applications VII: Eigenvalues of ra
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Applications VII: Eigenvalues of ra
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Appendix I: The canonical Gaussian
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Exceedence probabilities for canoni
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◮ We needP { sup〈U, t〉 ≥ u/
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Appendix II: Stationary and isotrop
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Appendix II: Stationary and isotrop
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◮ Elementary considerations give{
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◮ Elementary considerations give{
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Appendix III: Regularity of Gaussia
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Appendix III: Regularity of Gaussia
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Special cases of the entropy result
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Special cases of the entropy result
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Appendix IV: Borell-Tsirelson inequ
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Appendix IV: Borell-Tsirelson inequ
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