확률 및 랜덤변수 hw2

소개글

아주대 확률 및 랜덤변수

목차

1. Simulate an exponential random variable with CDF as follows:

2. Relationship of exponential and Gaussian distributions:

< 참고문헌 >

본문내용

help rand
RAND Uniformly distributed pseudo-random numbers.
R = RAND(N) returns an N-by-N matrix containing pseudo-random values
drawn from a uniform distribution on the unit interval.
RAND(M,N) or RAND([M,N]) returns an M-by-N matrix.
RAND(M,N,P,...) or RAND([M,N,P,...]) returns an M-by-N-by-P-by-... array.
RAND with no arguments returns a scalar.
RAND(SIZE(A)) returns an array the same size as A.

help histfit
HISTFIT Histogram with superimposed fitted normal density.
HISTFIT(DATA,NBINS) plots a histogram of the values in the vector DATA.
using NBINS bars in the histogram.
With one input argument,
NBINS is set to the square root of the number of elements in DATA.
H = HISTFIT(DATA,NBINS) returns a vector of handles to the plotted lines.
H(1) is a handle to the histogram, H(2) is a handle to the density curve.

참고 자료

Probability, Random Variables and Random Signal Processing, P.Z. Peebles Jr.,
McGraw-Hill, 4th ed, 2001.
MATLAB 객체 지향 프로그래밍 언어, 박전수 역, 아진, 2008.