'T t0' diaporamas de présentation

Lecture 22 Exemplary Inverse Problems including Filter Design

Lecture 22 Exemplary Inverse Problems including Filter Design. Syllabus.

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Lecture 22 Exemplary Inverse Problems including Filter Design

Lecture 22 Exemplary Inverse Problems including Filter Design. Syllabus.

602 views • 52 slides

Simulation and Animation

Simulation and Animation. Collisions. Collisions. Detection. Broad Phase. Bounding Volumes. Key idea: Surround the object with a (simpler) bounding object (the bounding volume). If something does not collide with the bounding volume, it does not collide with the object inside.

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Chapter 5. Ordinary Differential Equation

Chapter 5. Ordinary Differential Equation. ??? ??? , ????? ??? , ???. 5.1 The Elementary Theory of Initial-Value Problems. Definition 5.1 f( x , y ) : Lipschitz condition on set D ? R 2 , ? L > 0 with , ( t , y 1 ), ( t , y 2 ) ? D , L : Lipschitz constant Definition 5.2

719 views • 39 slides

Non-life insurance mathematics

Non-life insurance mathematics. Nils F. Haavardsson, University of Oslo and DNB Skadeforsikring. Overview. N on- life insurance from a financial perspective : for a premium an insurance company commits itself to pay a sum if an event has occured. Contract period.

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Courant and all that

Courant and all that. Consistency, Convergence Stability Numerical Dispersion Computational grids and numerical anisotropy

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Inflation and Monetary Policy (Romer, sections 11.1, 11.2, section 11.6 to 11.9)

Inflation and Monetary Policy (Romer, sections 11.1, 11.2, section 11.6 to 11.9). Inflation and Hyperinflation Term Structure of Interest Rates Control of Monetary Aggregates Interest-rate rules Why did ? > ?* : Dynamic-inconsistency and Seignorage The Costs of Inflation (Do-it your-self).

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Course Outline (Tentative)

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Hypotheses Testing

Hypotheses Testing Example 1 We have tossed a coin 50 times and we got k = 19 heads Should we accept/reject the hypothesis that p = 0.5 (the coin is fair) Null versus Alternative Null hypothesis (H 0 ): p = 0.5

611 views • 22 slides

Lecture 4 MR: 2D Projection Reconstruction, 2D FT

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Optical Flow

Optical Flow. 10-24-2005. Problem. Problems in motion estimation Noise, color (intensity) smoothness, lighting (shadowing effects), occlusion, abrupt movements, etc Approaches: Block matching, Generalized block matching, Optical flow (block-based, Horn-Schunck etc) Bayesian, etc.

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Physics 101: Lecture 16 Rotational Kinematics

471 views • 9 slides