'Statistical properties' presentation slideshows

Announcement

Announcement. T-lab accounts should have been set up Assignment upload webpage up Homework 1 released, due in two weeks. Review. What is security: history and definition Security policy, mechanisms and services Security models. Outline. Overview of Cryptography

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Cellular Automata

Cellular Automata. Biologically Inspired Computing Various credits for these slides, which have in part been adapted from slides by: Ajit Narayanan, Rod Hunt, Marek Kopicki. Cellular Automata. A CA is a spatial lattice of N cells, each of which is one of k states at time t .

1.13k views • 62 slides

MATHEMATICAL PROPERTIES OF NETWORK OF PROTEIN INTERACTIONS

MATHEMATICAL PROPERTIES OF NETWORK OF PROTEIN INTERACTIONS . Abhishek Rathod CS 374 Algorithms in Biology Prof. Serafim Batzoglou . Broad plan . Part A Basics of Protein Interaction Networks and some background

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Food Webs

Food Webs. A food web describes the feeding relations among organisms in all or part of a community Usually those feeding relations are described by a diagram linking the consumers and consumed with lines or arrows. Food Webs. Example of a food web. Food Webs.

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STOCHASTIC PROCESSES AND MODELS

STOCHASTIC PROCESSES AND MODELS. EigenAnalysis. Read Appendices E, B, C and others! Let R be an M x M autocorrelation matrix corresponding to u (n): M x1 The eigenvalue problem is There are M eigenvalues and M eigenvectors of R. Rewriting or ?eigenvalues { ? i }.

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Announcement

Announcement. Grading adjusted 10% participation and two exams 20% each Newsgroup up Assignment upload webpage up Homework 1 will be released over the weekend. Review. What is security: history and definition Security policy, mechanisms and services Security models. Outline.

616 views • 42 slides

Symmetric Encryption Algorithms

946 views • 40 slides

Putting the Power of Modern Applied Stochastics into DFA

Putting the Power of Modern Applied Stochastics into DFA. Peter Blum 1)2) , Michel Dacorogna 2) , Paul Embrechts 1). 1) ETH Zurich Department of Mathematics CH-8092 Zurich (Switzerland) www.math.ethz.ch/finance. 2) Zurich Insurance Company Reinsurance CH-8022 Zurich (Switzerland)

511 views • 40 slides

Developments in the Latest Version of the RegCM

Developments in the Latest Version of the RegCM. Jeremy Pal Contributors: Filippo Giorgi, Xunqiang Bi, Nellie Elguindi, Elfatih Eltahir, Raquel Francisco, Sonia Seneviratne, Eric Small, Fabien Solmon, and many more. Latest Developments. User-friendliness Preprocessor Terrain and landuse

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Multiscale transforms : wavelets, ridgelets, curvelets, etc.

Multiscale transforms : wavelets, ridgelets, curvelets, etc. Outline : The Fourier transform Time-frequency analysis and the Heisenberg principle Cauchy Schwartz inequality The continuous wavelet transform 2D wavelet transform Anisotropic frames : Ridgelets, curvelets, etc.

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Approaches for the generation of femtosecond x-ray pulses

Approaches for the generation of femtosecond x-ray pulses. Zhirong Huang (SLAC). The Promise of X-ray FELs. Ultra-bright. Ultra-fast. Single Molecule Imaging with Intense fs X-ray. R. Neutze et al. Nature, 2000 . Introduction.

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The Collegiate Learning Assessment (CLA)

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Chapter 7 Random-Number Generation

Chapter 7 Random-Number Generation. Banks, Carson, Nelson & Nicol Discrete-Event System Simulation. Purpose & Overview. Discuss the generation of random numbers. Introduce the subsequent testing for randomness: Frequency test Autocorrelation test. Properties of Random Numbers.

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How and Why Do I Choose Chaotic Cryptography as the Topic of My Dissertation

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Session 3, Unit 5 Dispersion Modeling

Session 3, Unit 5 Dispersion Modeling. The Box Model. Description and assumption Box model For line source with line strength of Q L Example. A More Realistic but Simple Approach. Basic assumption: Time averaged concentration is proportional to source strength

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Chapter 9

Chapter 9. Adaptive Filters. Objectives. Show and describe the structure of the discrete Wiener filter. Derive the statistical requirement for optimal estimation of a signal component using the discrete Wiener filter.

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Standard Error of the Mean

Standard Error of the Mean. This equation implies that sampling error decreases as sample size increases. This is important because it suggests that if we want to make sampling error as small as possible, we need to use as large of a sample size as we can manage. Standard Error of the Mean.

5.54k views • 20 slides

Statistical approaches to analyse interval-censored data in a confirmatory trial

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Hedge Fund Conference Kellogg School of Mgmt

Hedge Fund Conference Kellogg School of Mgmt. Roundtable Discussion Hedge Fund Performance Evaluation Lawrence R. Glosten Columbia University. The academic approach. Portfolio manager provides excess return (over the risk free rate) X pt in period t These returns are modeled as:

299 views • 10 slides