'Y1 y2 y3' presentation slideshows

829 views • 68 slides

15-16: Inter and intra AS, RIP, OSPF, BGP, Router Architecture

1.43k views • 56 slides

Outline

Outline Network Layer Routing Principles Link State Algorithm Distance Vector Algorithm Hierarchical Routing The Internet (IP) Protocol IPv4 addressing Moving a datagram from source to destination Datagram format IP fragmentation ICMP: Internet Control Message Protocol

900 views • 52 slides

WHAT IS S TRUCTURAL E QUATION M ODELING ( SEM )?

696 views • 43 slides

Multidimensional Scaling

Multidimensional Scaling. Agenda. Multidimensional Scaling Goodness of fit measures Nosofsky, 1986. Proximities. p Amherst, Hadley. Configuration (in 2-D). x i. Configuration (in 1-D). Formal MDS Definition. f: p ij ?d ij ( X )

764 views • 29 slides

Compiler Design 5 . Top-Down Parsing with a Recursive Descent Parser

Kanat Bolazar February 2, 2010. Compiler Design 5 . Top-Down Parsing with a Recursive Descent Parser. Parsing. Lexical Analyzer has translated the source program into a sequence of tokens The Parser must translate the sequence of tokens into an intermediate representation

435 views • 20 slides

????? ??????

????? ??????. ????????????. y=. ? ?. ??. 1. ????????? ??? ;. 2. ????????. K>0. K<0. ? k ? 0 ?????? ????????? ??? ?????? ???? y ? x ??? ???. ? k ? 0 ?????? ????????? ??? ?????? ???? y ? x ??? ???. 1. ?? ? ??????? ??? k= ???? x ?????? . 2. ?? ?????? ?? ,

301 views • 17 slides

WOOD 492 MODELLING FOR DECISION SUPPORT

WOOD 492 MODELLING FOR DECISION SUPPORT. Lecture 12 Duality Theory. Quiz 3. A multi period production plan Maximize revenue Limited production capacity Limited storage capacity Seasonal demand Storage costs. Quiz3 matrix. The Dual model.

235 views • 14 slides

WOOD 492 MODELLING FOR DECISION SUPPORT

WOOD 492 MODELLING FOR DECISION SUPPORT. Lecture 13 Duality Theory. The Dual Problem. Another way of looking at a linear program Has the same optimal value for the objective function as the primal model

214 views • 12 slides

Fuzzy Logic ToolKit Demo

Fuzzy Logic ToolKit Demo. Avishek Ghosh. After executing builder.sce and loader.sce. Trapezoidal Fuzzification. x=linspace(0,1,100)'; y1=trapmf(x,[0 0.2 0.4 0.6]); y2=trapmf(x,[0.2 0.5 0.6 0.9]); y3=trapmf(x,[0.5 0.6 0.8 0.9 ]); xbasc(); plot2d(x,[y1 y2 y3],leg="y1@y2@y3");

221 views • 6 slides