'1 length' diaporamas de présentation

Introduction to Algorithm Analysis Concepts

Introduction to Algorithm Analysis Concepts. 15-211 Fundamental Data Structures and Algorithms. Peter Lee January 15, 2004. Plan. Today Introduction to some basic concepts in the design of data structures Reading: For today: Chapter 5 and 7.1-7.3

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21. Working with Data Files

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Eamonn Keogh eamonn@cs.ucr

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LISP Data Types Functional Programming

LISP Data Types Functional Programming. Academic Year 2005-2006 Alessandro Cimatti cimatti@itc.it. LISP: basic data types. Everything is a symbolic expression Symbolic expressions can be Atoms Numbers Symbols Lists

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L25. Working with Sound Files

L25. Working with Sound Files. wavread sound wavwrite. Reading and Playing. [y,rate,nBits] = wavread(‘noCry.wav’) sound(y,rate). How is audio information encoded?. We will work with .wav files. Discrete vs Continuous. Sound is continuous. Capture its essence by sampling.

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LaValle Chapter 2 (Sections 2.1-2.3)

LaValle Chapter 2 (Sections 2.1-2.3). [2.1] Discrete feasible planning formulation [2.2] Basic search techniques To find discrete feasible plans But occasionally even to find optimal plans [2.3] Discrete optimal planning Fixed length Unspecified length. Discrete Feasible Planning.

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Loops II

Loops II. For Loop. For <index variable> = <vector of values> execute statements for each value of index end for x = [1 4 7 9] disp(num2str(x^2)); end 1 16 49 81. Drawing a Line. for cX = [10 11 12 13 14 15 16 17 18 19 20] putPixel(cX, 10, g) end a better way?.

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Properties of discrete-time Fourier transform

Properties of discrete-time Fourier transform. (1) Linearity. (2) Time shifting. (3) Time reversal. (4) Time scaling. if n is a multiple of k. otherwise. (4) Time scaling. clear; clf ; N = 5; x(1:N) = 1; r = 3; Gn = floor(N/r); for k = 1:N*r gn = floor(k/r); if k/r == gn

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CS3: Lecture 8 Advanced recursion

CS3: Lecture 8 Advanced recursion. Schedule. Next lab: Catch-up day. Number Spelling miniproject. Read Simply Scheme , page 233, which has hints Another hint (principle): don't force "everything" into the recursion.

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Radon Transform

Radon Transform. R98229029 CHC. 2-D Radon Transform. R = radon(I, theta) returns the Radon transform R of the intensity image I for the angle theta degrees. 2-D Radon Transform. 2-D Radon Transform. 2-D Radon Transform. 2-D Radon Transform. 3-D Radon Transform. 3-D Radon Transform.

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Energy-aware strategies for environmental monitoring with the MICAz

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Lec 13 Oct 17 cell arrays structures

Lec 13 Oct 17 cell arrays structures advanced recursive programs. Cell arrays suppose we want to represent a collection of sets such as: {1, 2, 4}, {3, 4, 6}, {7, 8} Each set can be represented by vector:

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LING 388: Language and Computers

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The response of system to complex exponentials

The response of system to complex exponentials. z - transform. The response of system to complex exponentials. Laplace transform. The response of system to complex exponentials. Fourier series representation of continuous-time periodical signal. Periodic signal. for all t. e.g.

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2-D Arrays (Matrices)

2-D Arrays (Matrices). Creating 2-D Arrays. m = [ 11 12 13 21 22 23 31 32 33]; or >> m = [11 12 13; 21 22 23; 31 32 33] m = 11 12 13 21 22 23 31 32 33. Accessing Elements. >> m(2, 1) ans = 21 >> m(2, 3) ans = 23 >> m(4, 1)

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Magnitude-phase representation of Fourier Transform

Magnitude-phase representation of Fourier Transform. Magnitude-phase representation of frequency response of LTI systems. Ignore reflection at both interfaces. Propagation constant. ? Is linear with ?. gives the group delay t 0. represents the group velocity. ? Is linear with ?.

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screws in delhi

RKC is one of the leading Importers/Exporters and Suppliers of Industrial fasteners in Delhi. With 35 Years' experience in trading of fasteners in Delhi,Rajender Kumar

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VSH, an efficient and provable collision resistant hash function

VSH, an efficient and provable collision resistant hash function. Scott Contini 1 , Arjen K. Lenstra 2 , Ron Steinfeld 1 1 Macquarie University 2 Lucent Technologies Bell Laboratories, Technical Univ. Eindhoven. As usual in crypto, we cheat. Efficient means:

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% p = adep('FUN','-opt') % p = adep(p,'-opt') % a wrapper for ML's <depfun>

% p = adep('FUN','-opt') % p = adep(p,'-opt') % a wrapper for ML's <depfun> % - returns struct <p>, which can be reused for display % - useful to determine which user defined modules must % be included in a distribution % % opt parameters comment

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